How can we calculate receptive field of a network includes transposed convolutional layer?
A network I designed includes transposed convolutional layer.
(ConvTranspose2d in pytorch)

I want to get receptive field size of my network.

Does the concept of receptive field also hold on with transposed convolutional layer?

If yes, then how can I get it?

You can use the library pytorch-receptive-field to automatically compute all layers' receptive fields.
