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Fix bug in choosing layers to drop

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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
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12
egs/librispeech/ASR/pruned_transducer_stateless7/conformer.py
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@ -471,16 +471,16 @@ class ConformerEncoder(nn.Module):
# with their specified probs while reaching this exact target.
num_to_drop = int(tot) + int(shared_rng.random() < (tot - int(tot)))
layers = list(range(num_layers))
independent_rng.shuffle(layers)
# go through the shuffled layers until we get the required number of samples.
for layer in itertools.cycle(layers):
if independent_rng.random() < layerdrop_probs[layer]:
ans.add(layer)
if len(ans) == num_to_drop:
break
if num_to_drop > 0:
for layer in itertools.cycle(layers):
if independent_rng.random() < layerdrop_probs[layer]:
ans.add(layer)
if len(ans) == num_to_drop:
break
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}")
return ans