Enhance Detector class with feature extraction and accuracy#57
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krataratha wants to merge 1 commit into
Open
Enhance Detector class with feature extraction and accuracy#57krataratha wants to merge 1 commit into
krataratha wants to merge 1 commit into
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Added feature to extract raw embedding features and calculate batch accuracy during training.
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Pull request overview
This PR enhances the Detector model API to optionally return EfficientNet feature maps (via return_features) and attempts to return batch accuracy from training_step during SAM-based training.
Changes:
- Added
return_featuresflag toDetector.forward()to returnnet.extract_features(x)instead of logits. - Refactored SAM step selection in
training_step()using astep_fnvariable. - Updated
training_step()to compute and return batch accuracy (but currently changes the return type).
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| # Feature: Now calculates and returns batch accuracy alongside the predictions | ||
| acc = (pred_first.argmax(dim=-1) == target).float().mean() | ||
| return pred_first, loss, acc | ||
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| return pred_first |
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Added feature to extract raw embedding features and calculate batch accuracy during training.