edit_intent_classification.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "celltoolbar": "Tags",
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.6"
    },
    "colab": {
      "name": "edit_intent_classification.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "ULADFGeEF_K0",
        "vEQIGePtAFTl",
        "2lGXXHulAFUB"
      ]
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "7eQkbD7OflXc",
        "colab_type": "code",
        "outputId": "cefcb446-2a1e-4895-b7a9-be560f9f3b23",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 229,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kLFcVjM2AFR1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "12468bed-f396-46d6-f7ee-32ba926298f6"
      },
      "source": [
        "%load_ext autoreload\n",
        "%autoreload 2"
      ],
      "execution_count": 230,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The autoreload extension is already loaded. To reload it, use:\n",
            "  %reload_ext autoreload\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AXdE4-nvAMqO",
        "colab_type": "code",
        "outputId": "5c269b81-3474-4da6-94f1-43d1875080fe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 177
        }
      },
      "source": [
        "!pip install overrides"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting overrides\n",
            "  Downloading https://files.pythonhosted.org/packages/72/dd/ac49f9c69540d7e09210415801a05d0a54d4d0ca8401503c46847dacd3a0/overrides-2.8.0.tar.gz\n",
            "Building wheels for collected packages: overrides\n",
            "  Building wheel for overrides (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for overrides: filename=overrides-2.8.0-cp36-none-any.whl size=5609 sha256=703eb6f1435aabbc87d37b54915fa797353fd057d0ffccb39c03bfd4be233468\n",
            "  Stored in directory: /root/.cache/pip/wheels/df/f1/ba/eaf6cd7d284d2f257dc71436ce72d25fd3be5a5813a37794ab\n",
            "Successfully built overrides\n",
            "Installing collected packages: overrides\n",
            "Successfully installed overrides-2.8.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OJL8IkCgAUEI",
        "colab_type": "code",
        "outputId": "b5103988-7818-46a2-c416-05598d1ec2d6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "!pip install allennlp"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting allennlp\n",
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            "Collecting responses>=0.7\n",
            "  Downloading https://files.pythonhosted.org/packages/3e/0c/940781dd49710f4b1f0650c450c9fd8491db0e1bffd99ebc36355607f96d/responses-0.10.9-py2.py3-none-any.whl\n",
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            "\u001b[?25hCollecting flask-cors>=3.0.7\n",
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            "Collecting tensorboardX>=1.2\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/35/f1/5843425495765c8c2dd0784a851a93ef204d314fc87bcc2bbb9f662a3ad1/tensorboardX-2.0-py2.py3-none-any.whl (195kB)\n",
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            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/33/b8/a8588d4010f13716a324f55d23999259bad9db2320f4fe919a66b2f651f3/jsonnet-0.15.0.tar.gz (255kB)\n",
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            "Building wheels for collected packages: numpydoc, ftfy, parsimonious, word2number, jsonnet\n",
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            "  Stored in directory: /root/.cache/pip/wheels/57/63/2e/da89cfe1ba08550bd7262d5d9c027edc313980c3b85b3b0a38\n",
            "Successfully built numpydoc ftfy parsimonious word2number jsonnet\n",
            "Installing collected packages: unidecode, numpydoc, ftfy, pytorch-pretrained-bert, responses, parsimonious, flask-cors, flaky, word2number, tensorboardX, jsonpickle, conllu, jsonnet, sentencepiece, pytorch-transformers, allennlp\n",
            "Successfully installed allennlp-0.9.0 conllu-1.3.1 flaky-3.6.1 flask-cors-3.0.8 ftfy-5.7 jsonnet-0.15.0 jsonpickle-1.3 numpydoc-0.9.2 parsimonious-0.8.1 pytorch-pretrained-bert-0.6.2 pytorch-transformers-1.1.0 responses-0.10.9 sentencepiece-0.1.85 tensorboardX-2.0 unidecode-1.1.1 word2number-1.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bR_xNtnmAFR7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from pathlib import Path\n",
        "from typing import *\n",
        "import torch\n",
        "import torch.optim as optim\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from functools import partial\n",
        "from overrides import overrides\n",
        "\n",
        "from allennlp.data import Instance\n",
        "from allennlp.data.token_indexers import TokenIndexer\n",
        "from allennlp.data.tokenizers import Token\n",
        "from allennlp.nn import util as nn_util"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BaadHIFPAFR-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class Config(dict):\n",
        "    def __init__(self, **kwargs):\n",
        "        super().__init__(**kwargs)\n",
        "        for k, v in kwargs.items():\n",
        "            setattr(self, k, v)\n",
        "    \n",
        "    def set(self, key, val):\n",
        "        self[key] = val\n",
        "        setattr(self, key, val)\n",
        "        \n",
        "config = Config(\n",
        "    testing=True,\n",
        "    seed=1,\n",
        "    batch_size=32,\n",
        "    lr=3e-4,\n",
        "    epochs=5,\n",
        "    hidden_sz=64,\n",
        "    max_seq_len=360, # necessary to limit memory usage\n",
        "    max_vocab_size=100000,\n",
        ")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ULkbW0uvAFSA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from allennlp.common.checks import ConfigurationError\n",
        "USE_GPU = torch.cuda.is_available()\n",
        "DATA_ROOT = Path(\"src\") / \"\"\n",
        "USE_GPU"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6Y79W7GfAFSL",
        "colab_type": "text"
      },
      "source": [
        "Set random seed manually to replicate results"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FIgGc_8LAFSM",
        "colab_type": "code",
        "outputId": "85a68153-86f1-42a1-8941-12fd736955a9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "torch.manual_seed(config.seed)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<torch._C.Generator at 0x7f105c898db0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZGDXmpbNAFSP",
        "colab_type": "code",
        "outputId": "cb110c3d-5dff-45a6-dcd3-1419e79a627f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "cd 'drive/My Drive/Brown Datathon/'"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/My Drive/Brown Datathon\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PB7sAc_zhleG",
        "colab_type": "code",
        "outputId": "08fa7029-310b-44c5-ee2b-19ce87a96ad2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "cd 'Wiki_Semantic_Intention'"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/My Drive/Brown Datathon/Wiki_Semantic_Intention\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "beAwUeq2AFSR",
        "colab_type": "text"
      },
      "source": [
        "# Load Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4eObD_zfAFSS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from allennlp.data.vocabulary import Vocabulary\n",
        "from allennlp.data.dataset_readers import DatasetReader"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gKS1lA_sAFSV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "#Splitting to train on Amazon MTurk & 3rd party Edit Intent Dataset and validate on MTurn dataset\n",
        "\n",
        "df1 = pd.read_csv('ps_pe_data2.csv')\n",
        "trdata1, tedata1 = train_test_split(df1, train_size=0.8)\n",
        "df2 = pd.read_csv('ps_pe_4.csv')\n",
        "df = df2.append(trdata1)\n",
        "trdata, tedata = df, tedata1"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4cUWMRgyDUrb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b8BQUILFAFSX",
        "colab_type": "text"
      },
      "source": [
        "### Prepare dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "srQtNqRiAFSX",
        "colab_type": "code",
        "outputId": "0ff93c51-776f-4a2c-c0fc-f20758c39ba2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 55
        }
      },
      "source": [
        "label_cols = df['label'].unique().tolist()\n",
        "print(label_cols)\n",
        "\n",
        "id2labels = {}\n",
        "for idx,i in enumerate(label_cols):\n",
        "    id2labels[i] = idx "
      ],
      "execution_count": 378,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['Elaboration(insert a fact or new meaningful assertion, update numbers, dates, scores etc)', 'Copy Editing(Rephrase without changing meaning,  improve grammar etc)', 'Wikification ( formating style, adding or removing links etc)', 'Adding spammy, useless or derogatory content', 'Other']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "marZKc-kAFSZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from allennlp.data.fields import TextField, MetadataField, ArrayField\n",
        "\n",
        "class IntentClsDatasetReader(DatasetReader):\n",
        "    def __init__(self, tokenizer: Callable[[str], List[str]]=lambda x: x.split(),\n",
        "                 token_indexers: Dict[str, TokenIndexer] = None,\n",
        "                 max_seq_len: Optional[int]=config.max_seq_len) -> None:\n",
        "        super().__init__(lazy=False)\n",
        "        self.tokenizer = tokenizer\n",
        "        self.token_indexers = token_indexers or {\"tokens\": SingleIdTokenIndexer()}\n",
        "        self.max_seq_len = max_seq_len\n",
        "\n",
        "    @overrides\n",
        "    def text_to_instance(self, tokens: List[Token], id: str=None,\n",
        "                         labels: np.ndarray=None) -> Instance:\n",
        "        sentence_field = TextField(tokens, self.token_indexers)\n",
        "        fields = {\"sentence_tokens\": sentence_field}\n",
        "        \n",
        "        id_field = MetadataField(id)\n",
        "        fields[\"id\"] = id_field\n",
        "        \n",
        "        labels = np.asarray([labels])\n",
        "        label_field = ArrayField(array=labels)\n",
        "        fields[\"label\"] = label_field\n",
        "\n",
        "        return Instance(fields)\n",
        "    \n",
        "    @overrides\n",
        "    def _read(self, df: str) -> Iterator[Instance]:\n",
        "        #df = pd.read_csv(file_path)\n",
        "        #if config.testing: df = df.head(1000)\n",
        "        for i, row in df.iterrows():\n",
        "            yield self.text_to_instance(\n",
        "                [Token(x) for x in self.tokenizer(\"[CLS]\"+row[\"edited_sentence\"]+'[PSTR]'+row['phrase']+'[PEND]')],\n",
        "                i, id2labels[row['label']],\n",
        "            )"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dKLKbLI5AFSg",
        "colab_type": "text"
      },
      "source": [
        "### Prepare token handlers"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FQSHmnZMAFSh",
        "colab_type": "text"
      },
      "source": [
        "We will use the spacy tokenizer here"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gKhpQBUeAFSi",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from allennlp.data.token_indexers import PretrainedBertIndexer\n",
        "\n",
        "token_indexer = PretrainedBertIndexer(\n",
        "    pretrained_model=\"bert-base-uncased\",\n",
        "    max_pieces=config.max_seq_len,\n",
        "    do_lowercase=True,\n",
        " )"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IQa2lZJGE1y4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from pytorch_pretrained_bert.tokenization import BertTokenizer\n",
        "bert_tokenizer_obj = BertTokenizer.from_pretrained(\"bert-base-uncased\", do_lower_case=True)\n",
        "\n",
        "def bert_tokenizer(s: str):\n",
        "    if type(s) == str:\n",
        "      tokens = bert_tokenizer_obj.basic_tokenizer.tokenize(s)[:360]\n",
        "    else:\n",
        "      tokens = ['[UNK]']\n",
        "    return tokens"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RO00toX0AFSk",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "reader = IntentClsDatasetReader(\n",
        "    tokenizer=bert_tokenizer,\n",
        "    token_indexers={\"tokens\": token_indexer}\n",
        ")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_6T1W-TnAFSm",
        "colab_type": "code",
        "outputId": "8fe5e1b5-26dd-4b3e-ac7b-5caa21e6e033",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "train_ds = [reader.read(trdata)][0]\n",
        "val_ds = None"
      ],
      "execution_count": 384,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "5237it [00:35, 147.56it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MMkXXIVcAFS1",
        "colab_type": "text"
      },
      "source": [
        "### Prepare vocabulary"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z9LgCj09AFS1",
        "colab_type": "text"
      },
      "source": [
        "We don't need to build the vocab: all that is handled by the token indexer"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "13P8Orp4AFS2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "vocab = Vocabulary()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ow325C5fAFS6",
        "colab_type": "text"
      },
      "source": [
        "### Prepare iterator"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pN0moqbXAFS6",
        "colab_type": "text"
      },
      "source": [
        "The iterator is responsible for batching the data and preparing it for input into the model. We'll use the BucketIterator that batches text sequences of smilar lengths together."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lZI5vKxJAFS7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from allennlp.data.iterators import BasicIterator, BucketIterator"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kXu1a84AAFS-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "iterator = BasicIterator(batch_size=config.batch_size)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Kplhj78AFTA",
        "colab_type": "text"
      },
      "source": [
        "We need to tell the iterator how to numericalize the text data. We do this by passing the vocabulary to the iterator. This step is easy to forget so be careful! "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hTjDow4lAFTA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "iterator.index_with(vocab)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CNNILZueAFTT",
        "colab_type": "text"
      },
      "source": [
        "# Prepare Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ugyYUSysAFTT",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SkPBnM0wAFTW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from allennlp.modules.seq2vec_encoders import Seq2VecEncoder, PytorchSeq2VecWrapper\n",
        "from allennlp.nn.util import get_text_field_mask\n",
        "from allennlp.models import Model\n",
        "from allennlp.modules.text_field_embedders import TextFieldEmbedder\n",
        "import torch.nn\n",
        "\n",
        "class Attn(nn.Module):\n",
        "    def __init__(self, method, hidden_size):\n",
        "        super(Attn, self).__init__()\n",
        "        \n",
        "        self.method = method\n",
        "        self.hidden_size = hidden_size\n",
        "        \n",
        "        if self.method == 'general':\n",
        "            self.attn = nn.Linear(self.hidden_size, hidden_size)\n",
        "\n",
        "        elif self.method == 'concat':\n",
        "            self.attn = nn.Linear(self.hidden_size * 2, hidden_size)\n",
        "            self.other = nn.Parameter(torch.FloatTensor(1, hidden_size))\n",
        "\n",
        "    def forward(self, hidden, encoder_outputs, l1, l2):\n",
        "        seq_len = len(encoder_outputs)\n",
        "\n",
        "        attn_energies = self.score(hidden, encoder_outputs)\n",
        "        s_mask = attn_energies.data.new(*attn_energies.size()).fill_(1).byte()  # [B, T1, T2]\n",
        "        # Init similarity mask using lengths\n",
        "        for i, (l_1, l_2) in enumerate(zip(l1, l2)):\n",
        "            s_mask[i][:l_1, :l_2] = 0\n",
        "\n",
        "        attn_energies.data.masked_fill_(s_mask.byte(), -math.inf)\n",
        "        attn_energies = F.softmax(attn_energies)\n",
        "        attn_energies.data.masked_fill_(attn_energies.data != attn_energies.data, 0)\n",
        "        return attn_energies\n",
        "    \n",
        "    def score(self, hidden, encoder_output):\n",
        "        \n",
        "        if self.method == 'dot':\n",
        "            energy = hidden.dot(encoder_output)\n",
        "            return energy\n",
        "        \n",
        "        elif self.method == 'general':\n",
        "            energy = self.attn(encoder_output)\n",
        "            energy = torch.bmm(hidden,energy.transpose(1,2))\n",
        "            return energy\n",
        "        \n",
        "        elif self.method == 'concat':\n",
        "            energy = self.attn(torch.cat((hidden, encoder_output), 1))\n",
        "            energy = self.other.dot(energy)\n",
        "            return energy\n",
        "\n",
        "class BaselineModel(nn.Module):\n",
        "    def __init__(self,\n",
        "                 rnn_size_in=(1024 + 300, 1024 + 300),\n",
        "                 rnn_size_out=(300, 300), max_l=150,\n",
        "                 mlp_d=300, num_of_class=3, drop_r=0.5, activation_type='relu'):\n",
        "        super(BaselineModel, self).__init__()\n",
        "        self.dropout_layer = nn.Dropout(drop_r)\n",
        "\n",
        "        self.lstm_1 = nn.LSTM(input_size=rnn_size_in[0], hidden_size=rnn_size_out[0],\n",
        "                              num_layers=1, bidirectional=True, batch_first=True)\n",
        "\n",
        "        self.lstm_2 = nn.LSTM(input_size=rnn_size_in[1], hidden_size=rnn_size_out[1],\n",
        "                              num_layers=1, bidirectional=True, batch_first=True)\n",
        "\n",
        "        self.attn = Attn('general', rnn_size_out[0] * 2)\n",
        "        self.projection = nn.Linear(rnn_size_out[0] * 2 * 2, rnn_size_out[0])\n",
        "        \n",
        "        self.max_l = max_l\n",
        "        self.bidaf = biDafAttn(300)\n",
        "\n",
        "        self.mlp_1 = nn.Linear(rnn_size_out[1] * 2, mlp_d)\n",
        "        self.sm = nn.Linear(mlp_d, num_of_class)\n",
        "\n",
        "        if activation_type == 'relu':\n",
        "            activation = nn.ReLU()\n",
        "        elif activation_type == 'tanh':\n",
        "            activation = nn.Tanh()\n",
        "        else:\n",
        "            raise ValueError(\"Not a valid activation!\")\n",
        "\n",
        "        self.classifier = nn.Sequential(*[nn.Dropout(drop_r), self.mlp_1, activation, nn.Dropout(drop_r), self.sm])\n",
        "    \n",
        "    def forward(self, layer1_s1, layer2_s1, l1):\n",
        "        p_s1 = self.dropout_layer(layer1_s1)\n",
        "        \n",
        "        tot_len1 = layer1_s1.size(1)\n",
        "        s1_layer1_out = auto_rnn(self.lstm_1, p_s1, l1, tot_len=tot_len1)\n",
        "        \n",
        "        S = self.bidaf.similarity(s1_layer1_out, l1, s1_layer1_out, l1)\n",
        "        \n",
        "        a_weight = F.softmax(S, dim=2)  # [B, t1, t2]\n",
        "        a_weight.data.masked_fill_(a_weight.data != a_weight.data, 0)  # remove nan from softmax on -inf\n",
        "\n",
        "        s1_att, s2_att = self.bidaf.get_both_tile(S, s1_layer1_out, s1_layer1_out)\n",
        "\n",
        "        s1_coattentioned = torch.cat([s1_layer1_out, s1_att], dim=2)\n",
        "\n",
        "        #Luong Attention\n",
        "        '''attn_weights = self.attn(s1_layer1_out, s1_layer1_out, l1, l1)\n",
        "        s1_layer1_outcontext = attn_weights.bmm(s1_layer1_out)\n",
        "        \n",
        "        s1_coattentioned = torch.cat([s1_layer1_out, s1_layer1_outcontext], dim=2)'''\n",
        "        \n",
        "        p_s1_coattentioned = F.relu(self.projection(s1_coattentioned))\n",
        "        \n",
        "        s1_coatt_features = torch.cat([p_s1_coattentioned, layer2_s1], dim=2)\n",
        "        \n",
        "        s1_coatt_features = self.dropout_layer(s1_coatt_features)\n",
        "\n",
        "        s1_layer2_out = auto_rnn(self.lstm_2, s1_coatt_features, l1, tot_len=s1_coatt_features.size(1))\n",
        "        s1_lay2_maxout = max_along_time(s1_layer2_out, l1)\n",
        "        \n",
        "        return self.classifier(s1_lay2_maxout), a_weight"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2JWtPWoDF5bj",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ULADFGeEF_K0",
        "colab_type": "text"
      },
      "source": [
        "# Torch util"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DQcSm2jdNdkK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "from torch import nn\n",
        "import torch.nn.functional as F\n",
        "import math\n",
        "\n",
        "\n",
        "class biDafAttn(nn.Module):\n",
        "    def __init__(self, channel_size):\n",
        "        super(biDafAttn, self).__init__()\n",
        "        \"\"\"\n",
        "        This method do biDaf from s2 to s1:\n",
        "            The return value will have the same size as s1.\n",
        "        :param channel_size: Hidden size of the input\n",
        "        \"\"\"\n",
        "\n",
        "    def similarity(self, s1, l1, s2, l2, masked=True):\n",
        "        \"\"\"\n",
        "        :param s1: [B, t1, D]\n",
        "        :param l1: [B]\n",
        "        :param s2: [B, t2, D]\n",
        "        :param l2: [B]\n",
        "        :return:\n",
        "        \"\"\"\n",
        "        batch_size = s1.size(0)\n",
        "        t1 = s1.size(1)\n",
        "        t2 = s2.size(1)\n",
        "        S = torch.bmm(s1, s2.transpose(1, 2))\n",
        "        # [B, t1, D] * [B, D, t2] -> [B, t1, t2] S is the similarity matrix from biDAF paper. [B, T1, T2]\n",
        "\n",
        "        if masked:\n",
        "            s_mask = S.data.new(*S.size()).fill_(1).byte()  # [B, T1, T2]\n",
        "            # Init similarity mask using lengths\n",
        "            for i, (l_1, l_2) in enumerate(zip(l1, l2)):\n",
        "                s_mask[i][:l_1, :l_2] = 0\n",
        "\n",
        "            S.data.masked_fill_(s_mask.byte(), -math.inf)\n",
        "        return S\n",
        "\n",
        "    def get_U_tile(self, S, s2):\n",
        "        a_weight = F.softmax(S, dim=2)  # [B, t1, t2]\n",
        "        a_weight.data.masked_fill_(a_weight.data != a_weight.data, 0)  # remove nan from softmax on -inf\n",
        "        U_tile = torch.bmm(a_weight, s2)  # [B, t1, t2] * [B, t2, D] -> [B, t1, D]\n",
        "        return U_tile\n",
        "\n",
        "    def get_V_tile(self, S, s1):\n",
        "        a1_weight = F.softmax(S, dim=1)  # [B, t1, t2]\n",
        "        a1_weight.data.masked_fill_(a1_weight.data != a1_weight.data, 0)  # remove nan from softmax on -inf\n",
        "        U1_tile = torch.bmm(a1_weight.transpose(1, 2), s1)  # [B, t2, t1] * [B, t1, D] -> [B, t2, D]\n",
        "        return U1_tile\n",
        "\n",
        "    def get_both_tile(self, S, s1, s2, retweight=False):\n",
        "        a_weight = F.softmax(S, dim=2)  # [B, t1, t2]\n",
        "        a_weight.data.masked_fill_(a_weight.data != a_weight.data, 0)  # remove nan from softmax on -inf\n",
        "        U_tile = torch.bmm(a_weight, s2)  # [B, t1, t2] * [B, t2, D] -> [B, t1, D]\n",
        "\n",
