Moores_Law.ipynb

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        "<a href=\"https://colab.research.google.com/github/selimunal/Pytorch/blob/main/Moores_Law.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "execution_count": null,
      "metadata": {
        "id": "9ECRpQS9hXUJ"
      },
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      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#get the data\n",
        "!wget -nc https://raw.githubusercontent.com/lazyprogrammer/machine_learning_examples/master/linear_regression_class/moore.csv"
      ],
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "File ‘moore.csv’ already there; not retrieving.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ls"
      ],
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        },
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        "outputId": "64f61204-1083-4019-9e59-a750587b378c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "moore.csv  \u001b[0m\u001b[01;34msample_data\u001b[0m/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data=pd.read_csv(\"moore.csv\",sep='\\t',header=None)#.values"
      ],
      "metadata": {
        "id": "pbFNNhbeCrTr"
      },
      "execution_count": null,
      "outputs": []
    },
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        "data"
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              "                                         0                   1     2  \\\n",
              "0                               Intel 4004               2,300  1971   \n",
              "1                               Intel 8008               3,500  1972   \n",
              "2                               Intel 8080               4,500  1974   \n",
              "3                            Motorola 6800               4,100  1974   \n",
              "4                                 RCA 1802               5,000  1974   \n",
              "..                                     ...                 ...   ...   \n",
              "97                                 IBM z13       3,990,000,000  2015   \n",
              "98              IBM z13 Storage Controller       7,100,000,000  2015   \n",
              "99   Quad-core + GPU GT2 Core i7 Skylake K   cca 1,750,000,000  2015   \n",
              "100                               SPARC M7  10,000,000,000[37]  2015   \n",
              "101              22-core Xeon Broadwell-E5  ~7,200,000,000[36]  2016   \n",
              "\n",
              "            3          4        5  \n",
              "0       Intel  10,000 nm   12 mm²  \n",
              "1       Intel  10,000 nm   14 mm²  \n",
              "2       Intel   6,000 nm   20 mm²  \n",
              "3    Motorola   6,000 nm   16 mm²  \n",
              "4         RCA   5,000 nm   27 mm²  \n",
              "..        ...        ...      ...  \n",
              "97        IBM      22 nm  678 mm²  \n",
              "98        IBM      22 nm  678 mm²  \n",
              "99      Intel      14 nm  122 mm²  \n",
              "100    Oracle      20 nm      NaN  \n",
              "101     Intel      14 nm  456 mm²  \n",
              "\n",
              "[102 rows x 6 columns]"
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              "(102,)"
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              "0       1971\n",
              "1       1972\n",
              "2       1974\n",
              "3       1974\n",
              "4       1974\n",
              "5    1974[7]\n",
              "6       1975\n",
              "7       1976\n",
              "8       1976\n",
              "9       1978\n",
              "Name: 2, dtype: object"
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          "execution_count": 7
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              "0    1971\n",
              "1    1972\n",
              "2    1974\n",
              "3    1974\n",
              "4    1974\n",
              "5    1974\n",
              "6    1975\n",
              "7    1976\n",
              "8    1976\n",
              "9    1978\n",
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              "(102,)"
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          "execution_count": 10
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              "0       2,300\n",
              "1       3,500\n",
              "2       4,500\n",
              "3       4,100\n",
              "4       5,000\n",
              "5       8,000\n",
              "6    3,510[8]\n",
              "7       6,500\n",
              "8       8,500\n",
              "9      29,000\n",
              "Name: 1, dtype: object"
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          "execution_count": 11
