I get the error described above when attempting to perform batch norm on my network
The isolated code for the section that fails to run is
            print(layer_f)
            print(layer_b)
            x = self.af(layer_f(x))
            print(x.shape)
            x = layer_b(x)

The print out for the objects are
Linear(in_features=84, out_features=1024, bias=True)
BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
torch.Size([11, 32, 1024])
From what I understand I am passing my 11,32,84 tensor into the linear layer to get a 11,32,1024 tensor then pushing that tensor through to a batch norm layer of size 1024. I do not understand what has gone wrong here?
The input dimensions are [Batch,channel,element] and the number of channels changes for each input.