architecture updates

CHANGELOG.md

@@ -8,6 +8,24 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
+-
+
+### Changed
+
+- 
+
+### Removed
+
+- 
+
+### Fixed
+
+- 
+
+
+## [20.05.1] - 2020-05-23
+
+### Added
 
 - Circle loss implementation ([#802](https://github.com/catalyst-team/catalyst/pull/802))
 - BatchBalanceSampler for metric learning and classification ([#806](https://github.com/catalyst-team/catalyst/pull/806))
@@ -31,6 +49,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - device selection fix for [#798](https://github.com/catalyst-team/catalyst/issues/798) ([#815](https://github.com/catalyst-team/catalyst/pull/815))
 - batch size counting fix for [#799](https://github.com/catalyst-team/catalyst/issues/799) and [#755](https://github.com/catalyst-team/catalyst/issues/755) issues ([#809](https://github.com/catalyst-team/catalyst/pull/809))
 
+
 ## [20.05] - 2020-05-07
 
 ### Added
@@ -91,3 +110,22 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 ### Fixed
 
 - 
+
+
+## [YY.MM.R] - YYYY-MM-DD
+
+### Added
+
+-
+
+### Changed
+
+- 
+
+### Removed
+
+- 
+
+### Fixed
+
+- 

README.md

@@ -49,7 +49,8 @@ import torch
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from catalyst import dl
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.utils import metrics
 
 model = torch.nn.Linear(28 * 28, 10)
@@ -212,7 +213,8 @@ import torch
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from catalyst import dl
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.utils import metrics
 
 model = torch.nn.Linear(28 * 28, 10)
@@ -265,7 +267,8 @@ from torch import nn
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from catalyst import dl
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.utils import metrics
 
 class ClassifyAE(nn.Module):
@@ -338,7 +341,8 @@ from torch import nn
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from catalyst import dl
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.utils import metrics
 
 LOG_SCALE_MAX = 2
@@ -436,7 +440,8 @@ from torch import nn
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from catalyst import dl
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.utils import metrics
 
 class ClassifyUnet(nn.Module):
@@ -511,7 +516,8 @@ from torch import nn
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from catalyst import dl
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.contrib.nn.modules import Flatten, GlobalMaxPool2d, Lambda
 
 latent_dim = 128
@@ -668,7 +674,8 @@ import torch
 from torch import nn
 from torch.nn import functional as F
 from catalyst import dl, utils
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.utils import metrics
 
 class ClassifyAE(nn.Module):
@@ -749,15 +756,24 @@ utils.distributed_cmd_run(train)
 
 
 ### Structure
-- **contrib** - additional modules contributed by Catalyst users.
 - **core** - framework core with main abstractions - 
     Experiment, Runner, Callback and State.
 - **data** - useful tools and scripts for data processing.
 - **dl** – runner for training and inference,
    all of the classic ML and CV/NLP/RecSys metrics
    and a variety of callbacks for training, validation
    and inference of neural networks.
-- **utils** - typical utils for Deep Learning research.
+- **tools** - extra tools for Deep Learning research, class-based helpers.   
+- **utils** - typical utils for Deep Learning research, function-based helpers.
+- **contrib** - additional modules contributed by Catalyst users.
+    - contrib/data - extra data-tools for CV, NLP and RecSys.
+    - contrib/datasets - typical datasets, such as MNIST, etc.
+    - contrib/dl - extensions for `catalyst.dl`
+    - contrib/models - predefined models for CV, NLP and RecSys.
+    - contrib/nn - extra PyTorch modules.
+    - contrib/scripts - user scripts for common deep learning routine.
+    - contrib/tools - `catalyst.tools` extensions. 
+    - contrib/utils - `catalyst.utils` extensions.
 
