Export model with torch.jit.trace()

In this section, we describe how to export a model via torch.jit.trace().

When to use it

If we want to use our trained model with torchscript, we can use torch.jit.trace().

Hint

See Export model with torch.jit.script() if you want to use torch.jit.script().

How to export

We use https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/lstm_transducer_stateless2 as an example in the following.

iter=468000
avg=16

cd egs/librispeech/ASR

./lstm_transducer_stateless2/export.py \
  --exp-dir ./lstm_transducer_stateless2/exp \
  --tokens data/lang_bpe_500/tokens.txt \
  --iter $iter \
  --avg  $avg \
  --jit-trace 1

It will generate three files inside lstm_transducer_stateless2/exp:

encoder_jit_trace.pt

decoder_jit_trace.pt

joiner_jit_trace.pt

You can use https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/lstm_transducer_stateless2/jit_pretrained.py to decode sound files with the following commands:

cd egs/librispeech/ASR
./lstm_transducer_stateless2/jit_pretrained.py \
  --bpe-model ./data/lang_bpe_500/bpe.model \
  --encoder-model-filename ./lstm_transducer_stateless2/exp/encoder_jit_trace.pt \
  --decoder-model-filename ./lstm_transducer_stateless2/exp/decoder_jit_trace.pt \
  --joiner-model-filename ./lstm_transducer_stateless2/exp/joiner_jit_trace.pt \
  /path/to/foo.wav \
  /path/to/bar.wav \
  /path/to/baz.wav

How to use the exported models

Please refer to https://k2-fsa.github.io/sherpa/python/streaming_asr/lstm/index.html for its usage in sherpa. You can also find pretrained models there.