Missed norm.py

timm/models/layers/norm.py

@@ -0,0 +1,14 @@
+""" Normalization layers and wrappers
+"""
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+
+class GroupNorm(nn.GroupNorm):
+    def __init__(self, num_channels, num_groups, eps=1e-5, affine=True):
+        # NOTE num_channels is swapped to first arg for consistency in swapping norm layers with BN
+        super().__init__(num_groups, num_channels, eps=eps, affine=affine)
+
+    def forward(self, x):
+        return F.group_norm(x, self.num_groups, self.weight, self.bias, self.eps)