mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-09-07 08:04:18 +00:00
Fix CI.
This commit is contained in:
parent
ad3fb63ad6
commit
a006d6494f
@ -19,38 +19,38 @@ Usage:
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(1) greedy search
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./pruned_transducer_stateless/pretrained.py \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method greedy_search \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method greedy_search \
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/path/to/foo.wav \
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/path/to/bar.wav
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(2) beam search
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./pruned_transducer_stateless/pretrained.py \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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(3) modified beam search
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./pruned_transducer_stateless/pretrained.py \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method modified_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method modified_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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(4) fast beam search
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./pruned_transducer_stateless/pretrained.py \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method fast_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method fast_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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You can also use `./pruned_transducer_stateless/exp/epoch-xx.pt`.
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@ -233,6 +233,9 @@ def main():
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logging.info("Creating model")
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model = get_transducer_model(params)
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num_param = sum([p.numel() for p in model.parameters()])
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logging.info(f"Number of model parameters: {num_param}")
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checkpoint = torch.load(args.checkpoint, map_location="cpu")
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model.load_state_dict(checkpoint["model"], strict=False)
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model.to(device)
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@ -19,20 +19,38 @@ Usage:
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(1) greedy search
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./pruned_transducer_stateless2/pretrained.py \
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--checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method greedy_search \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method greedy_search \
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/path/to/foo.wav \
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/path/to/bar.wav
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(1) beam search
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(2) beam search
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./pruned_transducer_stateless2/pretrained.py \
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--checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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(3) modified beam search
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./pruned_transducer_stateless2/pretrained.py \
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--checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method modified_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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(4) fast beam search
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./pruned_transducer_stateless2/pretrained.py \
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--checkpoint ./pruned_transducer_stateless2/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method fast_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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You can also use `./pruned_transducer_stateless2/exp/epoch-xx.pt`.
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@ -79,9 +97,7 @@ def get_parser():
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parser.add_argument(
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"--bpe-model",
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type=str,
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help="""Path to bpe.model.
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Used only when method is ctc-decoding.
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""",
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help="""Path to bpe.model.""",
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)
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parser.add_argument(
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@ -117,7 +133,33 @@ def get_parser():
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"--beam-size",
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type=int,
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default=4,
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help="Used only when --method is beam_search and modified_beam_search",
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help="""An integer indicating how many candidates we will keep for each
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frame. Used only when --method is beam_search or
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modified_beam_search.""",
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)
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parser.add_argument(
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"--beam",
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type=float,
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default=4,
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help="""A floating point value to calculate the cutoff score during beam
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search (i.e., `cutoff = max-score - beam`), which is the same as the
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`beam` in Kaldi.
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Used only when --method is fast_beam_search""",
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)
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parser.add_argument(
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"--max-contexts",
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type=int,
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default=4,
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help="""Used only when --method is fast_beam_search""",
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)
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parser.add_argument(
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"--max-states",
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type=int,
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default=8,
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help="""Used only when --method is fast_beam_search""",
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)
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parser.add_argument(
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@ -244,9 +286,9 @@ def main():
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decoding_graph=decoding_graph,
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encoder_out=encoder_out,
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encoder_out_lens=encoder_out_lens,
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beam=8.0,
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max_contexts=32,
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max_states=8,
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beam=params.beam,
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max_contexts=params.max_contexts,
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max_states=params.max_states,
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)
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for hyp in sp.decode(hyp_tokens):
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hyps.append(hyp.split())
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@ -254,6 +296,7 @@ def main():
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hyp_tokens = modified_beam_search(
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model=model,
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encoder_out=encoder_out,
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encoder_out_lens=encoder_out_lens,
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beam=params.beam_size,
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)
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@ -263,6 +306,7 @@ def main():
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hyp_tokens = greedy_search_batch(
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model=model,
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encoder_out=encoder_out,
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encoder_out_lens=encoder_out_lens,
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)
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for hyp in sp.decode(hyp_tokens):
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hyps.append(hyp.split())
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@ -19,20 +19,38 @@ Usage:
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(1) greedy search
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./pruned_transducer_stateless3/pretrained.py \
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--checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method greedy_search \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method greedy_search \
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/path/to/foo.wav \
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/path/to/bar.wav
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(1) beam search
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(2) beam search
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./pruned_transducer_stateless3/pretrained.py \
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--checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav \
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--checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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(3) modified beam search
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./pruned_transducer_stateless3/pretrained.py \
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--checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method modified_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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(4) fast beam search
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./pruned_transducer_stateless3/pretrained.py \
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--checkpoint ./pruned_transducer_stateless3/exp/pretrained.pt \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--method fast_beam_search \
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--beam-size 4 \
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/path/to/foo.wav \
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/path/to/bar.wav
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You can also use `./pruned_transducer_stateless3/exp/epoch-xx.pt`.
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@ -79,9 +97,7 @@ def get_parser():
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parser.add_argument(
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"--bpe-model",
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type=str,
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help="""Path to bpe.model.
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Used only when method is ctc-decoding.
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""",
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help="""Path to bpe.model.""",
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)
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parser.add_argument(
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@ -117,7 +133,33 @@ def get_parser():
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"--beam-size",
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type=int,
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default=4,
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help="Used only when --method is beam_search and modified_beam_search",
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help="""An integer indicating how many candidates we will keep for each
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frame. Used only when --method is beam_search or
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modified_beam_search.""",
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)
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parser.add_argument(
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"--beam",
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type=float,
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default=4,
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help="""A floating point value to calculate the cutoff score during beam
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search (i.e., `cutoff = max-score - beam`), which is the same as the
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`beam` in Kaldi.
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Used only when --method is fast_beam_search""",
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)
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parser.add_argument(
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"--max-contexts",
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type=int,
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default=4,
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help="""Used only when --method is fast_beam_search""",
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)
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parser.add_argument(
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"--max-states",
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type=int,
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default=8,
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help="""Used only when --method is fast_beam_search""",
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)
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parser.add_argument(
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@ -244,9 +286,9 @@ def main():
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decoding_graph=decoding_graph,
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encoder_out=encoder_out,
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encoder_out_lens=encoder_out_lens,
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beam=8.0,
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max_contexts=32,
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max_states=8,
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beam=params.beam,
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max_contexts=params.max_contexts,
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max_states=params.max_states,
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)
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for hyp in sp.decode(hyp_tokens):
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hyps.append(hyp.split())
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@ -254,6 +296,7 @@ def main():
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hyp_tokens = modified_beam_search(
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model=model,
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encoder_out=encoder_out,
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encoder_out_lens=encoder_out_lens,
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beam=params.beam_size,
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)
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@ -263,6 +306,7 @@ def main():
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hyp_tokens = greedy_search_batch(
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model=model,
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encoder_out=encoder_out,
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encoder_out_lens=encoder_out_lens,
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)
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for hyp in sp.decode(hyp_tokens):
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hyps.append(hyp.split())
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