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* Begin to add RNN-T training for librispeech. * Copy files from conformer_ctc. Will edit it. * Use conformer/transformer model as encoder. * Begin to add training script. * Add training code. * Remove long utterances to avoid OOM when a large max_duraiton is used. * Begin to add decoding script. * Add decoding script. * Minor fixes. * Add beam search. * Use LSTM layers for the encoder. Need more tunings. * Use stateless decoder. * Minor fixes to make it ready for merge. * Fix README. * Update RESULT.md to include RNN-T Conformer. * Minor fixes. * Fix tests. * Minor fixes. * Minor fixes. * Fix tests.
49 lines
1.2 KiB
Python
Executable File
49 lines
1.2 KiB
Python
Executable File
#!/usr/bin/env python3
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#
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# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
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#
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# See ../../../../LICENSE for clarification regarding multiple authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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To run this file, do:
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cd icefall/egs/librispeech/ASR
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python ./transducer_lstm/test_encoder.py
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"""
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from encoder import LstmEncoder
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def test_encoder():
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encoder = LstmEncoder(
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num_features=80,
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hidden_size=1024,
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proj_size=512,
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output_dim=512,
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subsampling_factor=4,
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num_encoder_layers=12,
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)
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num_params = sum(p.numel() for p in encoder.parameters() if p.requires_grad)
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print(num_params)
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# 93979284
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# 66427392
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def main():
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test_encoder()
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if __name__ == "__main__":
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main()
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