PGG-DeepAI:

I get a 8x8 grid filters (so 64 filters of variable sizes)


Be a bit careful about the shape of the weight parameter.
The filters in nn.Conv2d are stored as [output_channels=nb_filters, input_channels, kernel_height, kernel_width].
In the default setup, each filter (number of filters is defined by out_channels) will use all input channels to calculate its activation map.
Have a look as CS231n - Convolutional Layer 46 for more information on the shape of conv layers.



 PGG-DeepAI:

I imagine that is showing “filters” of also Relu layers


No, nn.ReLU() doesn’t have any trainable parameters and thus no filters.
Note that the conv.weight parameter gives you the convolution filters, not the activations in case you are mixing these up.