Add model resnext101_32x8d_wsl (#834)

* adds model resnext101_32x8d_wsl

* addresses PR comments

brainscore_vision/models/resnext101_32x8d_wsl/__init__.py

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+from brainscore_vision import model_registry
+from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
+from .model import get_model, get_layers
+
+model_registry['resnext101_32x8d_wsl'] = lambda: ModelCommitment(identifier='resnext101_32x8d_wsl',
+                                                               activations_model=get_model('resnext101_32x8d_wsl'),
+                                                               layers=get_layers('resnext101_32x8d_wsl'))

brainscore_vision/models/resnext101_32x8d_wsl/model.py

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+import functools
+from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
+from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
+from brainscore_vision.model_helpers.check_submission import check_models
+import torch.hub
+import ssl
+
+
+ssl._create_default_https_context = ssl._create_unverified_context
+
+
+def get_model(name):
+    assert name == 'resnext101_32x8d_wsl'
+    model_identifier = "resnext101_32x8d_wsl"
+    model = torch.hub.load('facebookresearch/WSL-Images', model_identifier)
+    preprocessing = functools.partial(load_preprocess_images, image_size=224)
+    batch_size = {8: 32, 16: 16, 32: 8, 48: 4}
+    wrapper = PytorchWrapper(identifier=model_identifier, model=model, preprocessing=preprocessing,
+                             batch_size=batch_size[8])
+    wrapper.image_size = 224
+    return wrapper
+
+
+def get_layers(name):
+    assert name == 'resnext101_32x8d_wsl'
+    return (['conv1'] +
+            # note that while relu is used multiple times, by default the last one will overwrite all previous ones
+            [f"layer{block + 1}.{unit}.relu"
+             for block, block_units in enumerate([3, 4, 23, 3]) for unit in range(block_units)] +
+            ['avgpool'])
+
+
+def get_bibtex(model_identifier):
+    """
+    A method returning the bibtex reference of the requested model as a string.
+    """
+    return """@inproceedings{mahajan2018exploring,
+              title={Exploring the limits of weakly supervised pretraining},
+              author={Mahajan, Dhruv and Girshick, Ross and Ramanathan, Vignesh and He, Kaiming and Paluri, Manohar and Li, Yixuan and Bharambe, Ashwin and Van Der Maaten, Laurens},
+              booktitle={Proceedings of the European conference on computer vision (ECCV)},
+              pages={181--196},
+              year={2018}
+            }"""
+
+
+if __name__ == '__main__':
+    check_models.check_base_models(__name__)

brainscore_vision/models/resnext101_32x8d_wsl/requirements.txt

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+torchvision
+torch
+ssl
+functools

brainscore_vision/models/resnext101_32x8d_wsl/test.py

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+import pytest
+import brainscore_vision
+
+
+@pytest.mark.travis_slow
+def test_has_identifier():
+    model = brainscore_vision.load_model('resnext101_32x8d_wsl')
+    assert model.identifier == 'resnext101_32x8d_wsl'