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Add num_features to train.py for training WSASR (#1528)

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Rezakh20 2024-03-05 12:10:30 +03:30 committed by GitHub
parent 242002e0bd
commit ff430b465f
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1 changed files with 9 additions and 1 deletions
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egs/librispeech/WSASR/conformer_ctc2/train.py
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@ -31,6 +31,7 @@ export CUDA_VISIBLE_DEVICES="0,1,2,3"
--exp-dir conformer_ctc2/exp \ --exp-dir conformer_ctc2/exp \
--lang-dir data/lang_bpe_200 \ --lang-dir data/lang_bpe_200 \
--otc-token "<star>" \ --otc-token "<star>" \
--feature-dim 768 \
--allow-bypass-arc true \ --allow-bypass-arc true \
--allow-self-loop-arc true \ --allow-self-loop-arc true \
--initial-bypass-weight -19 \ --initial-bypass-weight -19 \
@ -159,6 +160,14 @@ def get_parser():
"lexicon.txt" "lexicon.txt"
""", """,
) )
parser.add_argument(
"--feature-dim",
type=int,
default=768,
help="""Number of features extracted in feature extraction stage.last dimension of feature vector.
80 when using fbank features and 768 or 1024 whn using wave2vec""",
)
parser.add_argument( parser.add_argument(
"--initial-lr", "--initial-lr",
@ -385,7 +394,6 @@ def get_params() -> AttributeDict:
"valid_interval": 800, # For the 100h subset, use 800 "valid_interval": 800, # For the 100h subset, use 800
"alignment_interval": 25, "alignment_interval": 25,
# parameters for conformer # parameters for conformer
"feature_dim": 768,
"subsampling_factor": 2, "subsampling_factor": 2,
"encoder_dim": 512, "encoder_dim": 512,
"nhead": 8, "nhead": 8,