Add resnet50_v2

brainscore_vision/models/resnet50_v2/__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['resnet50_v2'] = lambda: ModelCommitment(identifier='resnet50_v2',
+                                                               activations_model=get_model(),
+                                                               layers=get_layers())

brainscore_vision/models/resnet50_v2/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
+import torchvision
+import ssl
+
+
+ssl._create_default_https_context = ssl._create_unverified_context
+
+'''
+This is a Pytorch implementation of resnet50.
+
+The model template can be found at the following URL:
+https://pytorch.org/vision/main/models/generated/torchvision.models.resnet50.html
+
+'''
+
+MODEL = torchvision.models.resnet50(weights='ResNet50_Weights.IMAGENET1K_V2')  # use V2 weights
+
+
+def get_model():
+    model_identifier = "resnet50_v2"
+    preprocessing = functools.partial(load_preprocess_images, image_size=224)
+    wrapper = PytorchWrapper(identifier=model_identifier, model=MODEL, preprocessing=preprocessing)
+    wrapper.image_size = 224
+    return wrapper
+
+
+def get_layers():
+    layer_names = []
+
+    for name, module in MODEL.named_modules():
+        layer_names.append(name)
+
+    return layer_names[2:]

brainscore_vision/models/resnet50_v2/requirements.txt

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+torch
+torchvision

brainscore_vision/models/resnet50_v2/test.py

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+import pytest
+import brainscore_vision
+
+
+@pytest.mark.travis_slow
+def test_has_identifier():
+    model = brainscore_vision.load_model('resnet50_v2')
+    assert model.identifier == 'resnet50_v2'