Fangjun Kuang 1d44da845b
RNN-T Conformer training for LibriSpeech (#143)
* 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.
2021-12-18 07:42:51 +08:00

49 lines
1.2 KiB
Python
Executable File

#!/usr/bin/env python3
#
# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
#
# See ../../../../LICENSE for clarification regarding multiple authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
To run this file, do:
cd icefall/egs/librispeech/ASR
python ./transducer_lstm/test_encoder.py
"""
from encoder import LstmEncoder
def test_encoder():
encoder = LstmEncoder(
num_features=80,
hidden_size=1024,
proj_size=512,
output_dim=512,
subsampling_factor=4,
num_encoder_layers=12,
)
num_params = sum(p.numel() for p in encoder.parameters() if p.requires_grad)
print(num_params)
# 93979284
# 66427392
def main():
test_encoder()
if __name__ == "__main__":
main()