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    Normalization Layer

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    lucycodes42

    Pytorch Public Recipes

    Library: pytorch

    Shortcut: pytorch.layer.norm

    norm = nn.BatchNorm1d(num_features\, eps=1e-5\, momentum=0.1\, affine=True\, track_running_stats=True),BatchNorm2d(num_features\, eps=1e-5\, momentum=0.1\, affine=True\, track_running_stats=True),BatchNorm3d(num_features\, eps=1e-5\, momentum=0.1\, affine=True\, track_running_stats=True),GroupNorm(num_groups\, num_channels\, eps=1e-5\, affine=True),SyncBatchNorm(num_features\, eps=1e-05\, momentum=0.1\, affine=True),InstanceNorm1d(num_features\, eps=1e-5\, momentum=0.1\, affine=False\, track_running_stats=False),InstanceNorm2d(num_features\, eps=1e-5\, momentum=0.1\, affine=False\, track_running_stats=False),InstanceNorm3d(num_features\, eps=1e-5\, momentum=0.1\, affine=False\, track_running_stats=False),LayerNorm(normalized_shape\, eps=1e-5\, elementwise_affine=True),LocalResponseNorm(size\, alpha=1e-4\, beta=0.75\, k=1)
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