        "        a1_weight = F.softmax(S, dim=1)  # [B, t1, t2]\n",
        "        a1_weight.data.masked_fill_(a1_weight.data != a1_weight.data, 0)  # remove nan from softmax on -inf\n",
        "        U1_tile = torch.bmm(a1_weight.transpose(1, 2), s1)  # [B, t2, t1] * [B, t1, D] -> [B, t2, D]\n",
        "        if not retweight:\n",
        "            return U_tile, U1_tile\n",
        "        else:\n",
        "            return U_tile, U1_tile, a1_weight\n",
        "\n",
        "    def forward(self, s1, l1, s2, l2):\n",
        "        S = self.similarity(s1, l1, s2, l2)\n",
        "        U_tile = self.get_U_tile(S, s2)\n",
        "        return U_tile"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E3hICR--F5tB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "from torch.autograd import Variable\n",
        "import numpy as np\n",
        "import functools\n",
        "\n",
        "from allennlp.nn.util import get_lengths_from_binary_sequence_mask\n",
        "\n",
        "\n",
        "def get_length_and_mask(seq):\n",
        "    len_mask = (seq != 0).long()\n",
        "    len_t = get_lengths_from_binary_sequence_mask(len_mask)\n",
        "    return len_mask, len_t\n",
        "\n",
        "\n",
        "def length_truncate(seq, max_l, is_elmo=False):\n",
        "    def _truncate(seq):\n",
        "        if seq.size(1) > max_l:\n",
        "            return seq[:, :max_l, ...]\n",
        "        else:\n",
        "            return seq\n",
        "\n",
        "    if not is_elmo:\n",
        "        return _truncate(seq)\n",
        "    else:\n",
        "        s1_elmo_embd = dict()\n",
        "        s1_elmo_embd['mask'] = _truncate(seq['mask'])\n",
        "        s1_elmo_embd['elmo_representations'] = []\n",
        "        for e_rep in seq['elmo_representations']:\n",
        "            s1_elmo_embd['elmo_representations'].append(_truncate(e_rep))\n",
        "        return s1_elmo_embd\n",
        "\n",
        "\n",
        "def pad_1d(seq, pad_l):\n",
        "    \"\"\"\n",
        "    The seq is a sequence having shape [T, ..]. Note: The seq contains only one instance. This is not batched.\n",
        "    \n",
        "    :param seq:  Input sequence with shape [T, ...]\n",
        "    :param pad_l: The required pad_length.\n",
        "    :return:  Output sequence will have shape [Pad_L, ...]\n",
        "    \"\"\"\n",
        "    l = seq.size(0)\n",
        "    if l >= pad_l:\n",
        "        return seq[:pad_l, ]  # Truncate the length if the length is bigger than required padded_length.\n",
        "    else:\n",
        "        pad_seq = Variable(seq.data.new(pad_l - l, *seq.size()[1:]).zero_())  # Requires_grad is False\n",
        "        return torch.cat([seq, pad_seq], dim=0)\n",
        "\n",
        "\n",
        "def get_state_shape(rnn: nn.RNN, batch_size, bidirectional=False):\n",
        "    \"\"\"\n",
        "    Return the state shape of a given RNN. This is helpful when you want to create a init state for RNN.\n",
        "\n",
        "    Example:\n",
        "    c0 = h0 = Variable(src_seq_p.data.new(*get_state_shape([your rnn], 3, bidirectional)).zero_())\n",
        "    \n",
        "    :param rnn: nn.LSTM, nn.GRU or subclass of nn.RNN\n",
        "    :param batch_size:  \n",
        "    :param bidirectional:  \n",
        "    :return: \n",
        "    \"\"\"\n",
        "    if bidirectional:\n",
        "        return rnn.num_layers * 2, batch_size, rnn.hidden_size\n",
        "    else:\n",
        "        return rnn.num_layers, batch_size, rnn.hidden_size\n",
        "\n",
        "\n",
        "def pack_list_sequence(inputs, l, max_l=None, batch_first=True):\n",
        "    \"\"\"\n",
        "    Pack a batch of Tensor into one Tensor with max_length.\n",
        "    :param inputs: \n",
        "    :param l: \n",
        "    :param max_l: The max_length of the packed sequence.\n",
        "    :param batch_first: \n",
        "    :return: \n",
        "    \"\"\"\n",
        "    batch_list = []\n",
        "    max_l = max(list(l)) if not max_l else max_l\n",
        "    batch_size = len(inputs)\n",
        "\n",
        "    for b_i in range(batch_size):\n",
        "        batch_list.append(pad_1d(inputs[b_i], max_l))\n",
        "    pack_batch_list = torch.stack(batch_list, dim=1) if not batch_first \\\n",
        "        else torch.stack(batch_list, dim=0)\n",
        "    return pack_batch_list\n",
        "\n",
        "\n",
        "def pack_for_rnn_seq(inputs, lengths, batch_first=True, states=None):\n",
        "    \"\"\"\n",
        "    :param states: [rnn.num_layers, batch_size, rnn.hidden_size]\n",
        "    :param inputs: Shape of the input should be [B, T, D] if batch_first else [T, B, D].\n",
        "    :param lengths:  [B]\n",
        "    :param batch_first: \n",
        "    :return: \n",
        "    \"\"\"\n",
        "    if not batch_first:\n",
        "        _, sorted_indices = lengths.sort()\n",
        "        '''\n",
        "            Reverse to decreasing order\n",
        "        '''\n",
        "        r_index = reversed(list(sorted_indices))\n",
        "\n",
        "        s_inputs_list = []\n",
        "        lengths_list = []\n",
        "        reverse_indices = np.zeros(lengths.size(0), dtype=np.int64)\n",
        "\n",
        "        for j, i in enumerate(r_index):\n",
        "            s_inputs_list.append(inputs[:, i, :].unsqueeze(1))\n",
        "            lengths_list.append(lengths[i])\n",
        "            reverse_indices[i] = j\n",
        "\n",
        "        reverse_indices = list(reverse_indices)\n",
        "\n",
        "        s_inputs = torch.cat(s_inputs_list, 1)\n",
        "        packed_seq = nn.utils.rnn.pack_padded_sequence(s_inputs, lengths_list)\n",
        "\n",
        "        return packed_seq, reverse_indices\n",
        "\n",
        "    else:\n",
        "        _, sorted_indices = lengths.sort()\n",
        "        '''\n",
        "            Reverse to decreasing order\n",
        "        '''\n",
        "        r_index = reversed(list(sorted_indices))\n",
        "\n",
        "        s_inputs_list = []\n",
        "        lengths_list = []\n",
        "        reverse_indices = np.zeros(lengths.size(0), dtype=np.int64)\n",
        "\n",
        "        if states is None:\n",
        "            states = ()\n",
        "        elif not isinstance(states, tuple):\n",
        "            states = (states,)  # rnn.num_layers, batch_size, rnn.hidden_size\n",
        "\n",
        "        states_lists = tuple([] for _ in states)\n",
        "\n",
        "        for j, i in enumerate(r_index):\n",
        "            s_inputs_list.append(inputs[i, :, :])\n",
        "            lengths_list.append(lengths[i])\n",
        "            reverse_indices[i] = j\n",
        "\n",
        "            for state_list, state in zip(states_lists, states):\n",
        "                state_list.append(state[:, i, :].unsqueeze(1))\n",
        "\n",
        "        reverse_indices = list(reverse_indices)\n",
        "\n",
        "        s_inputs = torch.stack(s_inputs_list, dim=0)\n",
        "        packed_seq = nn.utils.rnn.pack_padded_sequence(s_inputs, lengths_list, batch_first=batch_first)\n",
        "\n",
        "        r_states = tuple(torch.cat(state_list, dim=1) for state_list in states_lists)\n",
        "        if len(r_states) == 1:\n",
        "            r_states = r_states[0]\n",
        "\n",
        "        return packed_seq, reverse_indices, r_states\n",
        "\n",
        "\n",
        "def unpack_from_rnn_seq(packed_seq, reverse_indices, batch_first=True, tot_len=None):\n",
        "    unpacked_seq, _ = nn.utils.rnn.pad_packed_sequence(packed_seq, batch_first=batch_first, total_length=tot_len)\n",
        "    s_inputs_list = []\n",
        "\n",
        "    if not batch_first:\n",
        "        for i in reverse_indices:\n",
        "            s_inputs_list.append(unpacked_seq[:, i, :].unsqueeze(1))\n",
        "        return torch.cat(s_inputs_list, 1)\n",
        "    else:\n",
        "        for i in reverse_indices:\n",
        "            s_inputs_list.append(unpacked_seq[i, :, :].unsqueeze(0))\n",
        "        return torch.cat(s_inputs_list, 0)\n",
        "\n",
        "\n",
        "def reverse_indice_for_state(states, reverse_indices):\n",
        "    \"\"\"\n",
        "    :param states: [rnn.num_layers, batch_size, rnn.hidden_size]\n",
        "    :param reverse_indices: [batch_size]\n",
        "    :return:\n",
        "    \"\"\"\n",
        "    if states is None:\n",
        "        states = ()\n",
        "    elif not isinstance(states, tuple):\n",
        "        states = (states,)  # rnn.num_layers, batch_size, rnn.hidden_size\n",
        "\n",
        "    states_lists = tuple([] for _ in states)\n",
        "    for i in reverse_indices:\n",
        "        for state_list, state in zip(states_lists, states):\n",
        "            state_list.append(state[:, i, :].unsqueeze(1))\n",
        "\n",
        "    r_states = tuple(torch.cat(state_list, dim=1) for state_list in states_lists)\n",
        "    if len(r_states) == 1:\n",
        "        r_states = r_states[0]\n",
        "    return r_states\n",
        "\n",
        "\n",
        "def auto_rnn(rnn: nn.RNN, seqs, lengths, batch_first=True, init_state=None, output_last_states=False, tot_len=None):\n",
        "    batch_size = seqs.size(0) if batch_first else seqs.size(1)\n",
        "    state_shape = get_state_shape(rnn, batch_size, rnn.bidirectional)\n",
        "\n",
        "    # if init_state is None:\n",
        "    #     h0 = c0 = Variable(seqs.data.new(*state_shape).zero_())\n",
        "    # else:\n",
        "    #     h0 = init_state[0] # rnn.num_layers, batch_size, rnn.hidden_size\n",
        "    #     c0 = init_state[1]\n",
        "\n",
        "    packed_pinputs, r_index, init_state = pack_for_rnn_seq(seqs, lengths, batch_first, init_state)\n",
        "\n",
        "    if len(init_state) == 0:\n",
        "        h0 = c0 = Variable(seqs.data.new(*state_shape).zero_())\n",
        "        init_state = (h0, c0)\n",
        "\n",
        "    #rnn.flatten_parameters()\n",
        "    output, last_state = rnn(packed_pinputs, init_state)\n",
        "    output = unpack_from_rnn_seq(output, r_index, batch_first, tot_len)\n",
        "\n",
        "    if not output_last_states:\n",
        "        return output\n",
        "    else:\n",
        "        last_state = reverse_indice_for_state(last_state, r_index)\n",
        "        return output, last_state\n",
        "\n",
        "\n",
        "def pack_sequence_for_linear(inputs, lengths, batch_first=True):\n",
        "    \"\"\"\n",
        "    :param inputs: [B, T, D] if batch_first \n",
        "    :param lengths:  [B]\n",
        "    :param batch_first:  \n",
        "    :return: \n",
        "    \"\"\"\n",
        "    batch_list = []\n",
        "    if batch_first:\n",
        "        for i, l in enumerate(lengths):\n",
        "            # print(inputs[i, :l].size())\n",
        "            batch_list.append(inputs[i, :l])\n",
        "        packed_sequence = torch.cat(batch_list, 0)\n",
        "        # if chuck:\n",
        "        #     return list(torch.chunk(packed_sequence, chuck, dim=0))\n",
        "        # else:\n",
        "        return packed_sequence\n",
        "    else:\n",
        "        raise NotImplemented()\n",
        "\n",
        "\n",
        "def chucked_forward(inputs, net, chuck=None):\n",
        "    if not chuck:\n",
        "        return net(inputs)\n",
        "    else:\n",
        "        output_list = [net(chuck) for chuck in torch.chunk(inputs, chuck, dim=0)]\n",
        "        return torch.cat(output_list, dim=0)\n",
        "\n",
        "\n",
        "def unpack_sequence_for_linear(inputs, lengths, batch_first=True):\n",
        "    batch_list = []\n",
        "    max_l = max(lengths)\n",
        "\n",
        "    if not isinstance(inputs, list):\n",
        "        inputs = [inputs]\n",
        "    inputs = torch.cat(inputs)\n",
        "\n",
        "    if batch_first:\n",
        "        start = 0\n",
        "        for l in lengths:\n",
        "            end = start + l\n",
        "            batch_list.append(pad_1d(inputs[start:end], max_l))\n",
        "            start = end\n",
        "        return torch.stack(batch_list)\n",
        "    else:\n",
        "        raise NotImplemented()\n",
        "\n",
        "\n",
        "def seq2seq_cross_entropy(logits, label, l, chuck=None, sos_truncate=True):\n",
        "    \"\"\"\n",
        "    :param logits: [exB, V] : exB = sum(l)\n",
        "    :param label: [B] : a batch of Label\n",
        "    :param l: [B] : a batch of LongTensor indicating the lengths of each inputs\n",
        "    :param chuck: Number of chuck to process\n",
        "    :return: A loss value\n",
        "    \"\"\"\n",
        "    packed_label = pack_sequence_for_linear(label, l)\n",
        "    cross_entropy_loss = functools.partial(F.cross_entropy, size_average=False)\n",
        "    total = sum(l)\n",
        "\n",
        "    assert total == logits.size(0) or packed_label.size(0) == logits.size(0), \\\n",
        "        \"logits length mismatch with label length.\"\n",
        "\n",
        "    if chuck:\n",
        "        logits_losses = 0\n",
        "        for x, y in zip(torch.chunk(logits, chuck, dim=0), torch.chunk(packed_label, chuck, dim=0)):\n",
        "            logits_losses += cross_entropy_loss(x, y)\n",
        "        return logits_losses * (1 / total)\n",
        "    else:\n",
        "        return cross_entropy_loss(logits, packed_label) * (1 / total)\n",
        "\n",
        "\n",
        "def cat_along_time(inputs1, inputs2, lengths1, lengths2):\n",
        "    ls1 = list(lengths1)\n",
        "    ls2 = list(lengths2)\n",
        "    \n",
        "    batchmax = max(ls1+ls2)\n",
        "\n",
        "    b_seq_cat_list = []\n",
        "    for i, (l1, l2) in enumerate(zip(ls1, ls2)):\n",
        "        seq_i1 = inputs1[i, :l1, :]\n",
        "        seq_i2 = inputs2[i, :l2, :]\n",
        "        if inputs1.size(1) != l1:\n",
        "            seq_i1_rest = torch.zeros(inputs1[i, l1:, :].shape).to(seq_i1.device)\n",
        "        if inputs2.size(1) != l2:\n",
        "            seq_i2_rest = torch.zeros(inputs2[i, l2:, :].shape).to(seq_i2.device)\n",
        "        \n",
        "        seq_i_cat = torch.cat([seq_i1, seq_i2], dim=0)\n",
        "        if inputs1.size(1) != l1:\n",
        "            seq_i_cat = torch.cat([seq_i_cat, seq_i1_rest], dim=0)\n",
        "        if inputs2.size(1) != l2:\n",
        "            seq_i_cat = torch.cat([seq_i_cat, seq_i2_rest], dim=0)\n",
        "        b_seq_cat_list.append(seq_i_cat)\n",
        "\n",
        "    return torch.stack(b_seq_cat_list)\n",
        "\n",
        "\n",
        "def min_along_time(inputs, lengths, list_in=False):\n",
        "    \"\"\"\n",
        "    :param inputs: [B, T, D] \n",
        "    :param lengths:  [B]\n",
        "    :return: [B * D] max_along_time\n",
        "    :param list_in: \n",
        "    \"\"\"\n",
        "    ls = list(lengths)\n",
        "\n",
        "    if not list_in:\n",
        "        b_seq_max_list = []\n",
        "        for i, l in enumerate(ls):\n",
        "            seq_i = inputs[i, :l, :]\n",
        "            seq_i_max, _ = seq_i.min(dim=0)\n",
        "            seq_i_max = seq_i_max.squeeze()\n",
        "            b_seq_max_list.append(seq_i_max)\n",
        "\n",
        "        return torch.stack(b_seq_max_list)\n",
        "    else:\n",
        "        b_seq_max_list = []\n",
        "        for i, l in enumerate(ls):\n",
        "            seq_i = inputs[i]\n",
        "            seq_i_max, _ = seq_i.min(dim=0)\n",
        "            seq_i_max = seq_i_max.squeeze()\n",
        "            b_seq_max_list.append(seq_i_max)\n",
        "\n",
        "        return torch.stack(b_seq_max_list)\n",
        "        \n",
        "def max_along_time(inputs, lengths, list_in=False):\n",
        "    \"\"\"\n",
        "    :param inputs: [B, T, D] \n",
        "    :param lengths:  [B]\n",
        "    :return: [B * D] max_along_time\n",
        "    :param list_in: \n",
        "    \"\"\"\n",
        "    ls = list(lengths)\n",
        "\n",
        "    if not list_in:\n",
        "        b_seq_max_list = []\n",
        "        for i, l in enumerate(ls):\n",
        "            seq_i = inputs[i, :l, :]\n",
        "            seq_i_max, _ = seq_i.max(dim=0)\n",
        "            seq_i_max = seq_i_max.squeeze()\n",
        "            b_seq_max_list.append(seq_i_max)\n",
        "\n",
        "        return torch.stack(b_seq_max_list)\n",
        "    else:\n",
        "        b_seq_max_list = []\n",
        "        for i, l in enumerate(ls):\n",
        "            seq_i = inputs[i]\n",
        "            seq_i_max, _ = seq_i.max(dim=0)\n",
        "            seq_i_max = seq_i_max.squeeze()\n",
        "            b_seq_max_list.append(seq_i_max)\n",
        "\n",
        "        return torch.stack(b_seq_max_list)\n",
        "\n",
        "\n",
        "def avg_along_time(inputs, lengths, list_in=False):\n",
        "    \"\"\"\n",
        "    :param inputs: [B, T, D]\n",
        "    :param lengths:  [B]\n",
        "    :return: [B * D] max_along_time\n",
        "    :param list_in:\n",
        "    \"\"\"\n",
        "    ls = list(lengths)\n",
        "\n",
        "    if not list_in:\n",
        "        b_seq_avg_list = []\n",
        "        for i, l in enumerate(ls):\n",
        "            seq_i = inputs[i, :l, :]\n",
        "            seq_i_avg = seq_i.mean(dim=0)\n",
        "            seq_i_avg = seq_i_avg.squeeze()\n",
        "            b_seq_avg_list.append(seq_i_avg)\n",
        "\n",
        "        return torch.stack(b_seq_avg_list)\n",
        "    else:\n",
        "        b_seq_avg_list = []\n",
        "        for i, l in enumerate(ls):\n",
        "            seq_i = inputs[i]\n",
        "            seq_i_avg, _ = seq_i.mean(dim=0)\n",
        "            seq_i_avg = seq_i_avg.squeeze()\n",
        "            b_seq_avg_list.append(seq_i_avg)\n",
        "\n",
        "        return torch.stack(b_seq_avg_list)\n",
        "\n",
        "\n",
        "# def length_truncate(inputs, lengths, max_len):\n",
        "#     \"\"\"\n",
        "#     :param inputs: [B, T]\n",
        "#     :param lengths: [B]\n",
        "#     :param max_len: int\n",
        "#     :return: [B, T]\n",
        "#     \"\"\"\n",
        "#     max_l = max(1, max_len)\n",
        "#     max_s1_l = min(max(lengths), max_l)\n",
        "#     lengths = lengths.clamp(min=1, max=max_s1_l)\n",
        "#     if inputs.size(1) > max_s1_l:\n",
        "#         inputs = inputs[:, :max_s1_l]\n",
        "#\n",
        "#     return inputs, lengths, max_s1_l\n",
        "\n",
        "\n",
        "def get_reverse_indices(indices, lengths):\n",
        "    r_indices = indices.data.new(indices.size()).fill_(0)\n",
        "    batch_size = indices.size(0)\n",
        "    for i in range(int(batch_size)):\n",
        "        b_ind = indices[i]\n",
        "        b_l = lengths[i]\n",
        "        for k, ind in enumerate(b_ind):\n",
        "            if k >= b_l:\n",
        "                break\n",
        "            r_indices[i, int(ind)] = k\n",
        "    return r_indices\n",
        "\n",
        "\n",
        "def index_ordering(inputs, lengths, indices, pad_value=0):\n",
        "    \"\"\"\n",
        "    :param inputs: [B, T, ~]\n",
        "    :param lengths: [B]\n",
        "    :param indices: [B, T]\n",
        "    :return:\n",
        "    \"\"\"\n",
        "    batch_size = inputs.size(0)\n",
        "    ordered_out_list = []\n",
        "    for i in range(int(batch_size)):\n",
        "        b_input = inputs[i]\n",
        "        b_l = lengths[i]\n",
        "        b_ind = indices[i]\n",
        "        b_out = b_input[b_ind]\n",
        "        if b_out.size(0) > b_l:\n",
        "            b_out[b_l:] = pad_value\n",
        "        ordered_out_list.append(b_out)\n",
        "\n",
        "    outs = torch.stack(ordered_out_list, dim=0)\n",
        "    return outs\n",
        "\n",
        "\n",
        "def start_and_end_token_handling(inputs, lengths, sos_index=1, eos_index=2, pad_index=0,\n",
        "                                 op=None):\n",
        "    \"\"\"\n",
        "    :param inputs: [B, T]\n",
        "    :param lengths: [B]\n",
        "    :param sos_index: \n",
        "    :param eos_index: \n",
        "    :param pad_index: \n",
        "    :return: \n",
        "    \"\"\"\n",
        "    batch_size = inputs.size(0)\n",
        "\n",
        "    if not op:\n",
        "        return inputs, lengths\n",
        "    elif op == 'rm_start':\n",
        "        inputs = torch.cat([inputs[:, 1:], Variable(inputs.data.new(batch_size, 1).zero_())], dim=1)\n",
        "        return inputs, lengths - 1\n",
        "    elif op == 'rm_end':\n",
        "        for i in range(batch_size):\n",
        "            pass\n",
        "            # Potential problems!?\n",
        "            # inputs[i, lengths[i] - 1] = pad_index\n",
        "        return inputs, lengths - 1\n",
        "    elif op == 'rm_both':\n",
        "        for i in range(batch_size):\n",
        "            pass\n",
        "            # Potential problems!?\n",
        "            # inputs[i, lengths[i] - 1] = pad_index\n",
        "        inputs = torch.cat([inputs[:, 1:], Variable(inputs.data.new(batch_size, 1).zero_())], dim=1)\n",
        "        return inputs, lengths - 2\n",
        "\n",
        "\n",
        "def seq2seq_att(mems, lengths, state, att_net=None):\n",
        "    \"\"\"\n",
        "    :param mems: [B, T, D_mem] This are the memories.\n",
        "                    I call memory for this variable because I think attention is just like read something and then\n",
        "                    make alignments with your memories.\n",
        "                    This memory here is usually the input hidden state of the encoder.\n",
        "\n",
        "    :param lengths: [B]\n",
        "    :param state: [B, D_state]\n",
        "                    I call state for this variable because it's the state I percepts at this time step.\n",
        "\n",
        "    :param att_net: This is the attention network that will be used to calculate the alignment score between\n",
        "                    state and memories.\n",
        "                    input of the att_net is mems and state with shape:\n",
        "                        mems: [exB, D_mem]\n",
        "                        state: [exB, D_state]\n",
        "                    return of the att_net is [exB, 1]\n",
        "\n",
        "                    So any function that map a vector to a scalar could work.\n",
        "\n",
        "    :return: [B, D_result] \n",
        "    \"\"\"\n",
        "\n",
        "    d_state = state.size(1)\n",
        "\n",
        "    if not att_net:\n",
        "        return state\n",
        "    else:\n",
        "        batch_list_mems = []\n",
        "        batch_list_state = []\n",
        "        for i, l in enumerate(lengths):\n",
        "            b_mems = mems[i, :l]  # [T, D_mem]\n",
        "            batch_list_mems.append(b_mems)\n",
        "\n",
        "            b_state = state[i].expand(b_mems.size(0), d_state)  # [T, D_state]\n",
        "            batch_list_state.append(b_state)\n",
        "\n",
        "        packed_sequence_mems = torch.cat(batch_list_mems, 0)  # [sum(l), D_mem]\n",
        "        packed_sequence_state = torch.cat(batch_list_state, 0)  # [sum(l), D_state]\n",
        "\n",
