Actually, there’s a difference between keras model.summary() and print(model) in pytorch. print(model in pytorch only print the layers defined in the init function of the class but not the model architecture defined in forward function. Keras model.summary() actually prints the model architecture with input and output shape along with trainable and non trainable parameters.
I haven’t found anything like that in PyTorch. I end up writing bunch of print statements in forward function to determine the input and output shape.
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