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Fix (tests): skip effnetb0 with torch 2.1
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Giuseppe5 committed Nov 26, 2023
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5 changes: 5 additions & 0 deletions tests/brevitas_end_to_end/test_torchvision_models.py
Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,11 @@ def torchvision_model(model_name, quantize_fn):
if torch_version < version.parse('1.11.0') and model_name == 'vit_b_32':
return None

# Due to a regression in torchvision, we cannot load pretrained weights for effnet_b0
# https://github.com/pytorch/vision/issues/7744
if torch_version == version.parse('2.1.0') and model_name == 'efficientnet_b0':
return None

# Deeplab and fcn are in a different module, and they have a dict as output which is not suited for torchscript
if model_name in ('deeplabv3_resnet50', 'fcn_resnet50'):
model_fn = getattr(modelzoo.segmentation, model_name)
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