export-for-ncnn.sh

#!/usr/bin/env bash

# Please go to
# https://huggingface.co/Zengwei/icefall-asr-librispeech-conv-emformer-transducer-stateless2-2022-07-05
# to download the pre-trained models

#
# cd $dir
# ln -s icefall-asr-librispeech-conv-emformer-transducer-stateless2-2022-07-05/exp/pretrained-epoch-30-avg-10-averaged.pt epoch-30.pt

. path.sh

export CUDA_VISIBLE_DEVICES=""

dir=test-conv-emformer-librispeech
./conv_emformer_transducer_stateless2/export-for-ncnn.py \
  --exp-dir $dir \
  --epoch 30 \
  --avg 1 \
  --use-averaged-model 0 \
  \
  --num-encoder-layers 12 \
  --chunk-length 32 \
  --cnn-module-kernel 31 \
  --left-context-length 32 \
  --right-context-length 8 \
  --memory-size 32

mv ./test-conv-emformer-librispeech/encoder_jit_trace-pnnx.pt \
   ./test-conv-emformer-librispeech/encoder_jit_trace-epoch-30-avg-10-pnnx.pt

mv ./test-conv-emformer-librispeech/decoder_jit_trace-pnnx.pt \
   ./test-conv-emformer-librispeech/decoder_jit_trace-epoch-30-avg-10-pnnx.pt

mv ./test-conv-emformer-librispeech/joiner_jit_trace-pnnx.pt \
   ./test-conv-emformer-librispeech/joiner_jit_trace-epoch-30-avg-10-pnnx.pt

cd test-conv-emformer-librispeech

# If you are going to quantize the model using int8, please use
#
# pnnx encoder_jit_trace-epoch-30-avg-10-pnnx.pt fp16=0
# pnnx joiner_jit_trace-epoch-30-avg-10-pnnx.pt fp16=0
#

pnnx encoder_jit_trace-epoch-30-avg-10-pnnx.pt
pnnx decoder_jit_trace-epoch-30-avg-10-pnnx.pt
pnnx joiner_jit_trace-epoch-30-avg-10-pnnx.pt

# Note: You have to change encoder_jit_trace-epoch-30-avg-10-pnnx.ncnn.param
#
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#1060 1342
#Input                    in0                      0 1 in0
#
# to

#7767517
#1061 1342
#SherpaMetaData           sherpa_meta_data1        0 0 0=1 1=12 2=32 3=31 4=8 5=32 6=8 7=512
#Input                    in0                      0 1 in0