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)

      Python language logo
      your recipe card header background
      Normalization Layer

      Pytorch Public Recipes

      Shortcut: pytorch.layer.norm

      0 Comments

        Add Comment

        Log in to add a comment

        Codiga - All rights reserved 2022.