I have taken the pretrained model of MoviNet, I have changed the last layer.

This is last parameters of pretrained model that I have taken;

```
classifier.0.conv_1.conv2d.weight  :  torch.Size([2048, 640, 1, 1])
classifier.0.conv_1.conv2d.bias  :  torch.Size([2048])
classifier.3.conv_1.conv2d.weight  :  torch.Size([600, 2048, 1, 1])
classifier.3.conv_1.conv2d.bias  :  torch.Size([600])

```

The following are the parameters that I have changed at the last layer;

```
clfr.0.multi_head.0.head2.0.conv_1.conv2d.weight  :  torch.Size([2048, 640, 1, 1])
clfr.0.multi_head.0.head2.0.conv_1.conv2d.bias  :  torch.Size([2048])
clfr.0.multi_head.0.head1.weight  :  torch.Size([600, 2048, 1, 1])
clfr.0.multi_head.0.head1.bias  :  torch.Size([600])

```

I want to train only classifier (clfr) based on previous layer weights, and freeze all previous laers in pytorch, can anyone one tell me how canI do this?