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Add dropout to DeepMIL and fix feature extractor setup #653
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harshita-s
reviewed
Feb 4, 2022
harshita-s
previously approved these changes
Feb 4, 2022
maxilse
approved these changes
Feb 7, 2022
harshita-s
reviewed
Feb 7, 2022
| feature_extractor = nn.Sequential(*layers) | ||
| with no_grad(): | ||
| feature_shape = feature_extractor(rand(1, *input_dim)).shape | ||
| num_features = int(prod(as_tensor(feature_shape)).item()) | ||
| # fix weights, no fine-tuning | ||
| for param in feature_extractor.parameters(): | ||
| param.requires_grad = False |
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This should not be set False for fine-tuning, right?
harshita-s
approved these changes
Feb 7, 2022
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