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Add num_features arg
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@ -31,7 +31,7 @@ export CUDA_VISIBLE_DEVICES="0,1,2,3"
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--exp-dir conformer_ctc2/exp \
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--lang-dir data/lang_bpe_200 \
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--otc-token "<star>" \
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--num-features 80 \
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--num-features 768 \
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--allow-bypass-arc true \
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--allow-self-loop-arc true \
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--initial-bypass-weight -19 \
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@ -383,8 +383,8 @@ def get_params() -> AttributeDict:
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- warm_step: The warm_step for Noam optimizer.
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"""
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parser = get_parser()
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LibriSpeechAsrDataModule.add_arguments(parser)
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args = parser.parse_args()
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feature_dim = args.num_features
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params = AttributeDict(
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{
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"best_train_loss": float("inf"),
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@ -397,7 +397,7 @@ def get_params() -> AttributeDict:
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"valid_interval": 800, # For the 100h subset, use 800
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"alignment_interval": 25,
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# parameters for conformer
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"feature_dim": feature_dim,
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"feature_dim": args.num_features,
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"subsampling_factor": 2,
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"encoder_dim": 512,
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"nhead": 8,
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