 
 ### Tests

catalyst/__version__.py

@@ -1 +1 @@
-__version__ = "20.05"
+__version__ = "20.05.1"

catalyst/contrib/data/__init__.py

@@ -0,0 +1,3 @@
+# flake8: noqa
+
+from .transforms import Compose, Normalize, normalize, to_tensor, ToTensor

catalyst/contrib/data/nlp/__init__.py

@@ -1,3 +1,2 @@
 # flake8: noqa
-from .classification import *
-from .language_modeling import *
+from .dataset import *

catalyst/contrib/data/nlp/dataset/__init__.py

@@ -0,0 +1,8 @@
+# flake8: noqa
+
+from catalyst.contrib.data.nlp.dataset.language_modeling import (
+    LanguageModelingDataset,
+)
+from catalyst.contrib.data.nlp.dataset.text_classification import (
+    TextClassificationDataset,
+)

catalyst/contrib/data/nlp/language_modeling/tests/test_dataset.py → catalyst/contrib/data/nlp/dataset/tests/test_language_modeling_dataset.py

@@ -3,7 +3,7 @@
 import torch  # noqa: F401
 from transformers import AutoTokenizer
 
-from catalyst.contrib.data.nlp.language_modeling import LanguageModelingDataset
+from catalyst.contrib.data.nlp.dataset import LanguageModelingDataset
 
 texts = [
     """Bonaparte Crossing the Alps is an oil-on-canvas painting by French artist""",  # noqa: E501

catalyst/contrib/data/nlp/classification/tests/test_text_clf_dataset.py → catalyst/contrib/data/nlp/dataset/tests/test_text_classification_dataset.py

@@ -1,4 +1,4 @@
-from catalyst.contrib.data.nlp.classification import TextClassificationDataset
+from catalyst.contrib.data.nlp.dataset import TextClassificationDataset
 
 texts = [
     "The color of this T-shirt is sooo so horrible",

catalyst/contrib/data/dataset/transforms.py → catalyst/contrib/data/transforms.py

@@ -1,3 +1,8 @@
+"""
+This subpackage was borrowed from
+torchvision(https://github.com/pytorch/vision).
+"""
+
 import numpy as np
 
 import torch
@@ -149,3 +154,6 @@ def __repr__(self):
         return self.__class__.__name__ + "(mean={0}, std={1})".format(
             self.mean, self.std
         )
+
+
+__all__ = ["Compose", "Normalize", "ToTensor", "normalize", "to_tensor"]

catalyst/contrib/datasets/__init__.py

@@ -0,0 +1,3 @@
+# flake8: noqa
+
+from catalyst.contrib.datasets.mnist import MNIST

catalyst/contrib/data/dataset/mnist.py → catalyst/contrib/datasets/mnist.py

@@ -6,7 +6,7 @@
 import torch
 from torch.utils.data import Dataset
 
-from catalyst.contrib.data.dataset.utils import download_and_extract_archive
+from catalyst.contrib.datasets.utils import download_and_extract_archive
 
 
 class MNIST(Dataset):

catalyst/contrib/dl/callbacks/tests/test_optimizer_callback.py

@@ -9,7 +9,8 @@
 from torch.utils.data import DataLoader
 
 from catalyst.contrib import registry
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.contrib.dl.callbacks.optimizer import SaveModelGradsCallback
 from catalyst.core import (
     Callback,

catalyst/contrib/dl/callbacks/tests/test_trace_callback.py

@@ -9,7 +9,8 @@
 from torch.utils.data import DataLoader
 
 from catalyst.contrib import registry
-from catalyst.contrib.data.dataset import MNIST, ToTensor
+from catalyst.contrib.data.transforms import ToTensor
+from catalyst.contrib.datasets import MNIST
 from catalyst.contrib.dl.callbacks.trace import TracerCallback
 from catalyst.core import (
     Callback,

catalyst/contrib/utils/tools/tests/test_tensorboard.py → catalyst/contrib/tools/tests/test_tensorboard.py

@@ -7,7 +7,7 @@
 import numpy as np
 import pytest
 
-from catalyst.contrib.utils.tools.tensorboard import (
+from catalyst.contrib.tools.tensorboard import (
     EventReadingException,
     EventsFileReader,
     SummaryReader,

catalyst/contrib/utils/cv/tests/test_image.py

@@ -3,7 +3,7 @@
 import torch
 
 from catalyst import utils
-from catalyst.contrib.data.dataset.transforms import normalize, to_tensor
+from catalyst.contrib.data.transforms import normalize, to_tensor
 from catalyst.contrib.utils.cv.tensor import _IMAGENET_MEAN, _IMAGENET_STD
 
 

catalyst/contrib/utils/plotly.py

@@ -5,7 +5,7 @@
 import plotly.graph_objs as go
 from plotly.offline import init_notebook_mode, iplot
 
