Hi,
So I am trying to use torch.nn.utils.prune.global_unstructured as in https://pytorch.org/docs/master/generated/torch.nn.utils.prune.global_unstructured.html 1
I did it on a simple model and that worked. model.cov2 or other layers and that works. I am trying to do it on a model that’s (nested)? I get errors as:
AttributeError: ‘CNN’ object has no attribute ‘conv1’
and other errors. I tried everything to access this deep cov1, but I couldn’t.
You can find the model code below:
class CNN(nn.Module):
def init(self):
“”“CNN Builder.”""
super(CNN, self).init()
    self.conv_layer = nn.Sequential(

        # Conv Layer block 1
        nn.Conv2d(in_channels=3, out_channels=32, kernel_size=3, padding=1),
        nn.BatchNorm2d(32),
        nn.ReLU(inplace=True),
        nn.Conv2d(in_channels=32, out_channels=64, kernel_size=3, padding=1),
        nn.ReLU(inplace=True),
        nn.MaxPool2d(kernel_size=2, stride=2),

        # Conv Layer block 2
        nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, padding=1),
        nn.BatchNorm2d(128),
        nn.ReLU(inplace=True),
        nn.Conv2d(in_channels=128, out_channels=128, kernel_size=3, padding=1),
        nn.ReLU(inplace=True),
        nn.MaxPool2d(kernel_size=2, stride=2),
        nn.Dropout2d(p=0.05),

        # Conv Layer block 3
        nn.Conv2d(in_channels=128, out_channels=256, kernel_size=3, padding=1),
        nn.BatchNorm2d(256),
        nn.ReLU(inplace=True),
        nn.Conv2d(in_channels=256, out_channels=256, kernel_size=3, padding=1),
        nn.ReLU(inplace=True),
        nn.MaxPool2d(kernel_size=2, stride=2),
    )


    self.fc_layer = nn.Sequential(
        nn.Dropout(p=0.1),
        nn.Linear(4096, 1024),
        nn.ReLU(inplace=True),
        nn.Linear(1024, 512),
        nn.ReLU(inplace=True),
        nn.Dropout(p=0.1),
        nn.Linear(512, 100)
    )


def forward(self, x):
    """Perform forward."""
    # conv layers
    x = self.conv_layer(x)
    # flatten
    x = x.view(x.size(0), -1)
    # fc layer
    x = self.fc_layer(x)
    return x

How can I apply pruning on this model?