If the batchnorm layer is next to a con2d layer(out_channel is 64). So the batchnorm is nn.BatchNorm2d(num_features=64).
If the previous layer’s 10th filter was pruned(The output feature maps’ number cut 1).
Now the the batchnorm should be modified to nn.BatchNorm2d(num_features=63).
The weight, bias and running_mean in batchnorm layer are useful. How could I keep these parameters in new batchnorm layer? new_param[0:10] = old_param[0:10]; new_param[10:] = old_param[11:] ,like this.
Thank you!