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brain-score.org submission (user:121) | (public:False) #1253

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brain-score.org submission (user:121) | (public:False) #1253

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6 changes: 3 additions & 3 deletions brainscore_vision/models/resnext101_32x48d_wsl/__init__.py
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Expand Up @@ -2,6 +2,6 @@
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers

model_registry['resnext101_32x48d_wsl'] = lambda: ModelCommitment(identifier='resnext101_32x48d_wsl',
activations_model=get_model('resnext101_32x48d_wsl'),
layers=get_layers('resnext101_32x48d_wsl'))
model_registry['resnext101_32x48d_wsl_TEST'] = lambda: ModelCommitment(identifier='resnext101_32x48d_wsl_TEST',
activations_model=get_model('resnext101_32x48d_wsl_TEST'),
layers=get_layers('resnext101_32x48d_wsl_TEST'))
6 changes: 3 additions & 3 deletions brainscore_vision/models/resnext101_32x48d_wsl/model.py
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Expand Up @@ -10,8 +10,8 @@


def get_model(name):
assert name == 'resnext101_32x48d_wsl'
model_identifier = "resnext101_32x48d_wsl"
assert name == 'resnext101_32x48d_wsl_TEST'
model_identifier = "resnext101_32x48d_wsl_TEST"
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}
Expand All @@ -22,7 +22,7 @@ def get_model(name):


def get_layers(name):
assert name == 'resnext101_32x48d_wsl'
assert name == 'resnext101_32x48d_wsl_TEST'
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"
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1 change: 0 additions & 1 deletion brainscore_vision/models/resnext101_32x48d_wsl/requirements.txt
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@@ -1,3 +1,2 @@
torchvision
torch
torch
4 changes: 2 additions & 2 deletions brainscore_vision/models/resnext101_32x48d_wsl/test.py
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Expand Up @@ -4,5 +4,5 @@

@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('resnext101_32x48d_wsl')
assert model.identifier == 'resnext101_32x48d_wsl'
model = brainscore_vision.load_model('resnext101_32x48d_wsl_TEST')
assert model.identifier == 'resnext101_32x48d_wsl_TEST'