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              "0     2,300\n",
              "1     3,500\n",
              "2     4,500\n",
              "3     4,100\n",
              "4     5,000\n",
              "5     8,000\n",
              "6     3,510\n",
              "7     6,500\n",
              "8     8,500\n",
              "9    29,000\n",
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              "0      1971\n",
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              "       ... \n",
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              "array(['2,300', '3,500', '4,500', '4,100', '5,000', '8,000', '3,510',\n",
              "       '6,500', '8,500', '29,000', '9,000', '29,000', '68,000', '11,500',\n",
              "       '55,000', '134,000', '22,000', '190,000', '25,000', '275,000',\n",
              "       '16,000', '30,000', '553,000', '180,000', '250,000', '300,000',\n",
              "       '1,180,235', '35,000', '1,350,000', '3,100,000', '578,977',\n",
              "       '5,500,000', '2,500,000', '4,300,000', '8,800,000', '7,500,000',\n",
              "       '7,500,000', '21,300,000', '22,000,000', '111,000', '27,400,000',\n",
              "       '9,500,000', '42,000,000', '21,000,000', '45,000,000',\n",
              "       '220,000,000', '55,000,000', '105,900,000', '54,300,000',\n",
              "       '410,000,000', '592,000,000', '112,000,000', '169,000,000',\n",
              "       '228,000,000', '241,000,000', '291,000,000', '1,700,000,000',\n",
              "       '184,000,000', '362,000,000', '463,000,000', '26,000,000',\n",
              "       '169,000,000', '411,000,000', '789,000,000', '758,000,000',\n",
              "       '47,000,000', '230,000,000', '731,000,000', '1,900,000,000',\n",
              "       '904,000,000', '1,000,000,000', '1,200,000,000', '2,300,000,000',\n",
              "       '2,000,000,000', '1,400,000,000', '1,170,000,000', '2,600,000,000',\n",
              "       '1,160,000,000', '2,270,000,000', '5,000,000,000', '1,200,000,000',\n",
              "       '3,100,000,000', '2,100,000,000', '1,303,000,000', '1,400,000,000',\n",
              "       '2,750,000,000', '4,200,000,000', '1,000,000,000', '1,860,000,000',\n",
              "       '5,000,000,000', '4,310,000,000', '5,560,000,000', '2,600,000,000',\n",
              "       '2,000,000,000', '3,000,000,000', '1,400,000,000', '1,900,000,000',\n",
              "       '3,990,000,000', '7,100,000,000', 'cca 1,750,000,000',\n",
              "       '10,000,000,000', '~7,200,000,000'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,6))\n",
        "plt.scatter(X,Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "id": "CHXWqXxzDK-J",
        "outputId": "c70b93a3-8a97-4e59-b9e5-9c4ef18ba745"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7fa413d1bf90>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X=X.values.reshape(-1,1)\n",
        "Y=Y.reshape(-1,1)"
      ],
      "metadata": {
        "id": "wI8YjDybcstZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uO4A3DBtpc6-",
        "outputId": "6806a875-c2e9-4674-9b6f-b1803a2924f2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(102, 1)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "btSRMfFSpktN",
        "outputId": "9f9cca54-3e99-47fd-ceb8-fac5306fe1d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(102, 1)"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X=X[:,0]"
      ],
      "metadata": {
        "id": "LK6_gxUSt1zV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Y=Y[:,0]\n"
      ],
      "metadata": {
        "id": "Es1EH4ENt3G1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.scatter(X,Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "id": "VMnjO7SSuT1-",
        "outputId": "a592d4af-c954-400d-d3fc-d833af1d97c1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7fa4136b1490>"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y=Y.astype(str)"
      ],
      "metadata": {
        "id": "kZb4MYjyu1H-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "replace_func = np.vectorize(lambda x: (x.replace(',','')))"
      ],
      "metadata": {
        "id": "23mpuKTZ0TLe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Y[99]='1,750,000,000'"
      ],
      "metadata": {
        "id": "3r_JB_iT1rou"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "N7Tn6XoZ13zO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Y[101]='7,200,000,000'"
      ],
      "metadata": {
        "id": "Y6lDFyAx29GG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Y=replace_func(Y).astype(float)"
      ],
      "metadata": {
        "id": "CfFmxU7U3j0-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X=X.astype(float)"
      ],
      "metadata": {
