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dohe0342 2023-02-14 13:00:21 +09:00
parent a8e1b34735
commit 326a55eebc
2 changed files with 28 additions and 12 deletions
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egs/tedlium2/ASR/conformer_ctc3/.train.py.swp
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egs/tedlium2/ASR/conformer_ctc3/train.py
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@ -543,20 +543,36 @@ def compute_loss(
#token_ids = convert_texts_into_ids(texts, graph_compiler.sp)
token_ids = graph_compiler.texts_to_ids(texts)
decoding_graph = graph_compiler.compile(token_ids)
if params.interctc:
dense_fsa_vec1 = k2.DenseFsaVec(
nnet_output[8],
supervision_segments,
allow_truncate=params.subsampling_factor - 1,
)
dense_fsa_vec = k2.DenseFsaVec(
nnet_output,
supervision_segments,
allow_truncate=params.subsampling_factor - 1,
)
ctc_loss = k2.ctc_loss(
decoding_graph=decoding_graph,
dense_fsa_vec=dense_fsa_vec,
output_beam=params.beam_size,
reduction=params.reduction,
use_double_scores=params.use_double_scores,
)
ctc_loss = k2.ctc_loss(
decoding_graph=decoding_graph,
dense_fsa_vec=dense_fsa_vec,
output_beam=params.beam_size,
reduction=params.reduction,
use_double_scores=params.use_double_scores,
)
else:
dense_fsa_vec = k2.DenseFsaVec(
nnet_output,
supervision_segments,
allow_truncate=params.subsampling_factor - 1,
)
ctc_loss = k2.ctc_loss(
decoding_graph=decoding_graph,
dense_fsa_vec=dense_fsa_vec,
output_beam=params.beam_size,
reduction=params.reduction,
use_double_scores=params.use_double_scores,
)
if params.att_rate > 0.0:
with torch.set_grad_enabled(is_training):