Add TorchVision classification models: SqueezeNet, DenseNet, ShuffleN…#1550
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alinpahontu2912 wants to merge 1 commit intodotnet:mainfrom
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Add TorchVision classification models: SqueezeNet, DenseNet, ShuffleN…#1550alinpahontu2912 wants to merge 1 commit intodotnet:mainfrom
alinpahontu2912 wants to merge 1 commit intodotnet:mainfrom
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…etV2, EfficientNet, MNASNet Add 5 new model families (21 variants) ported from PyTorch torchvision: - SqueezeNet 1.0/1.1 - DenseNet-121/161/169/201 - ShuffleNet V2 x0.5/x1.0/x1.5/x2.0 - EfficientNet B0-B7, EfficientNet V2 S/M/L - MNASNet 0.5/0.75/1.0/1.3 All models support pre-trained weight loading via weights_file/skipfc parameters with state_dict keys matching PyTorch exactly. Tests added for all new model families. TODO: The following torchvision classification models are not yet implemented: - RegNet (Y/X variants) - ConvNeXt (Tiny, Small, Base, Large) - Vision Transformer / ViT (B-16, B-32, L-16, L-32, H-14) - Swin Transformer (T, S, B) - Swin Transformer V2 (T, S, B) - MaxViT (T) Closes dotnet#586 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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Fixes #588
Add 5 new model families (21 variants) ported from PyTorch torchvision:
All models support pre-trained weight loading via weights_file/skipfc parameters with state_dict keys matching PyTorch exactly.
Tests added for all new model families.
TODO: The following torchvision classification models are not yet implemented: