mirrors/icefall
1
0
Fork 0
mirror of https://github.com/k2-fsa/icefall.git synced 2025-12-11 06:55:27 +00:00
Code Issues Packages Projects Releases Wiki Activity

Fix bug in choosing layers to drop

Browse Source
This commit is contained in:
Daniel Povey 2022-10-10 13:38:36 +08:00
parent 857b3735e7
commit f941991331
1 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
egs/librispeech/ASR/pruned_transducer_stateless7/conformer.py
View File

@ -471,16 +471,16 @@ class ConformerEncoder(nn.Module):
# with their specified probs while reaching this exact target. # with their specified probs while reaching this exact target.
num_to_drop = int(tot) + int(shared_rng.random() < (tot - int(tot))) num_to_drop = int(tot) + int(shared_rng.random() < (tot - int(tot)))
layers = list(range(num_layers)) layers = list(range(num_layers))
independent_rng.shuffle(layers) independent_rng.shuffle(layers)
# go through the shuffled layers until we get the required number of samples. # go through the shuffled layers until we get the required number of samples.
for layer in itertools.cycle(layers): if num_to_drop > 0:
if independent_rng.random() < layerdrop_probs[layer]: for layer in itertools.cycle(layers):
ans.add(layer) if independent_rng.random() < layerdrop_probs[layer]:
if len(ans) == num_to_drop: ans.add(layer)
break if len(ans) == num_to_drop:
break
if shared_rng.random() < 0.005 or __name__ == "__main__": if shared_rng.random() < 0.005 or __name__ == "__main__":
logging.info(f"warmup_begin={warmup_begin}, warmup_end={warmup_end}, warmup_count={warmup_count:.1f}, num_to_drop={num_to_drop}, layers_to_drop={ans}") logging.info(f"warmup_begin={warmup_begin}, warmup_end={warmup_end}, warmup_count={warmup_count:.1f}, num_to_drop={num_to_drop}, layers_to_drop={ans}")
return ans return ans