pt/vmz/models/r2plus1d.py [40:55]:
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        stem=R2Plus1dStem_Pool if use_pool1 else R2Plus1dStem,
        **kwargs,
    )
    # We need exact Caffe2 momentum for BatchNorm scaling
    for m in model.modules():
        if isinstance(m, nn.BatchNorm3d):
            m.eps = 1e-3
            m.momentum = 0.9

    if pretrained:
        state_dict = torch.hub.load_state_dict_from_url(
            model_urls[arch], progress=progress
        )
        model.load_state_dict(state_dict)

    return model
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pt/vmz/models/r2plus1d.py [84:99]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        stem=R2Plus1dStem_Pool if use_pool1 else R2Plus1dStem,
        **kwargs,
    )
    # We need exact Caffe2 momentum for BatchNorm scaling
    for m in model.modules():
        if isinstance(m, nn.BatchNorm3d):
            m.eps = 1e-3
            m.momentum = 0.9

    if pretrained:
        state_dict = torch.hub.load_state_dict_from_url(
            model_urls[arch], progress=progress
        )
        model.load_state_dict(state_dict)

    return model
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