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PyTorchVideo Documentation — PyTorchVideo documentation
To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s ...
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Overview — PyTorchVideo documentation
You can construct a model with random weights by calling its constructor: import pytorchvideo.models as models resnet = models.create_resnet() acoustic_resnet = models.create_acoustic_resnet() slowfa...
- Overview: module code — PyTorchVideo documentation
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Overview — PyTorchVideo documentation
You can construct a layer with random weights by calling its constructor: import pytorchvideo.layers as layers nonlocal = layers.create_nonlocal(dim_in=256, dim_inner=128) swish = layers.Swish() conv...
- API Documentation — PyTorchVideo documentation
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Overview — PyTorchVideo documentation
torch.utils.data.DataLoader, which can load multiple samples in parallel using torch.multiprocessing workers. For example: dataset = pytorchvideo.data.Kinetics( data_path="path/to/kinetics_ro...