        "        align_score = att_net(packed_sequence_mems, packed_sequence_state)  # [sum(l), 1]\n",
        "\n",
        "        # The score grouped as [(a1, a2, a3), (a1, a2), (a1, a2, a3, a4)].\n",
        "        # aligned_seq = packed_sequence_mems * align_score\n",
        "\n",
        "        start = 0\n",
        "        result_list = []\n",
        "        for i, l in enumerate(lengths):\n",
        "            end = start + l\n",
        "\n",
        "            b_mems = packed_sequence_mems[start:end, :]  # [l, D_mems]\n",
        "            b_score = align_score[start:end, :]  # [l, 1]\n",
        "\n",
        "            softed_b_score = F.softmax(b_score.transpose(0, 1)).transpose(0, 1)  # [l, 1]\n",
        "\n",
        "            weighted_sum = torch.sum(b_mems * softed_b_score, dim=0, keepdim=False)  # [D_mems]\n",
        "\n",
        "            result_list.append(weighted_sum)\n",
        "\n",
        "            start = end\n",
        "\n",
        "        result = torch.stack(result_list, dim=0)\n",
        "\n",
        "        return result\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aRRBg6lxAFTY",
        "colab_type": "text"
      },
      "source": [
        "# Prepare embeddings"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I3UUhbimAFTZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from allennlp.modules.text_field_embedders import BasicTextFieldEmbedder, TextFieldEmbedder\n",
        "from allennlp.modules.token_embedders.bert_token_embedder import PretrainedBertEmbedder"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "29kaW5kMAFTb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "\n",
        "class InstanceClassifier(nn.Module):\n",
        "    def __init__(self,\n",
        "                 rnn_size_in=(1024 + 300, 1024 + 300),\n",
        "                 rnn_size_out=(300, 300), max_l=150, \n",
        "                 mlp_d=300, num_of_class=5, drop_r=0.5, activation_type='relu'):\n",
        "        super(InstanceClassifier, self).__init__()\n",
        "        bert_embedder = PretrainedBertEmbedder(\n",
        "                pretrained_model=\"bert-base-uncased\",\n",
        "                top_layer_only=True, # conserve memory\n",
        "        )\n",
        "        self.bert_embd_layer: TextFieldEmbedder = BasicTextFieldEmbedder({\"tokens\": bert_embedder},\n",
        "                                                                    # we'll be ignoring masks so we'll need to set this to True\n",
        "                                                                  allow_unmatched_keys = True)\n",
        "        self.esim_layer = BaselineModel(\n",
        "           rnn_size_in, rnn_size_out, max_l, mlp_d, num_of_class, drop_r, activation_type\n",
        "        )\n",
        "\n",
        "    def raw_input_to_esim_input(self, s_bert_chars):\n",
        "        s_bert_out = self.bert_embd_layer(s_bert_chars)\n",
        "        s_mask, s_len = get_length_and_mask(s_bert_chars['tokens'])\n",
        "        return s_bert_out, s_len\n",
        "\n",
        "    def forward(self, batch):\n",
        "        s1_tokens = batch['sentence_tokens']\n",
        "        s1_sent = []\n",
        "        for item in s1_tokens['tokens']:\n",
        "            sent = []\n",
        "            for word in item:\n",
        "                sent.append(vocab.get_token_from_index(word.item(), namespace='bert'))\n",
        "            s1_sent.append(sent)\n",
        "        s1_bert_embd, s1_len = self.raw_input_to_esim_input(s1_tokens)\n",
        "        instance_out = self.esim_layer(s1_bert_embd, s1_bert_embd, s1_len)\n",
        "        return instance_out, s1_sent        "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3MMOWA5PwOED",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "model = InstanceClassifier(rnn_size_in=(768,768+450),\n",
        "                  rnn_size_out=(450, 450),\n",
        "                  mlp_d=450, max_l=300)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pCsELiTKSTDw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "d2511e97-530e-40c3-91b3-caedcf64574b"
      },
      "source": [
        "#model.load_state_dict(torch.load('bigmodel'))"
      ],
      "execution_count": 290,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<All keys matched successfully>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 290
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BejUJtW1AFTc",
        "colab_type": "text"
      },
      "source": [
        "Notice how simple and modular the code for initializing the model is. All the complexity is delegated to each component."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ARo_94ehAFTe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "if USE_GPU: model.cuda()\n",
        "else: model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ckvuOEsRAFTd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zPa3WLtNAFTi",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F9RSKC_hAFT5",
        "colab_type": "text"
      },
      "source": [
        "# Train"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kiw3pjNYAFT6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "optimizer = optim.Adam(model.parameters(), lr=config.lr)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0C1jIE8wyrzL",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from tqdm import tqdm"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gCpi6_fWZSQO",
        "colab_type": "code",
        "outputId": "2011a9ac-6afc-4d5a-c2a8-8e0ded2d0b32",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "criterion = nn.CrossEntropyLoss()\n",
        "\n",
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\", index=0)\n",
        "device_num = -1 if device.type == 'cpu' else 0\n",
        "\n",
        "for i_epoch in range(5):\n",
        "    train_iter = iterator(train_ds, shuffle=True, num_epochs=1)\n",
        "    for i, batch in tqdm(enumerate(train_iter)):\n",
        "        model.train()\n",
        "        batch = nn_util.move_to_device(batch, 0 if USE_GPU else -1)\n",
        "        (out, attn), s1  = model(batch)\n",
        "        y = batch['label'].squeeze(1)\n",
        "        loss = criterion(out, y.type(torch.LongTensor).cuda())\n",
        "        print(\"Epoch : \", i_epoch, end='')\n",
        "        print(\" === Batch size : \", i, end='')\n",
        "        print(\" === loss : \",loss.item())\n",
        "        optimizer.zero_grad()\n",
        "        loss.backward()\n",
        "        optimizer.step()"
      ],
      "execution_count": 403,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0it [00:00, ?it/s]Too many wordpieces, truncating sequence. If you would like a sliding window, set `truncate_long_sequences` to False.The offending input was: ['[', 'cls', ']', '[', '\"', 'neon', ']', ']', '[', '[', 'montgomery', 'park', '(', 'portland', ',', 'oregon', ')', '|', 'montgomery', 'park', ']', ']', ',', 'formerly', '[', '[', 'montgomery', 'ward', ']', ']', ',', 'sign', ')', '<', 'ref', '>', '{', '{', 'cite', 'news', '|', 'url', 'http', ':', '/', '/', 'wwwmtvcom', '/', 'movies', '/', 'news', '/', 'articles', '/', '1565538', '/', '20070725', '/', 'storyjhtml', '|', 'title', \"'\", 'simpsons', \"'\", 'trivia', ',', 'from', 'swearing', 'lisa', 'to', \"'\", 'burns', '-', 'sexual', \"'\", 'smithers', '|', 'accessdate', '2007', '-', '08', '-', '17', '|', 'date', '2007', '-', '07', '-', '26', '|', 'author', 'larry', 'carroll', '|', 'publisher', '[', '[', 'mtv', ']', ']', '}', '}', '<', '/', 'ref', '>', '[', '[', 'file', ':', 'mlcjpg', '|', 'thumb', '|', 'the', '[', '[', 'metropolitan', 'learning', 'center', '(', 'portland', ',', 'oregon', ')', '|', 'metropolitan', 'learning', 'center', ']', ']', 'in', 'northwest', 'portland', ']', ']', 'see', 'also', '*', '[', '[', 'national', 'register', 'of', 'historic', 'places', 'listings', 'in', 'northwest', 'portland', ',', 'oregon', ']', ']', 'references', '{', '{', 'reflist', '}', '}', '{', '{', 'northwest', 'district', ',', 'portland', ',', 'oregon', '}', '}', '{', '{', 'portland', 'neighborhoods', '}', '}', '[', '[', 'category', ':', 'neighborhoods', 'in', 'portland', ',', '\"', ',', '\"', 'ward', ']', ']', ',', 'sign', ')', '<', 'ref', '>', '{', '{', 'cite', 'news', '|', 'url', 'http', ':', '/', '/', 'wwwmtvcom', '/', 'movies', '/', 'news', '/', 'articles', '/', '1565538', '/', '20070725', '/', 'storyjhtml', '|', 'title', \"'\", 'simpsons', \"'\", 'trivia', ',', 'from', 'swearing', 'lisa', 'to', \"'\", 'burns', '-', 'sexual', \"'\", 'smithers', '|', 'accessdate', '2007', '-', '08', '-', '17', '|', 'date', '2007', '-', '07', '-', '26', '|', 'author', 'larry', 'carroll', '|', 'publisher', '[', '[', 'mtv', ']', ']', '}', '}', '<', '/', 'ref', '>', '[', '[', 'file', ':', 'mlcjpg', '|', 'thumb', '|', 'the', '[', '[', 'metropolitan', 'learning', 'center', '(', 'portland', ',', 'oregon', ')', '|', 'metropolitan', 'learning', 'center', ']', ']', 'in', 'northwest', 'portland', ']', ']', 'see', 'also', '*', '[', '[', 'national', 'register', 'of', 'historic', 'places', 'listings', 'in', 'northwest', 'portland', ',', 'oregon', ']', ']', 'references', '{', '{', 'reflist', '}', '}', '{', '{', 'northwest', 'district', ',', 'portland', ',', 'oregon', '}', '}', '{', '{', 'portland', 'neighborhoods', '}', '}', '[', '[', 'category', ':', 'neighborhoods', 'in', 'portland', ',', 'oregon', ']', ']', '[', '[', 'category', ':', 'northwest', 'district', ',', 'portland', ',', 'oregon', '|'].To avoid polluting your logs we will not warn about this again.\n",
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "1it [00:00,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  0 === loss :  1.5404952764511108\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r2it [00:01,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  1 === loss :  1.3896069526672363\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r3it [00:02,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  2 === loss :  1.258595585823059\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r4it [00:03,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  3 === loss :  1.2040092945098877\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r5it [00:04,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  4 === loss :  1.633196234703064\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r6it [00:05,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  5 === loss :  1.3548610210418701\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r7it [00:06,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  6 === loss :  1.2133210897445679\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r8it [00:07,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  7 === loss :  1.4097155332565308\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r9it [00:08,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  8 === loss :  1.380820393562317\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r10it [00:09,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  9 === loss :  1.1485339403152466\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r11it [00:09,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  10 === loss :  1.1546974182128906\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r12it [00:10,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  11 === loss :  1.2007606029510498\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r13it [00:11,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  12 === loss :  1.1107441186904907\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r14it [00:12,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  13 === loss :  1.235710620880127\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r15it [00:13,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  14 === loss :  1.3425577878952026\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r16it [00:14,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  15 === loss :  1.1991244554519653\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r17it [00:15,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  16 === loss :  1.2348254919052124\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r18it [00:16,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  17 === loss :  1.1671103239059448\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r19it [00:17,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  18 === loss :  1.175645351409912\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r20it [00:18,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  19 === loss :  1.2715425491333008\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r21it [00:19,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  20 === loss :  1.1570791006088257\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r22it [00:19,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  21 === loss :  1.1833761930465698\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r23it [00:20,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  22 === loss :  1.3872495889663696\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r24it [00:21,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  23 === loss :  1.0913866758346558\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r25it [00:22,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  24 === loss :  1.1620968580245972\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r26it [00:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  25 === loss :  1.1186497211456299\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r27it [00:24,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  26 === loss :  1.1584317684173584\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r28it [00:25,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  27 === loss :  1.2219294309616089\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r29it [00:26,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  28 === loss :  1.147288203239441\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r30it [00:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  29 === loss :  1.2991989850997925\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r31it [00:28,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  30 === loss :  1.100097894668579\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r32it [00:28,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  31 === loss :  1.2484610080718994\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r33it [00:29,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  32 === loss :  1.1256728172302246\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r34it [00:30,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  33 === loss :  1.0937882661819458\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r35it [00:31,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  34 === loss :  1.0758954286575317\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r36it [00:32,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  35 === loss :  1.3888092041015625\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r37it [00:33,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  36 === loss :  1.0732680559158325\n"
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          "name": "stdout"
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        {
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            "\r38it [00:34,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  37 === loss :  1.2024999856948853\n"
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          "name": "stdout"
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        {
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            "\r39it [00:35,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r40it [00:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r41it [00:37,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r42it [00:38,  1.10it/s]"
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        },
        {
          "output_type": "stream",
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            "\r43it [00:38,  1.10it/s]"
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          "name": "stderr"
        },
        {
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            "\r44it [00:39,  1.10it/s]"
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        {
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            "\r45it [00:40,  1.10it/s]"
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        {
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            "\r46it [00:41,  1.10it/s]"
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        {
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        {
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            "\r47it [00:42,  1.10it/s]"
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        {
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        {
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        },
        {
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        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r50it [00:45,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  49 === loss :  1.264013648033142\n"
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          "name": "stdout"
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        {
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            "\r51it [00:46,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  50 === loss :  1.1931169033050537\n"
          ],
          "name": "stdout"
        },
        {
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            "\r52it [00:47,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  51 === loss :  1.2628552913665771\n"
          ],
          "name": "stdout"
        },
        {
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            "\r53it [00:48,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  52 === loss :  1.218840479850769\n"
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          "name": "stdout"
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        {
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            "\r54it [00:49,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  53 === loss :  1.1217948198318481\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r55it [00:49,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  54 === loss :  1.1120672225952148\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r56it [00:50,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  55 === loss :  1.2463446855545044\n"
          ],
          "name": "stdout"
        },
        {
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            "\r57it [00:51,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  56 === loss :  1.1629698276519775\n"
          ],
          "name": "stdout"
        },
        {
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            "\r58it [00:52,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  57 === loss :  1.036486029624939\n"
          ],
          "name": "stdout"
        },
        {
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            "\r59it [00:53,  1.08it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  58 === loss :  1.145817756652832\n"
          ],
          "name": "stdout"
        },
        {
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            "\r60it [00:54,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  59 === loss :  1.2568638324737549\n"
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          "name": "stdout"
        },
        {
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            "\r61it [00:55,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  60 === loss :  1.113139033317566\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r62it [00:56,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  61 === loss :  1.2573033571243286\n"
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          "name": "stdout"
        },
        {
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            "\r63it [00:57,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  62 === loss :  1.1906291246414185\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r64it [00:58,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  63 === loss :  1.0285496711730957\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r65it [00:59,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  64 === loss :  0.9694800972938538\n"
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          "name": "stdout"
        },
        {
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            "\r66it [01:00,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  65 === loss :  1.2679035663604736\n"
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          "name": "stdout"
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        {
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            "\r67it [01:00,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  66 === loss :  1.197623610496521\n"
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        {
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            "\r68it [01:01,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r69it [01:02,  1.11it/s]"
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        },
        {
          "output_type": "stream",
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        {
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            "\r70it [01:03,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r71it [01:04,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r72it [01:05,  1.11it/s]"
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        },
        {
          "output_type": "stream",
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        {
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            "\r73it [01:06,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r74it [01:07,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r75it [01:08,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r76it [01:09,  1.09it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r77it [01:10,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
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        {
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            "\r78it [01:10,  1.10it/s]"
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        },
        {
          "output_type": "stream",
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            "\r79it [01:11,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r80it [01:12,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r81it [01:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r82it [01:14,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r83it [01:15,  1.11it/s]"
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        },
        {
          "output_type": "stream",
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        {
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        },
        {
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        {
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        {
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        {
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        {
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        {
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r92it [01:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  91 === loss :  1.1076374053955078\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
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            "\r93it [01:24,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  92 === loss :  1.008110523223877\n"
          ],
          "name": "stdout"
        },
        {
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            "\r94it [01:25,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  93 === loss :  1.1852757930755615\n"
          ],
          "name": "stdout"
        },
        {
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            "\r95it [01:26,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  94 === loss :  0.9756921529769897\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
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            "\r96it [01:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  95 === loss :  1.1022615432739258\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
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            "\r97it [01:28,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  96 === loss :  1.0314545631408691\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r98it [01:28,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  97 === loss :  1.0725821256637573\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
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            "\r99it [01:29,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  98 === loss :  0.9890340566635132\n"
          ],
          "name": "stdout"
        },
        {
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            "\r100it [01:30,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  99 === loss :  0.9933907985687256\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
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            "\r101it [01:31,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  100 === loss :  1.018532156944275\n"
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          "name": "stdout"
        },
        {
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            "\r102it [01:32,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  101 === loss :  1.0851752758026123\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r103it [01:33,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  102 === loss :  0.9295248985290527\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r104it [01:34,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  103 === loss :  0.9059197306632996\n"
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          "name": "stdout"
        },
        {
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            "\r105it [01:35,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  104 === loss :  1.4012820720672607\n"
          ],
          "name": "stdout"
        },
        {
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            "\r106it [01:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  105 === loss :  0.9079646468162537\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r107it [01:37,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  106 === loss :  1.1307945251464844\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r108it [01:38,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  107 === loss :  0.7884365916252136\n"
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        {
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            "\r109it [01:38,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  108 === loss :  1.2410893440246582\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r110it [01:39,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r111it [01:40,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r112it [01:41,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  111 === loss :  1.3287397623062134\n"
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        {
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            "\r113it [01:42,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r114it [01:43,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r115it [01:44,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r116it [01:45,  1.12it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r117it [01:46,  1.12it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r118it [01:46,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r119it [01:47,  1.12it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r120it [01:48,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r121it [01:49,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r122it [01:50,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
          "output_type": "stream",
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        },
        {
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        },
        {
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        {
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        {
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        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r134it [02:01,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  133 === loss :  1.1612614393234253\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
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            "\r135it [02:02,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  134 === loss :  1.0913636684417725\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
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            "\r136it [02:03,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  135 === loss :  1.2089712619781494\n"
          ],
          "name": "stdout"
        },
        {
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            "\r137it [02:04,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  136 === loss :  1.2669590711593628\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
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            "\r138it [02:04,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  137 === loss :  1.1768280267715454\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
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            "\r139it [02:05,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  138 === loss :  0.9333251118659973\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r140it [02:06,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  139 === loss :  0.8858634233474731\n"
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          "name": "stdout"
        },
        {
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          "text": [
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            "\r141it [02:07,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  140 === loss :  0.9977359175682068\n"
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          "name": "stdout"
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r142it [02:08,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  141 === loss :  1.0319808721542358\n"
          ],
          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r143it [02:09,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  142 === loss :  1.1473835706710815\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r144it [02:10,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  143 === loss :  1.0979907512664795\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r145it [02:11,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  144 === loss :  1.2165758609771729\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r146it [02:12,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  145 === loss :  1.159199595451355\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r147it [02:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  146 === loss :  1.061028003692627\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r148it [02:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  147 === loss :  1.2026894092559814\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r149it [02:14,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  148 === loss :  1.201340675354004\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r150it [02:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  149 === loss :  1.0996023416519165\n"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r151it [02:16,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  150 === loss :  1.1884673833847046\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r152it [02:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  151 === loss :  1.0480315685272217\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r153it [02:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  152 === loss :  1.0897536277770996\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r154it [02:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  153 === loss :  1.2616913318634033\n"
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          "name": "stdout"
        },
        {
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            "\r155it [02:20,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  154 === loss :  1.0801749229431152\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r156it [02:21,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  155 === loss :  1.0584111213684082\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r157it [02:22,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  156 === loss :  1.1263865232467651\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r158it [02:22,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  157 === loss :  1.1158031225204468\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r159it [02:23,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  158 === loss :  1.0207924842834473\n"
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          "name": "stdout"
        },
        {
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            "\r160it [02:24,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  0 === Batch size :  159 === loss :  1.0795143842697144\n"
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          "name": "stdout"
        },
        {
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            "\r161it [02:25,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  160 === loss :  1.1544275283813477\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r162it [02:26,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  161 === loss :  1.1884562969207764\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r163it [02:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  0 === Batch size :  162 === loss :  1.168738842010498\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
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            "0it [00:00, ?it/s]"
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          "name": "stderr"
        },
        {
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            "Epoch :  0 === Batch size :  163 === loss :  0.9964731931686401\n"
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          "name": "stdout"
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r1it [00:00,  1.14it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  0 === loss :  1.138715147972107\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r2it [00:01,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  1 === loss :  1.110522747039795\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r3it [00:02,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  2 === loss :  1.3629409074783325\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r4it [00:03,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  3 === loss :  0.9955145120620728\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r5it [00:04,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  4 === loss :  1.257727026939392\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r6it [00:05,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  5 === loss :  0.8881589770317078\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r7it [00:06,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  6 === loss :  1.0284039974212646\n"
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          "name": "stdout"
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r8it [00:07,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  7 === loss :  1.2575063705444336\n"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r9it [00:08,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  8 === loss :  1.045140027999878\n"
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r10it [00:09,  1.11it/s]"
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          "name": "stderr"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r11it [00:09,  1.12it/s]"
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          "name": "stderr"
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        {
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            "Epoch :  1 === Batch size :  10 === loss :  1.0710053443908691\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r12it [00:10,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  11 === loss :  1.2359168529510498\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r13it [00:11,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  12 === loss :  1.1627529859542847\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r14it [00:12,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  13 === loss :  1.0991324186325073\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r15it [00:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  14 === loss :  1.106502652168274\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r16it [00:14,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  15 === loss :  0.9634920954704285\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r17it [00:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  16 === loss :  1.2416050434112549\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r18it [00:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  17 === loss :  0.8875555396080017\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r19it [00:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  18 === loss :  1.0274039506912231\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r20it [00:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  19 === loss :  0.8331307172775269\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r21it [00:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  20 === loss :  1.2076456546783447\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r22it [00:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  21 === loss :  1.1414333581924438\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r23it [00:20,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  22 === loss :  0.8580189347267151\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r24it [00:21,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  23 === loss :  1.02686607837677\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r25it [00:22,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  24 === loss :  0.9010499119758606\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r26it [00:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  25 === loss :  1.1174421310424805\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r27it [00:24,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  26 === loss :  1.1810805797576904\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r28it [00:25,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  27 === loss :  1.1084213256835938\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r29it [00:26,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  28 === loss :  0.8684818148612976\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r30it [00:27,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  29 === loss :  1.01949143409729\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r31it [00:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  30 === loss :  1.262808084487915\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r32it [00:28,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  31 === loss :  1.237400770187378\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r33it [00:29,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  32 === loss :  1.0423085689544678\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r34it [00:30,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  33 === loss :  1.075539231300354\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r35it [00:31,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  34 === loss :  1.2238601446151733\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r36it [00:32,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  35 === loss :  1.0014444589614868\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r37it [00:33,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  36 === loss :  0.8452193140983582\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r38it [00:34,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  37 === loss :  1.2220218181610107\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r39it [00:35,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  38 === loss :  1.039026141166687\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r40it [00:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  39 === loss :  1.120217204093933\n"
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          "name": "stdout"
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        {
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            "\r41it [00:37,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  40 === loss :  0.9834470152854919\n"
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          "name": "stdout"
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        {
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            "\r42it [00:37,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r43it [00:38,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  42 === loss :  1.273967981338501\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r44it [00:39,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r45it [00:40,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r46it [00:41,  1.10it/s]"
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          "name": "stderr"
        },
        {
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          "name": "stdout"
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        {
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            "\r47it [00:42,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r48it [00:43,  1.11it/s]"
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          "name": "stderr"
        },
        {
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          "name": "stdout"
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        {
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            "\r49it [00:44,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r50it [00:45,  1.12it/s]"
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          "name": "stderr"
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        {
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        {
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            "\r51it [00:46,  1.12it/s]"
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          "name": "stderr"
        },
        {
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            "\r52it [00:46,  1.11it/s]"
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          "name": "stderr"
        },
        {
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          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  52 === loss :  0.9222436547279358\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r54it [00:48,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  53 === loss :  0.9192125201225281\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r55it [00:49,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  54 === loss :  1.1000398397445679\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r56it [00:50,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  55 === loss :  0.9706634283065796\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r57it [00:51,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  56 === loss :  0.8870025277137756\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r58it [00:52,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  57 === loss :  0.971405029296875\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r59it [00:53,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  58 === loss :  0.88983154296875\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r60it [00:54,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  59 === loss :  0.7535161972045898\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r61it [00:55,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  60 === loss :  0.9867676496505737\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r62it [00:55,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  61 === loss :  0.9979480504989624\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r63it [00:56,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  62 === loss :  1.0978533029556274\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r64it [00:57,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  63 === loss :  1.1911137104034424\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r65it [00:58,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  64 === loss :  0.9475597143173218\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r66it [00:59,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  65 === loss :  0.9879911541938782\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r67it [01:00,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  66 === loss :  1.2428007125854492\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r68it [01:01,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  67 === loss :  0.9927524328231812\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r69it [01:02,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  68 === loss :  1.0857094526290894\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r70it [01:03,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r71it [01:04,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  70 === loss :  1.328678011894226\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r72it [01:04,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r73it [01:05,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r74it [01:06,  1.09it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r75it [01:07,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r76it [01:08,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r77it [01:09,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r78it [01:10,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r79it [01:11,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r80it [01:12,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r81it [01:13,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r82it [01:14,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r83it [01:14,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r84it [01:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r85it [01:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r86it [01:17,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r87it [01:18,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r88it [01:19,  1.10it/s]"
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          "name": "stderr"
        },
        {
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            "\r89it [01:20,  1.10it/s]"
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          "name": "stderr"
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        {
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        {
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            "\r90it [01:21,  1.10it/s]"
