Hello!
This is a simple but general problem. Recently I was training a deep learning model using Pytorch, but it seems that no matter how I modified the layer number, channels or layer output size, the training loss stop improving after  hundreds of iterations. Changing the optimizing algorithm did not help much. I wonder is there an automatic way which can help me analyze which layer is the bottleneck that affects the decrease of training loss or model parameter updating?
Thanks for your help!