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https://github.com/k2-fsa/icefall.git
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f6ce135608
* Various fixes to support torch script. * Add tests to ensure that the model is torch scriptable. * Update tests.
61 lines
1.5 KiB
Python
Executable File
61 lines
1.5 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang, Wei Kang)
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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 ./pruned_transducer_stateless/test_decoder.py
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"""
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import torch
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from decoder import Decoder
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def test_decoder():
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vocab_size = 3
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blank_id = 0
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unk_id = 2
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embedding_dim = 128
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context_size = 4
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decoder = Decoder(
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vocab_size=vocab_size,
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embedding_dim=embedding_dim,
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blank_id=blank_id,
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unk_id=unk_id,
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context_size=context_size,
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)
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N = 100
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U = 20
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x = torch.randint(low=0, high=vocab_size, size=(N, U))
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y = decoder(x)
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assert y.shape == (N, U, vocab_size)
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# for inference
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x = torch.randint(low=0, high=vocab_size, size=(N, context_size))
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y = decoder(x, need_pad=False)
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assert y.shape == (N, 1, vocab_size)
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def main():
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test_decoder()
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if __name__ == "__main__":
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main()
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