        "id": "sRy7BH523pbm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.scatter(X,Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "0RUIlRK23wg2",
        "outputId": "28627986-33f4-4560-fc64-6d10d837172a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7fa411c83210>"
            ]
          },
          "metadata": {},
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y=np.log(Y)"
      ],
      "metadata": {
        "id": "k99WMkt131uG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.scatter(X,Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "4rs2W2Zm5zr-",
        "outputId": "5569609d-face-4a02-da03-c94f07e5635a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7fa411c6cf90>"
            ]
          },
          "metadata": {},
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Preprocessing\n",
        "mx=X.mean()\n",
        "sx=X.std()\n",
        "my=Y.mean()\n",
        "sy=Y.std()"
      ],
      "metadata": {
        "id": "erdW90X951fO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X=(X-mx)/sx\n",
        "Y=(Y-my)/sy\n",
        "plt.scatter(X,Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "Cvf_wrFL9L7W",
        "outputId": "e10fba41-6d8c-424f-e061-97b467f97f05"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7fa411bdac10>"
            ]
          },
          "metadata": {},
          "execution_count": 33
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Convert the data to float32\n",
        "X=X.astype(np.float32)\n",
        "Y=Y.astype(np.float32)"
      ],
      "metadata": {
        "id": "a7hVPUBm9U12"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X=X.reshape(-1,1)"
      ],
      "metadata": {
        "id": "kZ9Tk9QU1qMb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DqfTDYnKDd_L",
        "outputId": "54c85414-462c-4bfd-8dd2-a744f0adc66e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(102, 1)"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y=Y.reshape(-1,1)"
      ],
      "metadata": {
        "id": "EXMfX40-Dl26"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model=nn.Linear(1,1)"
      ],
      "metadata": {
        "id": "ETwI0u4fDoei"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Convert the data to float32\n",
        "X=X.astype(np.float32)\n",
        "Y=Y.astype(np.float32)"
      ],
      "metadata": {
        "id": "RQzVN2Z8Gj_S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#LOSS AND OPTİMİZER\n",
        "criterion=nn.MSELoss()\n",
        "optimizer=torch.optim.SGD(model.parameters(),lr=0.01,momentum=0.7)\n",
        "inputs=torch.from_numpy(X)\n",
        "targets=torch.from_numpy(Y)"
      ],
      "metadata": {
        "id": "LLMzPyphD5Jx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#TRAIN THE MODEL\n",
        "n_epochs=100\n",
        "losses=[]\n",
        "\n",
        "for it in range(n_epochs):\n",
        "  #zero the parameter gradients\n",
        "  optimizer.zero_grad() #zero the parameter gradients\n",
        "  #forward pass\n",
        "  outputs=model(inputs) #forward pass  \n",
        "  \n",
        "  loss=criterion(outputs,targets)\n",
        "  \n",
        "  \n",
        "  #record the loss\n",
        "  losses.append(loss.item()) # record the loss\n",
        "  \n",
        "  #loss.requires_grad = True\n",
        "  #loss.retain_grad()\n",
        "  loss.backward() #backward and optimizer\n",
        "\n",
        "  optimizer.step()\n",
        "\n",
        "  print(f'Epoch {it+1}/{n_epochs},Loss:{loss.item():.4f}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c5ocCipbD7PC",
        "outputId": "d5227d19-99f1-4e9b-a8d8-13f209ad9292"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100,Loss:2.1542\n",
            "Epoch 2/100,Loss:2.0707\n",
            "Epoch 3/100,Loss:1.9343\n",
            "Epoch 4/100,Loss:1.7688\n",
            "Epoch 5/100,Loss:1.5916\n",
            "Epoch 6/100,Loss:1.4145\n",
            "Epoch 7/100,Loss:1.2452\n",
            "Epoch 8/100,Loss:1.0882\n",
            "Epoch 9/100,Loss:0.9457\n",
            "Epoch 10/100,Loss:0.8186\n",
            "Epoch 11/100,Loss:0.7065\n",
            "Epoch 12/100,Loss:0.6087\n",
            "Epoch 13/100,Loss:0.5239\n",
            "Epoch 14/100,Loss:0.4510\n",
            "Epoch 15/100,Loss:0.3885\n",
            "Epoch 16/100,Loss:0.3352\n",
            "Epoch 17/100,Loss:0.2899\n",
            "Epoch 18/100,Loss:0.2515\n",
            "Epoch 19/100,Loss:0.2190\n",
            "Epoch 20/100,Loss:0.1915\n",
            "Epoch 21/100,Loss:0.1684\n",
            "Epoch 22/100,Loss:0.1489\n",
            "Epoch 23/100,Loss:0.1325\n",
            "Epoch 24/100,Loss:0.1187\n",
            "Epoch 25/100,Loss:0.1071\n",
            "Epoch 26/100,Loss:0.0974\n",
            "Epoch 27/100,Loss:0.0892\n",
            "Epoch 28/100,Loss:0.0824\n",
