skip hanging tests & update imports (#258)

* fix imports

* timeout

* flake8

* skip

* skip

* skip

* skip

* Apply suggestions from code review

.github/workflows/ci_test-full.yml

@@ -27,7 +27,7 @@ jobs:
             os: windows-2019
 
     # Timeout: https://stackoverflow.com/a/59076067/4521646
-    timeout-minutes: 35
+    timeout-minutes: 45
 
     steps:
     - uses: actions/checkout@v2

pl_bolts/callbacks/variational.py

@@ -5,7 +5,7 @@
 
 try:
     import torchvision
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
 

pl_bolts/callbacks/vision/image_generation.py

@@ -5,7 +5,7 @@
 
 try:
     import torchvision
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
 

pl_bolts/datamodules/__init__.py

@@ -25,5 +25,5 @@
 
     from pl_bolts.datamodules.kitti_dataset import KittiDataset
     from pl_bolts.datamodules.kitti_datamodule import KittiDataModule
-except ImportError:
+except ModuleNotFoundError:
     pass

pl_bolts/datamodules/binary_mnist_datamodule.py

@@ -8,7 +8,7 @@
     from torchvision import transforms as transform_lib
     from torchvision.datasets import MNIST
     from pl_bolts.datamodules.mnist_dataset import BinaryMNIST
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -65,7 +65,9 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError('You want to use MNIST dataset loaded from `torchvision` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use MNIST dataset loaded from `torchvision` which is not installed yet.'
+            )
 
         self.dims = (1, 28, 28)
         self.data_dir = data_dir

pl_bolts/datamodules/cifar10_datamodule.py

@@ -13,7 +13,7 @@
     from torchvision import transforms as transform_lib
     from torchvision.datasets import CIFAR10
 
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -84,7 +84,9 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError('You want to use CIFAR10 dataset loaded from `torchvision` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use CIFAR10 dataset loaded from `torchvision` which is not installed yet.'
+            )
 
         self.dims = (3, 32, 32)
         self.DATASET = CIFAR10

pl_bolts/datamodules/cifar10_dataset.py

@@ -9,7 +9,7 @@
 
 try:
     from PIL import Image
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `Pillow` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install Pillow`.')
     _PIL_AVAILABLE = False

pl_bolts/datamodules/cityscapes_datamodule.py

@@ -7,7 +7,7 @@
 try:
     from torchvision import transforms as transform_lib
     from torchvision.datasets import Cityscapes
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -77,7 +77,7 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError(
+            raise ModuleNotFoundError(  # pragma: no-cover
                 'You want to use CityScapes dataset loaded from `torchvision` which is not installed yet.'
             )
 

pl_bolts/datamodules/fashion_mnist_datamodule.py

@@ -7,7 +7,7 @@
 try:
     from torchvision import transforms as transform_lib
     from torchvision.datasets import FashionMNIST
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -63,7 +63,7 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError(
+            raise ModuleNotFoundError(  # pragma: no-cover
                 'You want to use fashion MNIST dataset loaded from `torchvision` which is not installed yet.'
             )
 

pl_bolts/datamodules/imagenet_datamodule.py

@@ -9,7 +9,7 @@
 try:
     from torchvision import transforms as transform_lib
     from pl_bolts.datamodules.imagenet_dataset import UnlabeledImagenet
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -72,7 +72,9 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError('You want to use ImageNet dataset loaded from `torchvision` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use ImageNet dataset loaded from `torchvision` which is not installed yet.'
+            )
 
         self.image_size = image_size
         self.dims = (3, self.image_size, self.image_size)

pl_bolts/datamodules/imagenet_dataset.py

@@ -13,16 +13,17 @@
 
 try:
     from sklearn.utils import shuffle
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `sklearn` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install sklearn`.')
 
 try:
     from torchvision.datasets import ImageNet
     from torchvision.datasets.imagenet import load_meta_file
-except ImportError:
-    raise ImportError('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
-                      ' install it with `pip install torchvision`.')
+except ModuleNotFoundError:
+    raise ModuleNotFoundError(  # pragma: no-cover
+        'You want to use `torchvision` which is not installed yet, install it with `pip install torchvision`.'
+    )
 
 
 class UnlabeledImagenet(ImageNet):

pl_bolts/datamodules/mnist_datamodule.py

@@ -7,7 +7,7 @@
 try:
     from torchvision import transforms as transform_lib
     from torchvision.datasets import MNIST
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -65,7 +65,9 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError('You want to use MNIST dataset loaded from `torchvision` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use MNIST dataset loaded from `torchvision` which is not installed yet.'
+            )
 
         self.dims = (1, 28, 28)
         self.data_dir = data_dir

pl_bolts/datamodules/mnist_dataset.py

@@ -3,13 +3,14 @@
 try:
     from torchvision import transforms as transform_lib
     from torchvision.datasets import MNIST
-except ImportError:
-    raise ImportError('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
-                      ' install it with `pip install torchvision`.')
+except ModuleNotFoundError:
+    raise ModuleNotFoundError(  # pragma: no-cover
+        'You want to use `torchvision` which is not installed yet, install it with `pip install torchvision`.'
+    )
 
 try:
     from PIL import Image
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `Pillow` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install Pillow`.')
     _PIL_AVAILABLE = False

pl_bolts/datamodules/sklearn_datamodule.py

@@ -9,7 +9,7 @@
 
 try:
     from sklearn.utils import shuffle as sk_shuffle
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `sklearn` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install sklearn`.')
     _SKLEARN_AVAILABLE = False
@@ -162,7 +162,9 @@ def __init__(
         if shuffle and _SKLEARN_AVAILABLE:
             X, y = sk_shuffle(X, y, random_state=random_state)
         elif shuffle and not _SKLEARN_AVAILABLE:
-            raise ImportError('You want to use shuffle function from `scikit-learn` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use shuffle function from `scikit-learn` which is not installed yet.'
+            )
 
         val_split = 0 if x_val is not None or y_val is not None else val_split
         test_split = 0 if x_test is not None or y_test is not None else test_split

pl_bolts/datamodules/ssl_amdim_datasets.py

@@ -6,13 +6,13 @@
 
 try:
     from sklearn.utils import shuffle
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `sklearn` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install sklearn`.')
 
 try:
     from torchvision.datasets import CIFAR10
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
 

pl_bolts/datamodules/ssl_imagenet_datamodule.py

@@ -10,7 +10,7 @@
 try:
     from torchvision import transforms as transform_lib
 
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -33,7 +33,9 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError('You want to use ImageNet dataset loaded from `torchvision` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use ImageNet dataset loaded from `torchvision` which is not installed yet.'
+            )
 
         self.data_dir = data_dir
         self.num_workers = num_workers

pl_bolts/datamodules/stl10_datamodule.py

@@ -11,7 +11,7 @@
 try:
     from torchvision import transforms as transform_lib
     from torchvision.datasets import STL10
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -75,7 +75,9 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError('You want to use STL10 dataset loaded from `torchvision` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use STL10 dataset loaded from `torchvision` which is not installed yet.'
+            )
 
         self.dims = (3, 96, 96)
         self.data_dir = data_dir if data_dir is not None else os.getcwd()

pl_bolts/datamodules/vocdetection_datamodule.py

@@ -8,7 +8,7 @@
 try:
     from torchvision.datasets import VOCDetection
 
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
     _TORCHVISION_AVAILABLE = False
@@ -120,7 +120,9 @@ def __init__(
         super().__init__(*args, **kwargs)
 
         if not _TORCHVISION_AVAILABLE:
-            raise ImportError('You want to use VOC dataset loaded from `torchvision` which is not installed yet.')
+            raise ModuleNotFoundError(  # pragma: no-cover
+                'You want to use VOC dataset loaded from `torchvision` which is not installed yet.'
+            )
 
         self.year = year
         self.data_dir = data_dir

pl_bolts/models/detection/__init__.py

@@ -2,7 +2,7 @@
 
 try:
     from pl_bolts.models.detection.faster_rcnn import FasterRCNN
-except ImportError:  # pragma: no-cover
+except ModuleNotFoundError:  # pragma: no-cover
     pass  # pragma: no-cover
 else:
     __all__.append('FasterRCNN')

pl_bolts/models/detection/faster_rcnn.py

@@ -7,7 +7,7 @@
 try:
     from torchvision.models.detection import faster_rcnn, fasterrcnn_resnet50_fpn
     from torchvision.ops import box_iou
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
 

pl_bolts/models/mnist_module.py

@@ -10,7 +10,7 @@
 try:
     from torchvision import transforms
     from torchvision.datasets import MNIST
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')
 

pl_bolts/models/regression/linear_regression.py

@@ -126,9 +126,10 @@ def cli_main():
     # create dataset
     try:
         from sklearn.datasets import load_boston
-    except ImportError:
-        raise ImportError('You want to use `sklearn` which is not installed yet,'  # pragma: no-cover
-                          ' install it with `pip install sklearn`.')
+    except ModuleNotFoundError:
+        raise ModuleNotFoundError(  # pragma: no-cover
+            'You want to use `sklearn` which is not installed yet, install it with `pip install sklearn`.'
+        )
 
     X, y = load_boston(return_X_y=True)  # these are numpy arrays
     loaders = SklearnDataModule(X, y)

pl_bolts/models/regression/logistic_regression.py

@@ -132,9 +132,10 @@ def cli_main():
     # Example: Iris dataset in Sklearn (4 features, 3 class labels)
     try:
         from sklearn.datasets import load_iris
-    except ImportError:
-        raise ImportError('You want to use `sklearn` which is not installed yet,'  # pragma: no-cover
-                          ' install it with `pip install sklearn`.')
+    except ModuleNotFoundError:
+        raise ModuleNotFoundError(  # pragma: no-cover
+            'You want to use `sklearn` which is not installed yet, install it with `pip install sklearn`.'
+        )
 
     X, y = load_iris(return_X_y=True)
     loaders = SklearnDataModule(X, y)

pl_bolts/models/self_supervised/amdim/__init__.py

@@ -9,5 +9,5 @@
         AMDIMTrainTransformsImageNet128,
         AMDIMEvalTransformsImageNet128,
     )
-except ImportError:
+except ModuleNotFoundError:
     pass

pl_bolts/models/self_supervised/amdim/amdim_module.py

@@ -9,7 +9,7 @@
 
 try:
     from pl_bolts.models.self_supervised.amdim.datasets import AMDIMPretraining
-except ImportError:
+except ModuleNotFoundError:
     pass
 from pl_bolts.losses.self_supervised_learning import FeatureMapContrastiveTask
 from pl_bolts.models.self_supervised.amdim.networks import AMDIMEncoder

pl_bolts/models/self_supervised/amdim/datasets.py

@@ -7,7 +7,7 @@
     from pl_bolts.datamodules.imagenet_dataset import UnlabeledImagenet
     from pl_bolts.datamodules.ssl_amdim_datasets import CIFAR10Mixed
     from pl_bolts.models.self_supervised.amdim import transforms as amdim_transforms
-except ImportError:
+except ModuleNotFoundError:
     warn('You want to use `torchvision` which is not installed yet,'  # pragma: no-cover
          ' install it with `pip install torchvision`.')