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          "name": "stderr"
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        {
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          "name": "stderr"
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        {
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          "name": "stderr"
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        {
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          "name": "stderr"
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        {
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        {
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        {
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          "text": [
            "Epoch :  1 === Batch size :  94 === loss :  0.8372901082038879\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r96it [01:26,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  95 === loss :  1.0832555294036865\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r97it [01:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  96 === loss :  1.0263042449951172\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r98it [01:28,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  97 === loss :  0.9961689710617065\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r99it [01:29,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  98 === loss :  1.0505532026290894\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r100it [01:30,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  99 === loss :  1.0595024824142456\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r101it [01:31,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  100 === loss :  1.135005235671997\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r102it [01:32,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  101 === loss :  0.9013203382492065\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r103it [01:32,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  102 === loss :  0.6448299288749695\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r104it [01:33,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  103 === loss :  1.2633111476898193\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r105it [01:34,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  104 === loss :  0.9837095737457275\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r106it [01:35,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  105 === loss :  0.8409251570701599\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r107it [01:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  106 === loss :  0.8960718512535095\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r108it [01:37,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  107 === loss :  0.9871894717216492\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r109it [01:38,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  108 === loss :  1.102902889251709\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r110it [01:39,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  109 === loss :  0.9168412685394287\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r111it [01:40,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  110 === loss :  0.9966845512390137\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r112it [01:41,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  111 === loss :  1.0132535696029663\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r113it [01:42,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  112 === loss :  0.9290328025817871\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r114it [01:42,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  113 === loss :  0.8289616107940674\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r115it [01:43,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  114 === loss :  0.9936487674713135\n"
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          "name": "stdout"
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        {
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            "\r116it [01:44,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  115 === loss :  1.037063717842102\n"
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          "name": "stdout"
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        {
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            "\r117it [01:45,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  116 === loss :  1.0057417154312134\n"
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          "name": "stdout"
        },
        {
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            "\r118it [01:46,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r119it [01:47,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r120it [01:48,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r121it [01:49,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  120 === loss :  1.099847435951233\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r122it [01:50,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  121 === loss :  1.0478606224060059\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r123it [01:51,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  122 === loss :  1.0232728719711304\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r124it [01:52,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r125it [01:52,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r126it [01:53,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r127it [01:54,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r128it [01:55,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r129it [01:56,  1.12it/s]"
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          "name": "stderr"
        },
        {
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            "\r130it [01:57,  1.12it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r131it [01:58,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r132it [01:59,  1.12it/s]"
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          "name": "stderr"
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        {
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          "name": "stderr"
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        {
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          "name": "stderr"
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        {
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        {
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        {
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        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  136 === loss :  0.8807957172393799\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r138it [02:04,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  137 === loss :  0.8888025879859924\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r139it [02:05,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  138 === loss :  1.06881844997406\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r140it [02:06,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  139 === loss :  0.9993796348571777\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r141it [02:07,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  140 === loss :  1.1652510166168213\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r142it [02:08,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  141 === loss :  0.9490929841995239\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r143it [02:09,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  142 === loss :  0.8725149035453796\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r144it [02:09,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  143 === loss :  1.1459965705871582\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r145it [02:10,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  144 === loss :  1.2116985321044922\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r146it [02:11,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  145 === loss :  1.0841575860977173\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r147it [02:12,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  146 === loss :  0.8396844267845154\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r148it [02:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  147 === loss :  1.220069169998169\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r149it [02:14,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  148 === loss :  1.1684705018997192\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r150it [02:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  149 === loss :  1.0315607786178589\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r151it [02:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  150 === loss :  1.2860270738601685\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r152it [02:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  151 === loss :  1.1617928743362427\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r153it [02:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  152 === loss :  1.0888359546661377\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r154it [02:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  153 === loss :  1.041232943534851\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r155it [02:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  154 === loss :  0.9659753441810608\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r156it [02:20,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  155 === loss :  1.0374048948287964\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r157it [02:21,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  156 === loss :  0.9537785053253174\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r158it [02:22,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  157 === loss :  0.8467916250228882\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r159it [02:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  1 === Batch size :  158 === loss :  0.9753717184066772\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r160it [02:24,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  159 === loss :  0.9440032839775085\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r161it [02:25,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  160 === loss :  0.9678375124931335\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r162it [02:26,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  161 === loss :  0.9331488609313965\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r163it [02:27,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  162 === loss :  0.8972609043121338\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "164it [02:27,  1.21it/s]\n",
            "0it [00:00, ?it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  1 === Batch size :  163 === loss :  1.0915249586105347\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r1it [00:00,  1.14it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  0 === loss :  0.9249740242958069\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r2it [00:01,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  1 === loss :  0.7341644167900085\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r3it [00:02,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  2 === loss :  1.0378100872039795\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r4it [00:03,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  3 === loss :  0.9812771081924438\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r5it [00:04,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  4 === loss :  0.8384587168693542\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r6it [00:05,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  5 === loss :  0.9769065976142883\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r7it [00:06,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  6 === loss :  0.9712269902229309\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r8it [00:07,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  7 === loss :  0.8465365767478943\n"
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          "name": "stdout"
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r9it [00:08,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  8 === loss :  1.0443906784057617\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r10it [00:08,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r11it [00:09,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r12it [00:10,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r13it [00:11,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r14it [00:12,  1.12it/s]"
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          "name": "stderr"
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        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r15it [00:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  14 === loss :  0.744957685470581\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r16it [00:14,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  15 === loss :  1.11664879322052\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r17it [00:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  16 === loss :  1.2454330921173096\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r18it [00:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  17 === loss :  1.0307161808013916\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r19it [00:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  18 === loss :  0.946139395236969\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r20it [00:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  19 === loss :  0.9181414842605591\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r21it [00:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  20 === loss :  0.8415835499763489\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r22it [00:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  21 === loss :  1.0352022647857666\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r23it [00:20,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  22 === loss :  1.0995441675186157\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r24it [00:21,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  23 === loss :  0.9754475951194763\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r25it [00:22,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  24 === loss :  0.9417621493339539\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r26it [00:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  25 === loss :  1.1659297943115234\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r27it [00:24,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  26 === loss :  1.2308838367462158\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r28it [00:25,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  27 === loss :  0.8959404230117798\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r29it [00:26,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  28 === loss :  1.2374651432037354\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r30it [00:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  29 === loss :  1.151692271232605\n"
          ],
          "name": "stdout"
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r31it [00:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  30 === loss :  0.9688166379928589\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r32it [00:28,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  31 === loss :  1.173476219177246\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r33it [00:29,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  32 === loss :  0.72968590259552\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r34it [00:30,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  33 === loss :  0.9551238417625427\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r35it [00:31,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  34 === loss :  0.7871695160865784\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r36it [00:32,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  35 === loss :  0.9787080883979797\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r37it [00:33,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  36 === loss :  0.7743760347366333\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r38it [00:34,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  37 === loss :  1.0426691770553589\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r39it [00:35,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  38 === loss :  1.1007071733474731\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r40it [00:36,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  39 === loss :  0.7955543994903564\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r41it [00:36,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  40 === loss :  1.2516032457351685\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r42it [00:37,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  41 === loss :  1.261661410331726\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r43it [00:38,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  42 === loss :  1.021302342414856\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r44it [00:39,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  43 === loss :  1.025955080986023\n"
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          "name": "stdout"
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        {
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            "\r45it [00:40,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  44 === loss :  1.1020938158035278\n"
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          "name": "stdout"
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        {
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            "\r46it [00:41,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r47it [00:42,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r48it [00:43,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r49it [00:44,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r50it [00:45,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r51it [00:45,  1.11it/s]"
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          "name": "stderr"
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        {
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            "\r52it [00:46,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r53it [00:47,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r54it [00:48,  1.11it/s]"
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          "name": "stderr"
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        {
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            "\r55it [00:49,  1.11it/s]"
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          "name": "stderr"
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        {
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            "\r56it [00:50,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r57it [00:51,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  56 === loss :  0.7877633571624756\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r58it [00:52,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  57 === loss :  1.0661247968673706\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r59it [00:53,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  58 === loss :  0.9379456043243408\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r60it [00:54,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  59 === loss :  1.3001823425292969\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r61it [00:54,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  60 === loss :  1.1844482421875\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r62it [00:55,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  61 === loss :  0.8968154788017273\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r63it [00:56,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  62 === loss :  1.0060094594955444\n"
          ],
          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r64it [00:57,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  63 === loss :  0.9335889220237732\n"
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          "name": "stdout"
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        {
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            "\r65it [00:58,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  64 === loss :  1.1218193769454956\n"
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          "name": "stdout"
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        {
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            "\r66it [00:59,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  65 === loss :  0.9452833533287048\n"
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          "name": "stdout"
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        {
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            "\r67it [01:00,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r68it [01:01,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  67 === loss :  1.1157945394515991\n"
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          "name": "stdout"
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        {
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            "\r69it [01:02,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  68 === loss :  0.9945728778839111\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r70it [01:03,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  69 === loss :  0.8769263625144958\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r71it [01:03,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  70 === loss :  1.0508590936660767\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r72it [01:04,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  71 === loss :  1.002254843711853\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r73it [01:05,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  72 === loss :  0.8705857992172241\n"
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          "name": "stdout"
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        {
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            "\r74it [01:06,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  73 === loss :  0.8421621322631836\n"
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          "name": "stdout"
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        {
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            "\r75it [01:07,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  74 === loss :  1.1339013576507568\n"
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          "name": "stdout"
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        {
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            "\r76it [01:08,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r77it [01:09,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r78it [01:10,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r79it [01:11,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r80it [01:12,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r81it [01:13,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r82it [01:13,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r83it [01:14,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r84it [01:15,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r85it [01:16,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r86it [01:17,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r87it [01:18,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r88it [01:19,  1.12it/s]"
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          "name": "stderr"
        },
        {
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          "name": "stderr"
        },
        {
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          "name": "stderr"
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        {
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          "name": "stderr"
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        {
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          "name": "stderr"
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        {
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          "name": "stderr"
        },
        {
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          "name": "stderr"
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        {
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          "name": "stderr"
        },
        {
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          "name": "stderr"
        },
        {
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        {
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        },
        {
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        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r99it [01:29,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  98 === loss :  1.0839284658432007\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r100it [01:30,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  99 === loss :  1.0849263668060303\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r101it [01:31,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  100 === loss :  1.1298259496688843\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r102it [01:32,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  101 === loss :  1.0685778856277466\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r103it [01:32,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  102 === loss :  0.9072902202606201\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r104it [01:33,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  103 === loss :  1.0333878993988037\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r105it [01:34,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  104 === loss :  0.990837812423706\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r106it [01:35,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  105 === loss :  1.2067899703979492\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r107it [01:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  106 === loss :  1.0480527877807617\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r108it [01:37,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  107 === loss :  1.0676438808441162\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r109it [01:38,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  108 === loss :  0.9470970034599304\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r110it [01:39,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  109 === loss :  1.1035583019256592\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r111it [01:40,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  110 === loss :  1.041764259338379\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r112it [01:41,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  111 === loss :  1.0317280292510986\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r113it [01:42,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  112 === loss :  0.9448025226593018\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r114it [01:42,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  113 === loss :  0.8716670870780945\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r115it [01:43,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  114 === loss :  0.7951924204826355\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r116it [01:44,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  115 === loss :  1.1379237174987793\n"
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          "name": "stdout"
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        {
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            "\r117it [01:45,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  116 === loss :  0.9869160056114197\n"
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        {
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            "\r118it [01:46,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  117 === loss :  1.0688292980194092\n"
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          "name": "stdout"
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        {
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            "\r119it [01:47,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r120it [01:48,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r121it [01:49,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r122it [01:50,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r123it [01:51,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r124it [01:52,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r125it [01:52,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r126it [01:53,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r127it [01:54,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r128it [01:55,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r129it [01:56,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r130it [01:57,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r131it [01:58,  1.12it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r132it [01:59,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r133it [02:00,  1.12it/s]"
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          "name": "stderr"
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        {
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        {
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            "\r134it [02:01,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r135it [02:01,  1.11it/s]"
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        },
        {
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        },
        {
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          "name": "stderr"
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        {
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        {
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        {
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            "\r140it [02:06,  1.10it/s]"
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        {
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          "name": "stdout"
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        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r141it [02:07,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  140 === loss :  1.198486089706421\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r142it [02:08,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  141 === loss :  0.8473418951034546\n"
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          "name": "stdout"
        },
        {
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            "\r143it [02:09,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  142 === loss :  0.9040430784225464\n"
          ],
          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r144it [02:10,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  143 === loss :  1.0104691982269287\n"
          ],
          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r145it [02:10,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  144 === loss :  0.7956088185310364\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r146it [02:11,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  145 === loss :  0.7499557137489319\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r147it [02:12,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  146 === loss :  0.9885661602020264\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r148it [02:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  147 === loss :  0.834335207939148\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r149it [02:14,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  148 === loss :  1.013102650642395\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r150it [02:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  149 === loss :  1.0346693992614746\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r151it [02:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  150 === loss :  0.9437543153762817\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r152it [02:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  151 === loss :  0.8308018445968628\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r153it [02:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  152 === loss :  1.2448046207427979\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r154it [02:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  153 === loss :  0.9181649684906006\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r155it [02:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  154 === loss :  0.9713957905769348\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r156it [02:20,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  155 === loss :  0.9122474193572998\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r157it [02:21,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  156 === loss :  1.0888783931732178\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r158it [02:22,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  157 === loss :  1.0269886255264282\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r159it [02:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  158 === loss :  1.2037715911865234\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r160it [02:24,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  159 === loss :  1.1066588163375854\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r161it [02:25,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  160 === loss :  0.8407713174819946\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r162it [02:26,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  161 === loss :  0.8993950486183167\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r163it [02:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  2 === Batch size :  162 === loss :  0.9945260882377625\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
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            "0it [00:00, ?it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  2 === Batch size :  163 === loss :  0.934842586517334\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r1it [00:00,  1.17it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  0 === loss :  1.1572418212890625\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r2it [00:01,  1.15it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  1 === loss :  1.0423613786697388\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r3it [00:02,  1.14it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  2 === loss :  1.264593482017517\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r4it [00:03,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  3 === loss :  0.8583299517631531\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r5it [00:04,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  4 === loss :  1.0088075399398804\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r6it [00:05,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  5 === loss :  0.9245854020118713\n"
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          "name": "stdout"
        },
        {
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            "\r7it [00:06,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  6 === loss :  0.9521806836128235\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r8it [00:07,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  7 === loss :  0.8705859184265137\n"
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          "name": "stdout"
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r9it [00:08,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  8 === loss :  0.9618826508522034\n"
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          "name": "stdout"
        },
        {
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            "\r10it [00:08,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r11it [00:09,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r12it [00:10,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  11 === loss :  0.8149069547653198\n"
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          "name": "stdout"
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        {
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            "\r13it [00:11,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r14it [00:12,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r15it [00:13,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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            "\r16it [00:14,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r17it [00:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r18it [00:16,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  17 === loss :  1.0520658493041992\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r19it [00:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  18 === loss :  1.0496491193771362\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r20it [00:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  19 === loss :  1.2498605251312256\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r21it [00:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  20 === loss :  1.1105133295059204\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r22it [00:19,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  21 === loss :  0.7927820086479187\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r23it [00:20,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  22 === loss :  1.185457468032837\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r24it [00:21,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  23 === loss :  0.9552035927772522\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r25it [00:22,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  24 === loss :  1.0922762155532837\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r26it [00:23,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  25 === loss :  1.0342292785644531\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r27it [00:24,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  26 === loss :  0.8633261322975159\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r28it [00:25,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  27 === loss :  0.754026472568512\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r29it [00:25,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  28 === loss :  0.9969364404678345\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r30it [00:26,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  29 === loss :  0.884423017501831\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r31it [00:27,  1.13it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  30 === loss :  1.1685718297958374\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r32it [00:28,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  31 === loss :  0.7975562810897827\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r33it [00:29,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  32 === loss :  0.9329569339752197\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r34it [00:30,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  33 === loss :  0.886788010597229\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r35it [00:31,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  34 === loss :  0.9606451392173767\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r36it [00:32,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  35 === loss :  0.785479724407196\n"
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          "name": "stdout"
        },
        {
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            "\r37it [00:33,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  36 === loss :  1.154921054840088\n"
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          "name": "stdout"
        },
        {
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            "\r38it [00:34,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  37 === loss :  1.1432610750198364\n"
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          "name": "stdout"
        },
        {
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            "\r39it [00:34,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  38 === loss :  0.8451611399650574\n"
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          "name": "stdout"
        },
        {
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            "\r40it [00:35,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r41it [00:36,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  40 === loss :  0.9068230390548706\n"
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          "name": "stdout"
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        {
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            "\r42it [00:37,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r43it [00:38,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  42 === loss :  1.0241405963897705\n"
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          "name": "stdout"
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        {
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            "\r44it [00:39,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  43 === loss :  0.8796861171722412\n"
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          "name": "stdout"
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        {
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            "\r45it [00:40,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r46it [00:41,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r47it [00:42,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r48it [00:43,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r49it [00:43,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r50it [00:44,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r51it [00:45,  1.12it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r52it [00:46,  1.12it/s]"
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          "name": "stderr"
        },
        {
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            "\r53it [00:47,  1.12it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r54it [00:48,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r55it [00:49,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r56it [00:50,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r57it [00:51,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r58it [00:52,  1.11it/s]"
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          "name": "stderr"
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        {
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        {
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          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  59 === loss :  1.110494613647461\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r61it [00:54,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  60 === loss :  0.793032169342041\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r62it [00:55,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  61 === loss :  0.8593171834945679\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r63it [00:56,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  62 === loss :  1.095743179321289\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r64it [00:57,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  63 === loss :  0.9402076005935669\n"
          ],
          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r65it [00:58,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  64 === loss :  0.8820508122444153\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r66it [00:59,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  65 === loss :  0.9566709995269775\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r67it [01:00,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  66 === loss :  0.8698666095733643\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r68it [01:01,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  67 === loss :  1.0003589391708374\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r69it [01:02,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  68 === loss :  0.9479342103004456\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r70it [01:02,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  69 === loss :  0.8036152124404907\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r71it [01:03,  1.12it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  70 === loss :  0.9402461647987366\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r72it [01:04,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  71 === loss :  0.8125666379928589\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r73it [01:05,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  72 === loss :  0.8728700280189514\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r74it [01:06,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  73 === loss :  0.8466455340385437\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r75it [01:07,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  74 === loss :  0.701949417591095\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r76it [01:08,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  75 === loss :  0.8544663190841675\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r77it [01:09,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  76 === loss :  0.6544561386108398\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r78it [01:10,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  77 === loss :  0.8249351382255554\n"
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          "name": "stdout"
        },
        {
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            "\r79it [01:11,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  78 === loss :  1.0785548686981201\n"
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          "name": "stdout"
        },
        {
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            "\r80it [01:11,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r81it [01:12,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r82it [01:13,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  81 === loss :  1.1443336009979248\n"
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          "name": "stdout"
        },
        {
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            "\r83it [01:14,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r84it [01:15,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r85it [01:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r86it [01:17,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r87it [01:18,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r88it [01:19,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r89it [01:20,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r90it [01:21,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r91it [01:21,  1.10it/s]"