-from .tools.tensorboard import SummaryItem, SummaryReader
+from catalyst.contrib.tools.tensorboard import SummaryItem, SummaryReader
 
 
 def _get_tensorboard_scalars(

catalyst/core/callbacks/logging.py

@@ -5,7 +5,7 @@
 
 from tqdm import tqdm
 
-from catalyst.contrib.utils.tools.tensorboard import SummaryWriter
+from catalyst.contrib.tools.tensorboard import SummaryWriter
 from catalyst.core import Callback, CallbackNode, CallbackOrder, State, utils
 
 from . import formatters

catalyst/core/callbacks/metrics.py

@@ -6,7 +6,7 @@
 import torch
 
 from catalyst.core import Callback, CallbackNode, CallbackOrder, State, utils
-from catalyst.utils import meters
+from catalyst.tools import meters
 
 logger = logging.getLogger(__name__)
 

catalyst/core/state.py

@@ -439,6 +439,21 @@ def need_backward_pass(self):
         )
         return self.is_train_loader
 
+    @property
+    def loader_step(self):
+        """Alias for `state.loader_batch_step`.
+
+        .. warning::
+            Deprecated, saved for backward compatibility.
+            Please use `state.loader_batch_step` instead.
+        """
+        warnings.warn(
+            "`loader_step` was deprecated, "
+            "please use `loader_batch_step` instead",
+            DeprecationWarning,
+        )
+        return self.loader_batch_step
+
     def get_attr(self, key: str, inner_key: str = None) -> Any:
         """
         Alias for python `getattr` method. Useful for Callbacks preparation

catalyst/data/reader.py

@@ -171,9 +171,25 @@ def __call__(self, element):
         return result
 
 
-__all__ = [
-    "ReaderSpec",
-    "ScalarReader",
-    "LambdaReader",
-    "ReaderCompose",
-]
+try:
+    # @TODO: remove hotfix
+    from catalyst.contrib.data.cv.reader import (  # noqa: F401
+        ImageReader,
+        MaskReader,
+    )
+
+    __all__ = [
+        "ReaderSpec",
+        "ScalarReader",
+        "LambdaReader",
+        "ReaderCompose",
+        "ImageReader",
+        "MaskReader",
+    ]
+except ImportError:
+    __all__ = [
+        "ReaderSpec",
+        "ScalarReader",
+        "LambdaReader",
+        "ReaderCompose",
+    ]

catalyst/data/scripts/project_embeddings.py

@@ -8,7 +8,7 @@
 
 import torch
 
-from catalyst.contrib.utils.tools.tensorboard import SummaryWriter
+from catalyst.contrib.tools.tensorboard import SummaryWriter
 
 
 def build_args(parser):

catalyst/dl/callbacks/confusion_matrix.py

@@ -7,7 +7,7 @@
 import torch.distributed
 
 from catalyst.dl import Callback, CallbackNode, CallbackOrder, State, utils
-from catalyst.utils import meters
+from catalyst.tools import meters
 
 
 class ConfusionMatrixCallback(Callback):

catalyst/dl/callbacks/metrics/auc.py

@@ -1,7 +1,7 @@
 from typing import List
 
 from catalyst.dl.callbacks import MeterMetricsCallback
-from catalyst.utils import meters
+from catalyst.tools import meters
 
 
 class AUCCallback(MeterMetricsCallback):

catalyst/dl/callbacks/metrics/ppv_tpr_f1.py

@@ -1,7 +1,7 @@
 from typing import List
 
 from catalyst.dl.callbacks import MeterMetricsCallback
-from catalyst.utils import meters
+from catalyst.tools import meters
 
 
 class PrecisionRecallF1ScoreCallback(MeterMetricsCallback):

catalyst/utils/meters/mapmeter.py → catalyst/tools/meters/mapmeter.py

@@ -11,7 +11,7 @@
 class mAPMeter(meter.Meter):
     """
     This meter is a wrapper for
-    :py:class:`catalyst.utils.meters.apmeter.APMeter`.
+    :py:class:`catalyst.tools.meters.apmeter.APMeter`.
     The mAPMeter is designed to operate on `NxK` Tensors `output` and
     `target`, and optionally a `Nx1` Tensor weight where: