o ϯi @sddlmZmZddlmZddlmZddlmZdZ e de de de d d Z dd e de dee dedej f ddZ dd e de fddZ dd e de fddZ dd e de fddZ dd e de fddZdS))AnyOptionalN) create_x3d)load_state_dict_from_urlz>https://dl.fbaipublicfiles.com/pytorchvideo/model_zoo/kineticsz /X3D_XS.pythz /X3D_S.pythz /X3D_M.pythz /X3D_L.pyth)x3d_xsx3d_sx3d_mx3d_lFT pretrainedprogresscheckpoint_pathkwargsreturncKs>tdi|}|r|durt||dd}|d}|||S)Ncpu)r map_location model_state)rrload_state_dict)r r r r model checkpoint state_dictrrO/home/ubuntu/.local/lib/python3.10/site-packages/pytorchvideo/models/hub/x3d.py_x3ds  rcKtd||tdddd|S)a  X3D-XS model architecture [1] trained on the Kinetics dataset. Model with pretrained weights has top1 accuracy of 69.12. [1] Christoph Feichtenhofer, "X3D: Expanding Architectures for Efficient Video Recognition." https://arxiv.org/abs/2004.04730 Args: pretrained (bool): If True, returns a model pre-trained on the Kinetics dataset progress (bool): If True, displays a progress bar of the download to stderr kwargs: use these to modify any of the other model settings. All the options are defined in pytorchvideo/models/x3d.py NOTE: to use the pretrained model, do not modify the model configuration via the kwargs. Only modify settings via kwargs to initialize a new model without pretrained weights. rr r r input_clip_lengthinput_crop_sizeNrrcheckpoint_pathsr r r rrrr$rcKr)a  X3D-XS model architecture [1] trained on the Kinetics dataset. Model with pretrained weights has top1 accuracy of 73.33. [1] Christoph Feichtenhofer, "X3D: Expanding Architectures for Efficient Video Recognition." https://arxiv.org/abs/2004.04730 Args: pretrained (bool): If True, returns a model pre-trained on the Kinetics dataset progress (bool): If True, displays a progress bar of the download to stderr kwargs: use these to modify any of the other model settings. All the options are defined in pytorchvideo/models/x3d.py NOTE: to use the pretrained model, do not modify the model configuration via the kwargs. Only modify settings via kwargs to initialize a new model without pretrained weights. r rrNrrr!rrrrDr"rcKr)a  X3D-XS model architecture [1] trained on the Kinetics dataset. Model with pretrained weights has top1 accuracy of 75.94. [1] Christoph Feichtenhofer, "X3D: Expanding Architectures for Efficient Video Recognition." https://arxiv.org/abs/2004.04730 Args: pretrained (bool): If True, returns a model pre-trained on the Kinetics dataset progress (bool): If True, displays a progress bar of the download to stderr kwargs: use these to modify any of the other model settings. All the options are defined in pytorchvideo/models/x3d.py NOTE: to use the pretrained model, do not modify the model configuration via the kwargs. Only modify settings via kwargs to initialize a new model without pretrained weights. rrNrrr!rrrrdr"rc Ks td||tddddd|S)a  X3D-XS model architecture [1] trained on the Kinetics dataset. Model with pretrained weights has top1 accuracy of 77.44. [1] Christoph Feichtenhofer, "X3D: Expanding Architectures for Efficient Video Recognition." https://arxiv.org/abs/2004.04730 Args: pretrained (bool): If True, returns a model pre-trained on the Kinetics dataset progress (bool): If True, displays a progress bar of the download to stderr kwargs: use these to modify any of the other model settings. All the options are defined in pytorchvideo/models/x3d.py NOTE: to use the pretrained model, do not modify the model configuration via the kwargs. Only modify settings via kwargs to initialize a new model without pretrained weights. r r$i8g@)r r r rr depth_factorNrrr!rrrr sr )FTN)FT)typingrrtorch.nnnnpytorchvideo.models.x3dr torch.hubrroot_dirr boolstrModulerrrrr rrrrsh      ! ! !