Add model AT_efficientnet-b4

brainscore_vision/models/AT_efficientnet_b4/__init__.py

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+from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
+from brainscore_vision import model_registry
+from .model import get_layers,get_model
+
+
+model_registry['AT_efficientnet-b4'] = \
+    lambda: ModelCommitment(identifier='AT_efficientnet-b4', activations_model=get_model('AT_efficientnet-b4'), layers=get_layers('AT_efficientnet-b4'))

brainscore_vision/models/AT_efficientnet_b4/model.py

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+import functools
+from efficientnet_pytorch import EfficientNet
+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
+
+
+def get_model(name):
+    assert name == 'AT_efficientnet-b4'
+    model = EfficientNet.from_pretrained("efficientnet-b4", advprop=True)
+    model.set_swish(memory_efficient=False)
+    preprocessing = functools.partial(load_preprocess_images, image_size=224, normalize_mean=(0.5, 0.5, 0.5), normalize_std=(0.5, 0.5, 0.5))
+    wrapper = PytorchWrapper(identifier=name, model=model, preprocessing=preprocessing)
+    from types import MethodType
+    def _output_layer(self):
+        return self._model._fc
+
+    wrapper._output_layer = MethodType(_output_layer, wrapper)
+    wrapper.image_size = 224
+    return wrapper
+
+
+def get_layers(name):
+    assert name == 'AT_efficientnet-b4'
+    return [
+        '_blocks.0',
+        '_blocks.1',
+        '_blocks.2',
+        '_blocks.3',
+        '_blocks.4',
+        '_blocks.5',
+        '_blocks.6',
+        '_blocks.7',
+        '_blocks.8',
+        '_blocks.9',
+        '_blocks.10',
+        '_blocks.11',
+        '_blocks.12',
+        '_blocks.13',
+        '_blocks.14',
+        '_blocks.15',
+        '_blocks.16',
+        '_blocks.17',
+        '_blocks.18',
+        '_blocks.19',
+        '_blocks.20',
+        '_blocks.21',
+        '_blocks.22',
+        '_blocks.23',
+        '_blocks.24',
+        '_blocks.25',
+        '_blocks.26',
+        '_blocks.27',
+        '_blocks.28',
+        '_blocks.29',
+        '_blocks.30',
+        '_blocks.31',
+    ]
+
+def get_bibtex(model_identifier):
+    """
+    A method returning the bibtex reference of the requested model as a string.
+    """
+    return ''
+
+if __name__ == '__main__':
+    check_models.check_base_models(__name__)

brainscore_vision/models/AT_efficientnet_b4/region_layer_map/AT_efficientnet-b4.json

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+{
+    "IT": "_blocks.22",
+    "V4": "_blocks.10",
+    "V2": "_blocks.10",
+    "V1": "_blocks.10"
+}

brainscore_vision/models/AT_efficientnet_b4/requirements.txt

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+efficientnet_pytorch

brainscore_vision/models/AT_efficientnet_b4/test.py

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+import brainscore_vision
+import pytest
+
+
+@pytest.mark.travis_slow
+def test_has_identifier():
+    model = brainscore_vision.load_model('AT_efficientnet-b4')
+    assert model.identifier == 'AT_efficientnet-b4'