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modify doc

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This commit is contained in:
yaozengwei 2022-07-24 20:00:57 +08:00
parent 9576b2cb2c
commit 0adfe6595d
9 changed files with 27 additions and 18 deletions
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5
egs/librispeech/ASR/conv_emformer_transducer_stateless/train.py
View File

@ -686,10 +686,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/conv_emformer_transducer_stateless2/train.py
View File

@ -686,10 +686,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/pruned_stateless_emformer_rnnt2/train.py
View File

@ -603,10 +603,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/pruned_transducer_stateless/train.py
View File

@ -559,10 +559,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/pruned_transducer_stateless2/train.py
View File

@ -627,10 +627,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/pruned_transducer_stateless3/train.py
View File

@ -652,10 +652,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/pruned_transducer_stateless4/train.py
View File

@ -657,10 +657,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/pruned_transducer_stateless5/train.py
View File

@ -644,10 +644,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)

5
egs/librispeech/ASR/pruned_transducer_stateless6/train.py
View File

@ -661,10 +661,11 @@ def compute_loss(
(feature_lens // params.subsampling_factor).sum().item()
)
info["utterances"] = feature.size(0)
# `utt_duration` and `utt_pad_proportion` would be normalized by `utterances` # noqa
info["utterances"] = feature.size(0)
# averaged input duration in frames over utterances
info["utt_duration"] = feature_lens.sum().item()
# padding proportion of each utterance
# averaged padding proportion over utterances
info["utt_pad_proportion"] = (
((feature.size(1) - feature_lens) / feature.size(1)).sum().item()
)