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          "name": "stderr"
        },
        {
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        {
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          "name": "stderr"
        },
        {
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        {
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            "\r93it [01:23,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r94it [01:24,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
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          "name": "stderr"
        },
        {
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          "name": "stderr"
        },
        {
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          "name": "stderr"
        },
        {
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          "name": "stderr"
        },
        {
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        {
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          "name": "stderr"
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        {
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        {
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        {
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          "text": [
            "Epoch :  3 === Batch size :  101 === loss :  0.8814136385917664\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r103it [01:32,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  102 === loss :  1.0431572198867798\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r104it [01:33,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  103 === loss :  0.9545225501060486\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r105it [01:34,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  104 === loss :  1.2588187456130981\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r106it [01:35,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  105 === loss :  0.9983458518981934\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r107it [01:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  106 === loss :  0.8491871356964111\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r108it [01:37,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  107 === loss :  0.8689770698547363\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r109it [01:38,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  108 === loss :  0.8705731630325317\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r110it [01:39,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  109 === loss :  1.047959804534912\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r111it [01:40,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  110 === loss :  1.136268138885498\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r112it [01:41,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  111 === loss :  0.814959704875946\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r113it [01:41,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  112 === loss :  1.0038955211639404\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r114it [01:42,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  113 === loss :  0.8744809627532959\n"
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          "name": "stdout"
        },
        {
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            "\r115it [01:43,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  114 === loss :  1.0228744745254517\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r116it [01:44,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  115 === loss :  0.7834654450416565\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r117it [01:45,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  116 === loss :  0.8448362946510315\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r118it [01:46,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  117 === loss :  1.1046152114868164\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r119it [01:47,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  118 === loss :  0.9112563133239746\n"
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          "name": "stdout"
        },
        {
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            "\r120it [01:48,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  119 === loss :  0.8941587209701538\n"
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          "name": "stdout"
        },
        {
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            "\r121it [01:49,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  120 === loss :  1.1389970779418945\n"
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          "name": "stdout"
        },
        {
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            "\r122it [01:50,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  121 === loss :  0.8891412019729614\n"
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        {
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            "\r123it [01:50,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r124it [01:51,  1.12it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r125it [01:52,  1.12it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r126it [01:53,  1.12it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r127it [01:54,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r128it [01:55,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r129it [01:56,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r130it [01:57,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r131it [01:58,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r132it [01:59,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r133it [01:59,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r134it [02:00,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r135it [02:01,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r136it [02:02,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r137it [02:03,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r138it [02:04,  1.11it/s]"
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          "name": "stderr"
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        {
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            "\r139it [02:05,  1.11it/s]"
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          "name": "stderr"
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        {
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        {
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            "\r140it [02:06,  1.11it/s]"
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          "name": "stderr"
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        {
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        {
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        {
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        {
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        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  143 === loss :  0.7945758104324341\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r145it [02:10,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  144 === loss :  1.145180583000183\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r146it [02:11,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  145 === loss :  0.6800463199615479\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r147it [02:12,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  146 === loss :  0.9356593489646912\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r148it [02:13,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  147 === loss :  0.7542548179626465\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r149it [02:14,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  148 === loss :  0.7555288672447205\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r150it [02:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  149 === loss :  0.9627231955528259\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r151it [02:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  150 === loss :  0.5950695276260376\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r152it [02:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  151 === loss :  0.8277356028556824\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r153it [02:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  152 === loss :  1.0358951091766357\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r154it [02:19,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  153 === loss :  1.0519518852233887\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r155it [02:19,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  154 === loss :  0.9276103377342224\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r156it [02:20,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  155 === loss :  0.9674056172370911\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r157it [02:21,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  156 === loss :  0.9602484703063965\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r158it [02:22,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  157 === loss :  0.9634149074554443\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r159it [02:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  158 === loss :  0.9767882823944092\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r160it [02:24,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  159 === loss :  1.0232763290405273\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r161it [02:25,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  160 === loss :  1.0227100849151611\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r162it [02:26,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  161 === loss :  0.8591755032539368\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r163it [02:27,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  3 === Batch size :  162 === loss :  0.8250740766525269\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
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            "0it [00:00, ?it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  3 === Batch size :  163 === loss :  0.933533251285553\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r1it [00:00,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  0 === loss :  0.8664984107017517\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r2it [00:01,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  1 === loss :  0.7322503328323364\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r3it [00:02,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  2 === loss :  0.8751381039619446\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r4it [00:03,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  3 === loss :  0.8481124043464661\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r5it [00:04,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  4 === loss :  0.7983189821243286\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r6it [00:05,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  5 === loss :  0.7185738682746887\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r7it [00:06,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  6 === loss :  1.020872950553894\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r8it [00:07,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  7 === loss :  0.8501213788986206\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r9it [00:08,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  8 === loss :  0.9654288291931152\n"
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          "name": "stdout"
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        {
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            "\r10it [00:09,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  9 === loss :  0.9466255307197571\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r11it [00:10,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  10 === loss :  0.856397271156311\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r12it [00:10,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  11 === loss :  0.889927864074707\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r13it [00:11,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  12 === loss :  0.7868800163269043\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r14it [00:12,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r15it [00:13,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  14 === loss :  1.0404033660888672\n"
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        {
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            "\r16it [00:14,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  15 === loss :  0.7755497694015503\n"
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        {
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            "\r17it [00:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  16 === loss :  0.8441253900527954\n"
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          "name": "stdout"
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        {
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            "\r18it [00:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  17 === loss :  0.7247292399406433\n"
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          "name": "stdout"
        },
        {
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            "\r19it [00:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r20it [00:18,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r21it [00:19,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r22it [00:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  21 === loss :  0.500946044921875\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r23it [00:20,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  22 === loss :  0.9542162418365479\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r24it [00:21,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  23 === loss :  0.7538365721702576\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r25it [00:22,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  24 === loss :  1.015053391456604\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r26it [00:23,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  25 === loss :  0.9868842959403992\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r27it [00:24,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  26 === loss :  0.9530215263366699\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r28it [00:25,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  27 === loss :  0.8667609691619873\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r29it [00:26,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  28 === loss :  0.8319026827812195\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r30it [00:27,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  29 === loss :  0.8285677433013916\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r31it [00:28,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  30 === loss :  0.9301034808158875\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r32it [00:28,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  31 === loss :  0.786095142364502\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r33it [00:29,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  32 === loss :  0.9790844321250916\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r34it [00:30,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  33 === loss :  0.9975432753562927\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r35it [00:31,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  34 === loss :  0.6896728277206421\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r36it [00:32,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  35 === loss :  0.9360243082046509\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r37it [00:33,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  36 === loss :  0.6935852766036987\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r38it [00:34,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  37 === loss :  1.1031192541122437\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r39it [00:35,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  38 === loss :  0.9253653883934021\n"
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r40it [00:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  39 === loss :  0.8508484959602356\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r41it [00:37,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  40 === loss :  0.8449093699455261\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r42it [00:38,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  41 === loss :  0.7824530005455017\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r43it [00:38,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  42 === loss :  0.8332139253616333\n"
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          "name": "stdout"
        },
        {
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            "\r44it [00:39,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  43 === loss :  0.9600396752357483\n"
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          "name": "stdout"
        },
        {
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            "\r45it [00:40,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  44 === loss :  1.0956825017929077\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r46it [00:41,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  45 === loss :  1.025611162185669\n"
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          "name": "stdout"
        },
        {
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            "\r47it [00:42,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  46 === loss :  0.9312806725502014\n"
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          "name": "stdout"
        },
        {
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            "\r48it [00:43,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r49it [00:44,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  48 === loss :  0.9809194803237915\n"
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          "name": "stdout"
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        {
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            "\r50it [00:45,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r51it [00:46,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  50 === loss :  0.6872817873954773\n"
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          "name": "stdout"
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            "\r52it [00:47,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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            "\r53it [00:47,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r54it [00:48,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r55it [00:49,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r56it [00:50,  1.10it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r57it [00:51,  1.10it/s]"
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          "name": "stderr"
        },
        {
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            "\r58it [00:52,  1.10it/s]"
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          "name": "stderr"
        },
        {
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          "name": "stderr"
        },
        {
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        {
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            "\r60it [00:54,  1.10it/s]"
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          "name": "stderr"
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        {
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        {
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            "\r61it [00:55,  1.10it/s]"
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          "name": "stderr"
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        {
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            "\r62it [00:56,  1.10it/s]"
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        {
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        {
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r64it [00:57,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  63 === loss :  0.7406868934631348\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r65it [00:58,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  64 === loss :  0.7967129349708557\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r66it [00:59,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  65 === loss :  0.9074354767799377\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r67it [01:00,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  66 === loss :  1.150437831878662\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r68it [01:01,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  67 === loss :  0.6967400312423706\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r69it [01:02,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  68 === loss :  0.9105868935585022\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r70it [01:03,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  69 === loss :  1.0569331645965576\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r71it [01:04,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  70 === loss :  0.6526389122009277\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r72it [01:05,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  71 === loss :  0.909699022769928\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r73it [01:06,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  72 === loss :  1.024221658706665\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r74it [01:07,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  73 === loss :  0.6915532350540161\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r75it [01:07,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  74 === loss :  0.9412433505058289\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r76it [01:08,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  75 === loss :  0.7109341025352478\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r77it [01:09,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  76 === loss :  0.6623519659042358\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r78it [01:10,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  77 === loss :  0.9263431429862976\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r79it [01:11,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  78 === loss :  0.750304102897644\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r80it [01:12,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  79 === loss :  1.1301958560943604\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r81it [01:13,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  80 === loss :  0.719714343547821\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r82it [01:14,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  81 === loss :  0.8125583529472351\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r83it [01:15,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  82 === loss :  0.8571275472640991\n"
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          "name": "stdout"
        },
        {
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            "\r84it [01:16,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r85it [01:17,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  84 === loss :  0.7193264961242676\n"
