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Bug fixes in conformer_bn dir
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@ -246,7 +246,7 @@ class DiscreteBottleneck(nn.Module):
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self.class_probs = (self.class_probs * self.class_probs_decay +
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mean_class_probs * (1.0 - self.class_probs_decay))
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prob_floor = self.min_prob_ratio / self.classes_per_group
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self.class_offsets += (self.class_probs > prob_floor) * self.prob_boost
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self.class_offsets += (self.class_probs < prob_floor) * self.prob_boost
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else:
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x = torch.softmax(x, dim=-1)
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@ -21,25 +21,6 @@
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# 6000 of epoch 15. was 0.429 last time the valid loss was printed on
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# epoch 14.
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# RESULTS (it's worse!), with:
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# python3 conformer_ctc_bn/decode.py --lattice-score-scale=0.5 --method=attention-decoder --epoch=25 --avg=10 --max-duration=30
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#
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# With sampling in test-time:
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# ngram_lm_scale_1.2_attention_scale_1.5 3.48 best for test-clean
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# ngram_lm_scale_0.9_attention_scale_1.2 8.4 best for test-other
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# After I modified conformer.py so that in eval mode, it uses the softmax output with no sampling:
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# ngram_lm_scale_0.9_attention_scale_1.2 3.44 best for test-clean
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# ngram_lm_scale_0.9_attention_scale_1.0 8.09 best for test-other
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# Vs. BASELINE:
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# evaluated with
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# python3 conformer_ctc/decode.py --lattice-score-scale=0.5 --method=attention-decoder --epoch=23 --avg=10 --max-duration=30 &
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# (also uses foam optimizer)
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# ngram_lm_scale_1.2_attention_scale_1.2 2.8 best for test-clean
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# ngram_lm_scale_0.9_attention_scale_0.7 6.6 best for test-other
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import argparse
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import logging
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from pathlib import Path
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