Feat: Frame-level Extraction and PyTorch API Updates#41
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TioSisai wants to merge 2 commits intofschmid56:mainfrom
Open
Feat: Frame-level Extraction and PyTorch API Updates#41TioSisai wants to merge 2 commits intofschmid56:mainfrom
TioSisai wants to merge 2 commits intofschmid56:mainfrom
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- Replace closely deprecated ConvNormActivation with Conv2dNormActivation - Update torch.stft to use return_complex=True for complex tensor handling and torch.square(torch.abs(x)) for power magnitude computation from complex-valued spectrogram - Replace torch.cuda.amp.autocast with torch.amp.autocast for better device compatibility These changes ensure compatibility with newer PyTorch versions while maintaining backward compatibility and fixing deprecation warnings.
…odels - Add 'frame' parameter to forward methods in MN and DyMN classes - Modify _clf_forward and _forward_impl methods to support frame-level feature extraction - Update adaptive pooling logic to preserve temporal dimension when frame=True - Maintain backward compatibility with existing clip-level feature extraction - Enable frame-wise embeddings output alongside classification results This enhancement allows models to extract features at frame level (preserving temporal dimension) in addition to the existing clip-level aggregation, enabling more fine-grained temporal analysis.
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This pull request introduces two main sets of changes: a new feature for frame-level embedding extraction and several updates to ensure compatibility with modern PyTorch versions by replacing deprecated APIs.
New Features:
Frame-level Feature Extraction:
Fixes & Maintenance:
PyTorch API Modernization: