Hy @IamSparky, I guess the error occurs here in your model.
(conv1): conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (gn1): GroupNorm(32, 64, eps=1e-05, affine=True)
  (layer1): Sequential(
    (0): bottleNeck(
      (conv1): conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), dilation=(False, False))
      (gn1): GroupNorm(32, 64, eps=1e-05, affine=True)
      (conv2): conv2d(64, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), dilation=(False, False))
      (gn2): GroupNorm(32, 192, eps=1e-05, affine=True) # Here output channel is 192
      (dim_change): Sequential(
        (0): Conv2d(64, 192, kernel_size=(1, 1), stride=(1, 1))# here input channel is 64
        (1): GroupNorm(32, 192, eps=1e-05, affine=True)#Here Also
      )