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Merge branch 'zlm25' into zlm26

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Daniel Povey 2023-05-20 22:24:15 +08:00
commit 45043e2e21
1 changed files with 1 additions and 4 deletions
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egs/libriheavy/LM/zipformer1/subformer.py
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@ -876,15 +876,12 @@ class LearnedDownsamplingModule(nn.Module):
logging.info(f"mean weight={weights.mean()}, mean-abs-scores={scores.abs().mean()} positive-scores={(scores>0).to(torch.float32).mean()}, discarded-weights={weights_discarded.mean()}, seq_len={seq_len}, seq_len_reduced={seq_len_reduced}") logging.info(f"mean weight={weights.mean()}, mean-abs-scores={scores.abs().mean()} positive-scores={(scores>0).to(torch.float32).mean()}, discarded-weights={weights_discarded.mean()}, seq_len={seq_len}, seq_len_reduced={seq_len_reduced}")
# we were getting too many discarded weights before introducing this factor, which was
# hurting test-mode performance by creating a mismatch.
discarded_weights_factor = 2.0
if random.random() < 0.5: if random.random() < 0.5:
# flipping it half the time increases the randomness, so gives an extra incentive # flipping it half the time increases the randomness, so gives an extra incentive
# to avoid nonzero weights in the discarded half # to avoid nonzero weights in the discarded half
weights_discarded = weights_discarded.flip(dims=(1,)) weights_discarded = weights_discarded.flip(dims=(1,))
weights = (weights[:, :seq_len_reduced] - (weights_discarded * discarded_weights_factor)).clamp(min=0.0, max=1.0) weights = weights[:, :seq_len_reduced] - weights_discarded
else: else:
# test mode. because the sequence might be short, we keep all nonzero scores; # test mode. because the sequence might be short, we keep all nonzero scores;
# and there is no need for any penalty. # and there is no need for any penalty.