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          "name": "stdout"
        },
        {
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            "\r86it [01:17,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  85 === loss :  0.6487815976142883\n"
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          "name": "stdout"
        },
        {
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            "\r87it [01:18,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r88it [01:19,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r89it [01:20,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r90it [01:21,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
        },
        {
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            "\r91it [01:22,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  90 === loss :  0.8349605798721313\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r92it [01:23,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r93it [01:24,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r94it [01:25,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r95it [01:26,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r96it [01:27,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r97it [01:27,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r98it [01:28,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r99it [01:29,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r100it [01:30,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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          "name": "stderr"
        },
        {
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        {
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            "\r102it [01:32,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r103it [01:33,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r104it [01:34,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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            "\r105it [01:35,  1.11it/s]"
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          "name": "stderr"
        },
        {
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        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r106it [01:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  105 === loss :  1.129616618156433\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r107it [01:36,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  106 === loss :  1.0162025690078735\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r108it [01:37,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  107 === loss :  0.8581556677818298\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r109it [01:38,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  108 === loss :  0.9475218057632446\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r110it [01:39,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  109 === loss :  1.076279640197754\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r111it [01:40,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  110 === loss :  0.9554503560066223\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r112it [01:41,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  111 === loss :  0.8229154348373413\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r113it [01:42,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  112 === loss :  1.0168852806091309\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r114it [01:43,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  113 === loss :  0.9538986086845398\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r115it [01:44,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  114 === loss :  0.9210459589958191\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r116it [01:45,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  115 === loss :  0.7105585336685181\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r117it [01:46,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  116 === loss :  0.8637657165527344\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r118it [01:46,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  117 === loss :  0.7723241448402405\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r119it [01:47,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  118 === loss :  1.0761427879333496\n"
          ],
          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r120it [01:48,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  119 === loss :  0.9175034165382385\n"
          ],
          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r121it [01:49,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  120 === loss :  0.9832116365432739\n"
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          "name": "stdout"
        },
        {
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          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r122it [01:50,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  121 === loss :  0.7831350564956665\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r123it [01:51,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  122 === loss :  0.9520175457000732\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r124it [01:52,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  123 === loss :  1.1239320039749146\n"
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          "name": "stdout"
        },
        {
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            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r125it [01:53,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  124 === loss :  0.8892635107040405\n"
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          "name": "stdout"
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        {
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            "\r126it [01:54,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  125 === loss :  1.0975168943405151\n"
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          "name": "stdout"
        },
        {
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            "\r127it [01:55,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r128it [01:56,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r129it [01:56,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  128 === loss :  0.8806100487709045\n"
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          "name": "stdout"
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        {
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            "\r130it [01:57,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r131it [01:58,  1.09it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r132it [01:59,  1.09it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "Epoch :  4 === Batch size :  131 === loss :  0.8667327165603638\n"
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          "name": "stdout"
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        {
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            "\r133it [02:00,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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          "name": "stdout"
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        {
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            "\r134it [02:01,  1.10it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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        {
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            "\r135it [02:02,  1.11it/s]"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r136it [02:03,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "\r137it [02:04,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r138it [02:05,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r139it [02:05,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
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            "\r140it [02:06,  1.12it/s]"
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          "name": "stderr"
        },
        {
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            "\r141it [02:07,  1.12it/s]"
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          "name": "stderr"
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        {
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            "\r142it [02:08,  1.11it/s]"
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          "name": "stderr"
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        {
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            "\r143it [02:09,  1.11it/s]"
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          "name": "stderr"
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        {
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            "\r144it [02:10,  1.11it/s]"
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        {
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            "\r145it [02:11,  1.11it/s]"
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          "name": "stderr"
        },
        {
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            "\r146it [02:12,  1.11it/s]"
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        {
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        {
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        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r148it [02:14,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  147 === loss :  0.9612146019935608\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r149it [02:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  148 === loss :  0.958970844745636\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r150it [02:15,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  149 === loss :  0.842115581035614\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r151it [02:16,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  150 === loss :  0.9518862962722778\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r152it [02:17,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  151 === loss :  0.8556625247001648\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r153it [02:18,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  152 === loss :  0.8244922757148743\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r154it [02:19,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  153 === loss :  0.7208001613616943\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r155it [02:20,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  154 === loss :  0.7811059951782227\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r156it [02:21,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  155 === loss :  0.7898170948028564\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r157it [02:22,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  156 === loss :  0.9899775385856628\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r158it [02:23,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  157 === loss :  0.937222957611084\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r159it [02:24,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  158 === loss :  0.7175519466400146\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r160it [02:24,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  159 === loss :  1.0250269174575806\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r161it [02:25,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  160 === loss :  0.8025585412979126\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r162it [02:26,  1.10it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  161 === loss :  1.0368340015411377\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r163it [02:27,  1.11it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  162 === loss :  0.7073191404342651\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "\r164it [02:28,  1.20it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch :  4 === Batch size :  163 === loss :  0.7601584196090698\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JsL2zBXsAFT_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2lGXXHulAFUB",
        "colab_type": "text"
      },
      "source": [
        "# Generating Predictions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7LHp4DpaEE4q",
        "colab_type": "code",
        "outputId": "05600690-180c-4c31-ea63-417c99761395",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "biterator = BasicIterator(batch_size=32)\n",
        "biterator.index_with(vocab)\n",
        "test_ds = [reader.read(tedata)][0]\n",
        "val_ds = None\n",
        "eval_iter = biterator(test_ds, shuffle=False, num_epochs=1)"
      ],
      "execution_count": 412,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "170it [00:00, 1456.66it/s]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wjZ4y_9aEjlm",
        "colab_type": "code",
        "outputId": "290a078f-bff3-4329-afae-34beaf9a9a1b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        }
      },
      "source": [
        "from sklearn.metrics import classification_report\n",
        "\n",
        "model.eval()\n",
        "n_correct = loss = totoal_size = 0\n",
        "with torch.no_grad():  # Important fixing.\n",
        "    ypredlst = []\n",
        "    ytruelst = []\n",
        "    for batch_idx, batch in enumerate(eval_iter):\n",
        "        batch = nn_util.move_to_device(batch, 0 if USE_GPU else -1)\n",
        "        (out, attn), s1 = model(batch)\n",
        "        y = batch['label'].squeeze(1)\n",
        "        y = y.type(torch.LongTensor).cuda()\n",
        "\n",
        "        n_correct += (torch.max(out, 1)[1].view(y.size()) == y).sum().item()\n",
        "\n",
        "        \n",
        "        loss += criterion(out, y).item() * y.size(0)\n",
        "        totoal_size += y.size(0)\n",
        "\n",
        "        \n",
        "        ypredlst.extend(torch.max(out, 1)[1].cpu().tolist())\n",
        "        ytruelst.extend(y.cpu().tolist())\n",
        "\n",
        "    print(ytruelst, ypredlst)\n",
        "    print(classification_report(ytruelst, ypredlst))\n",
        "    avg_acc = 100. * n_correct / totoal_size\n",
        "    avg_loss = loss / totoal_size\n",
        "\n",
        "    print(avg_acc)"
      ],
      "execution_count": 413,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "[1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 3, 0, 0, 1, 0, 3, 3, 0, 1, 0, 0, 0, 0, 4, 0, 2, 1, 0, 1, 3, 1, 1, 4, 1, 0, 1, 0, 1, 1, 1, 2, 0, 3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 3, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 4, 0, 0, 0, 0, 0, 1, 1, 0, 0, 3, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 2, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 3, 2, 0, 4, 1, 0, 0, 1, 1, 3, 0, 4, 1, 1, 3, 0, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 1, 0, 0, 0, 4, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 3, 0, 0, 1, 0, 0, 4, 1, 0, 1, 0] [0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.63      0.88      0.73        97\n",
            "           1       0.54      0.39      0.45        49\n",
            "           2       0.00      0.00      0.00         4\n",
            "           3       0.00      0.00      0.00        12\n",
            "           4       0.00      0.00      0.00         8\n",
            "\n",
            "    accuracy                           0.61       170\n",
            "   macro avg       0.23      0.25      0.24       170\n",
            "weighted avg       0.52      0.61      0.55       170\n",
            "\n",
            "61.1764705882353\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "  _warn_prf(average, modifier, msg_start, len(result))\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yPnmoBTjQyIl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def save_model(fname):\n",
        "    torch.save(model.state_dict(), fname)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nJFkkT1ARbqK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "save_model('bigmodel')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wdQP6ZENVE2_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "%matplotlib inline\n",
        "import matplotlib\n",
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K6yoSEEdVG5M",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import matplotlib.ticker as ticker\n",
        "import pickle"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TKhoYCOPAFUH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def show_attention(input_sentence, output_words, attentions, spl=100):\n",
        "    # Set up figure with colorbar\n",
        "    r=len(input_sentence)//spl+1\n",
        "    fig = plt.figure(figsize=(500,8*r))\n",
        "    \n",
        "    for i in range(r):\n",
        "        ax = fig.add_subplot(r,1,i+1)\n",
        "        cax = ax.matshow(attentions[:,i*spl:i*spl+spl], cmap='bone', vmin=0., vmax=1.1)\n",
        "        fig.colorbar(cax)\n",
        "\n",
        "        # Set up axes\n",
        "        ax.set_xticklabels([''] + input_sentence[i*spl:i*spl+spl], rotation=90)\n",
        "        ax.set_yticklabels([''] + output_words)\n",
        "\n",
        "        # Show label at every tick\n",
        "        ax.xaxis.set_major_locator(ticker.MultipleLocator(1))\n",
        "        ax.yaxis.set_major_locator(ticker.MultipleLocator(1))\n",
        "\n",
        "    plt.show()\n",
        "    plt.close()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rAQgB82YSgzn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 689
        },
        "outputId": "f40d80f8-8d6d-4865-b1b9-dcefeee8a5f0"
      },
      "source": [
        "model.eval()\n",
        "n_correct = loss = totoal_size = 0\n",
        "with torch.no_grad():  # Important fixing.\n",
        "\n",
        "    for batch_idx, batch in enumerate(eval_iter):\n",
        "        batch = nn_util.move_to_device(batch, 0 if USE_GPU else -1)\n",
        "        (out, attn), s1 = model(batch)\n",
        "        if '[PAD]' in s1[0]:\n",
        "          padding=s1[0].index('[PAD]')\n",
        "        else:\n",
        "          padding=len(s1[0])\n",
        "        show_attention(s1[0][:padding],s1[0][:padding],attn.cpu()[0][:padding,:padding])\n",
        "        break"
      ],
      "execution_count": 222,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tensor([[  101,  1031, 18856,  2015,  1033,  5912, 11320, 21504,  1006,  2254,\n",
            "          2324,  1010, 12094,  1011,  1011,  2254,  2321,  1010,  7257,  1007,\n",
            "          2001,  1037,  9137,  1011,  2301,  2137,  6883,  1010, 13891,  5797,\n",
            "          1998, 13448,  1031,  8827, 16344,  1033,  2137,  1031,  7279,  2094,\n",
            "          1033,   102]], device='cuda:0')\n",
            "['[CLS]', '[', 'cl', '##s', ']', 'nelson', 'lu', '##dington', '(', 'january', '18', ',', '1818', '-', '-', 'january', '15', ',', '1883', ')', 'was', 'a', 'nineteenth', '-', 'century', 'american', 'businessman', ',', 'lumber', 'baron', 'and', 'banker', '[', 'ps', '##tr', ']', 'american', '[', 'pen', '##d', ']', '[SEP]']\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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pJ1CSR1XVcUmePtX5qvp6v0lW1eVJOg/dOk3T7yd5bFX9eKZ4STbpeLmAZj/z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\nQzua7NIu8b0X8DngA1V1Tnv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            "text/plain": [
              "<Figure size 36000x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "izukhLlqQi6I",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "outputId": "9627ec3f-0de9-426d-e449-b937c10a20cc"
      },
      "source": [
        "tedata"
      ],
      "execution_count": 215,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>186</th>\n",
              "      <td>186</td>\n",
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              "      <th>126</th>\n",
              "      <td>126</td>\n",
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              "      <th>258</th>\n",
              "      <td>258</td>\n",
              "      <td>it also managed to reach # 11 on the us billbo...</td>\n",
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              "      <td>[CLS] it also managed to reach # 11 on the us ...</td>\n",
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              "      <th>457</th>\n",
              "      <td>457</td>\n",
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              "      <th>268</th>\n",
              "      <td>268</td>\n",
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              "      <td>['[CLS]', 'in', '1887', '[ps]', ',', 'he', 're...</td>\n",
              "      <td>[CLS] in 1887 [ps] , he returned to london as ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>552</th>\n",
              "      <td>552</td>\n",
              "      <td>a branch of the luo , the shilluk ( or chollo ...</td>\n",
              "      <td>a chief named</td>\n",
              "      <td>a branch of the luo , the shilluk ( or chollo ...</td>\n",
              "      <td>Elaboration(insert a fact or new meaningful as...</td>\n",
              "      <td>['a', 'branch', 'of', 'the', 'luo', ',', 'the'...</td>\n",
              "      <td>['a', 'chief', 'named']</td>\n",
              "      <td>['[CLS]', '[ps]', 'a', 'branch', 'of', 'the', ...</td>\n",
              "      <td>[CLS] [ps] a branch of the luo , the shilluk (...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>255 rows × 9 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0  ...                                         Final_Text\n",
              "213         213  ...  [CLS] nelson ludington ( january 18 , 1818 -- ...\n",
              "431         431  ...  [CLS] currently [ps] senior 's [pe] union has ...\n",
              "137         137  ...  [CLS] from 1990 to 2004 , he was member of the...\n",
              "316         316  ...  [CLS] the patronage of the church of holm then...\n",
              "186         186  ...  [CLS] sceptic is a polish death metal band fro...\n",
              "..          ...  ...                                                ...\n",
              "126         126  ...  [CLS] the song that was written also by larraz...\n",
              "258         258  ...  [CLS] it also managed to reach # 11 on the us ...\n",
              "457         457  ...  [CLS] international labor migration surged dur...\n",
              "268         268  ...  [CLS] in 1887 [ps] , he returned to london as ...\n",
              "552         552  ...  [CLS] [ps] a branch of the luo , the shilluk (...\n",
              "\n",
              "[255 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 215
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jf9MvJ4sYj5d",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "l=[1.33,1.02,0.97,0.86,0.72]\n",
        "l = pd.DataFrame(l,columns=['Loss'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1a4gWmyebwDa",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "outputId": "4756744c-0d73-474f-cff2-f70e601f05ad"
      },
      "source": [
        "l.plot(title='Epoch VS Loss')"
      ],
      "execution_count": 228,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0fe94217f0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 228
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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M9ozo0znokkSkhTP3YMaR8/LyvKioKJB9x4ode8u44J532b6vjOe+N5pendsFXZKIxDgz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\no6/sAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6ljc-MNNcJDQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}