I want to print the output of each of the layers in AWD_LSTM, the encoder+classifier architecture. I.e. When I pass a text as input, I want to see the tensors after individual layers. And play with them, like you do with BERT to extract word embeddings. How do I get hold of individual layers in fastai v1?
You should register/use a pytorch hook similar to:
-
Grad-Cam:
with hook_output(m[0]) as hook_a:
-
CUda-cnn-hooks
with Hooks(model, append_stats) as hooks: run.fit(1, learn)
1 Like