            "Epoch 29/100,Loss:0.0766\n",
            "Epoch 30/100,Loss:0.0718\n",
            "Epoch 31/100,Loss:0.0678\n",
            "Epoch 32/100,Loss:0.0644\n",
            "Epoch 33/100,Loss:0.0616\n",
            "Epoch 34/100,Loss:0.0592\n",
            "Epoch 35/100,Loss:0.0572\n",
            "Epoch 36/100,Loss:0.0556\n",
            "Epoch 37/100,Loss:0.0542\n",
            "Epoch 38/100,Loss:0.0530\n",
            "Epoch 39/100,Loss:0.0521\n",
            "Epoch 40/100,Loss:0.0512\n",
            "Epoch 41/100,Loss:0.0506\n",
            "Epoch 42/100,Loss:0.0500\n",
            "Epoch 43/100,Loss:0.0495\n",
            "Epoch 44/100,Loss:0.0491\n",
            "Epoch 45/100,Loss:0.0488\n",
            "Epoch 46/100,Loss:0.0485\n",
            "Epoch 47/100,Loss:0.0483\n",
            "Epoch 48/100,Loss:0.0481\n",
            "Epoch 49/100,Loss:0.0479\n",
            "Epoch 50/100,Loss:0.0478\n",
            "Epoch 51/100,Loss:0.0476\n",
            "Epoch 52/100,Loss:0.0476\n",
            "Epoch 53/100,Loss:0.0475\n",
            "Epoch 54/100,Loss:0.0474\n",
            "Epoch 55/100,Loss:0.0473\n",
            "Epoch 56/100,Loss:0.0473\n",
            "Epoch 57/100,Loss:0.0473\n",
            "Epoch 58/100,Loss:0.0472\n",
            "Epoch 59/100,Loss:0.0472\n",
            "Epoch 60/100,Loss:0.0472\n",
            "Epoch 61/100,Loss:0.0472\n",
            "Epoch 62/100,Loss:0.0471\n",
            "Epoch 63/100,Loss:0.0471\n",
            "Epoch 64/100,Loss:0.0471\n",
            "Epoch 65/100,Loss:0.0471\n",
            "Epoch 66/100,Loss:0.0471\n",
            "Epoch 67/100,Loss:0.0471\n",
            "Epoch 68/100,Loss:0.0471\n",
            "Epoch 69/100,Loss:0.0471\n",
            "Epoch 70/100,Loss:0.0471\n",
            "Epoch 71/100,Loss:0.0471\n",
            "Epoch 72/100,Loss:0.0471\n",
            "Epoch 73/100,Loss:0.0471\n",
            "Epoch 74/100,Loss:0.0471\n",
            "Epoch 75/100,Loss:0.0471\n",
            "Epoch 76/100,Loss:0.0471\n",
            "Epoch 77/100,Loss:0.0471\n",
            "Epoch 78/100,Loss:0.0471\n",
            "Epoch 79/100,Loss:0.0471\n",
            "Epoch 80/100,Loss:0.0471\n",
            "Epoch 81/100,Loss:0.0471\n",
            "Epoch 82/100,Loss:0.0471\n",
            "Epoch 83/100,Loss:0.0471\n",
            "Epoch 84/100,Loss:0.0471\n",
            "Epoch 85/100,Loss:0.0471\n",
            "Epoch 86/100,Loss:0.0471\n",
            "Epoch 87/100,Loss:0.0471\n",
            "Epoch 88/100,Loss:0.0471\n",
            "Epoch 89/100,Loss:0.0471\n",
            "Epoch 90/100,Loss:0.0471\n",
            "Epoch 91/100,Loss:0.0471\n",
            "Epoch 92/100,Loss:0.0471\n",
            "Epoch 93/100,Loss:0.0471\n",
            "Epoch 94/100,Loss:0.0471\n",
            "Epoch 95/100,Loss:0.0471\n",
            "Epoch 96/100,Loss:0.0471\n",
            "Epoch 97/100,Loss:0.0471\n",
            "Epoch 98/100,Loss:0.0471\n",
            "Epoch 99/100,Loss:0.0471\n",
            "Epoch 100/100,Loss:0.0471\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#loss per iteration\n",
        "plt.plot(losses)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "bVDdYm_CD9SK",
        "outputId": "7a90ecc8-1865-46c5-d7b8-bcb3950e39ea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fa411b63390>]"
            ]
          },
          "metadata": {},
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#prediction\n",
        "predicted=model(torch.from_numpy(X)).detach().numpy()\n",
        "plt.plot(X,Y,'ro',label='Original Data')\n",
        "plt.plot(X,predicted,label='predicted data')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "Gl1lLMU3LENZ",
        "outputId": "c2c4aaef-d49d-4f37-db18-bb4dbd4d8129"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#what does this mean?\n",
        "w=model.weight.data.numpy()\n",
        "print(w)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8gOn-9voL00x",
        "outputId": "d24f3ad3-0aff-4d79-93c2-dfcd90b900ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0.9759745]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a=w[0,0]*sy/sx"
      ],
      "metadata": {
        "id": "tnOx8YAUfrOJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dMd8HsiQfxvo",
        "outputId": "1bac6561-d67c-4632-8cc3-675ba4b54a0a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.35096656285166006"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Time to double:',np.log(2)/a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mp-eWEpafylR",
        "outputId": "8b69bd3f-4324-4497-f18d-1142beceaa79"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Time to double: 1.9749664324943448\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "0JOVpnDSf8FI"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}