I’m getting started with PyTorch and following the 60 minute Blitz tutorial on neural networks 6.
When defining a new Conv2d layer, one passes (input_channels, output_channels, kernel_size). But when accessing the layer’s parameters by calling .parameters(), the result is [output_channels, input_channels, kernel_dimensions]. What is the rationale behind putting the number of output channels first in the latter case? I found this to be very confusing.