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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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egs/librispeech/ASR/pruned_transducer_stateless7/conformer.py
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@ -471,11 +471,11 @@ 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.
if num_to_drop > 0:
for layer in itertools.cycle(layers): for layer in itertools.cycle(layers):
if independent_rng.random() < layerdrop_probs[layer]: if independent_rng.random() < layerdrop_probs[layer]:
ans.add(layer) ans.add(layer)