mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-08 09:32:20 +00:00
Export streaming zipformer models with whisper feature to onnx (#1973)
This commit is contained in:
Fangjun Kuang
GitHub
parent
abd9437e6d
commit
71377d21cd
4
.github/scripts/docker/Dockerfile
vendored
4
.github/scripts/docker/Dockerfile
vendored
@ -55,9 +55,9 @@ RUN pip install --no-cache-dir \
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"numpy<2.0" \
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onnxoptimizer \
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onnxsim \
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onnx \
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onnx==1.17.0 \
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onnxmltools \
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onnxruntime \
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onnxruntime==1.17.1 \
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piper_phonemize -f https://k2-fsa.github.io/icefall/piper_phonemize.html \
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pypinyin==0.50.0 \
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pytest \
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21
.github/scripts/docker/generate_build_matrix.py
vendored
21
.github/scripts/docker/generate_build_matrix.py
vendored
@ -63,23 +63,24 @@ def get_torchaudio_version(torch_version):
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def get_matrix(min_torch_version, specified_torch_version, specified_python_version):
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k2_version = "1.24.4.dev20241029"
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kaldifeat_version = "1.25.5.dev20241029"
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version = "20241218"
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k2_version = "1.24.4.dev20250630"
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kaldifeat_version = "1.25.5.dev20250630"
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version = "20250630"
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# torchaudio 2.5.0 does not support python 3.13
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python_version = ["3.8", "3.9", "3.10", "3.11", "3.12"]
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python_version = ["3.8", "3.9", "3.10", "3.11", "3.12", "3.13"]
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torch_version = []
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torch_version += ["1.13.0", "1.13.1"]
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torch_version += ["2.0.0", "2.0.1"]
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# torch_version += ["2.1.0", "2.1.1", "2.1.2"]
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# torch_version += ["2.2.0", "2.2.1", "2.2.2"]
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torch_version += ["2.1.0", "2.1.1", "2.1.2"]
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torch_version += ["2.2.0", "2.2.1", "2.2.2"]
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# Test only torch >= 2.3.0
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torch_version += ["2.3.0", "2.3.1"]
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torch_version += ["2.4.0"]
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torch_version += ["2.4.1"]
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torch_version += ["2.5.0"]
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torch_version += ["2.5.1"]
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torch_version += ["2.6.0", "2.7.0", "2.7.1"]
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if specified_torch_version:
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torch_version = [specified_torch_version]
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@ -109,12 +110,8 @@ def get_matrix(min_torch_version, specified_torch_version, specified_python_vers
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# torch>=2.5 requires python 3.10
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continue
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if t == "2.5.1":
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k2_version_2 = "1.24.4.dev20241122"
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kaldifeat_version_2 = "1.25.5.dev20241126"
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else:
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k2_version_2 = k2_version
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kaldifeat_version_2 = kaldifeat_version
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k2_version_2 = k2_version
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kaldifeat_version_2 = kaldifeat_version
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matrix.append(
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{
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200
.github/scripts/multi-zh-hans.sh
vendored
200
.github/scripts/multi-zh-hans.sh
vendored
@ -1,200 +0,0 @@
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#!/usr/bin/env bash
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set -ex
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git config --global user.name "k2-fsa"
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git config --global user.email "csukuangfj@gmail.com"
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git config --global lfs.allowincompletepush true
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log() {
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# This function is from espnet
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local fname=${BASH_SOURCE[1]##*/}
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echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
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}
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log "pwd: $PWD"
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cd egs/multi_zh-hans/ASR
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repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-2023-9-2
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log "Downloading pre-trained model from $repo_url"
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GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
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repo=$(basename $repo_url)
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pushd $repo
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cd exp
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git lfs pull --include pretrained.pt
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ln -s pretrained.pt epoch-99.pt
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cd ../data/lang_bpe_2000
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ls -lh
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git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
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git lfs pull --include "*.model"
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ls -lh
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popd
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log "--------------------------------------------"
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log "Export non-streaming ONNX transducer models "
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log "--------------------------------------------"
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./zipformer/export-onnx.py \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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--use-averaged-model 0 \
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--epoch 99 \
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--avg 1 \
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--exp-dir $repo/exp \
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--causal False
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ls -lh $repo/exp
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./zipformer/onnx_pretrained.py \
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--encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.onnx \
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--decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.onnx \
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--joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.onnx \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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$repo/test_wavs/DEV_T0000000000.wav \
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$repo/test_wavs/DEV_T0000000001.wav \
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$repo/test_wavs/DEV_T0000000002.wav \
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$repo/test_wavs/TEST_MEETING_T0000000113.wav \
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$repo/test_wavs/TEST_MEETING_T0000000219.wav \
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$repo/test_wavs/TEST_MEETING_T0000000351.wav
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rm -rf $repo
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repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-ctc-streaming-2023-11-05
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log "Downloading pre-trained model from $repo_url"
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GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
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repo=$(basename $repo_url)
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pushd $repo
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cd exp/
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git lfs pull --include pretrained.pt
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rm -fv epoch-20.pt
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rm -fv *.onnx
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ln -s pretrained.pt epoch-20.pt
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cd ../data/lang_bpe_2000
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ls -lh
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git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
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git lfs pull --include "*.model"
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ls -lh
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popd
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log "----------------------------------------"
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log "Export streaming ONNX CTC models "
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log "----------------------------------------"
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./zipformer/export-onnx-streaming-ctc.py \
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--exp-dir $repo/exp \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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--causal 1 \
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--avg 1 \
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--epoch 20 \
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--use-averaged-model 0 \
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--chunk-size 16 \
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--left-context-frames 128 \
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--use-ctc 1
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ls -lh $repo/exp/
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log "------------------------------------------------------------"
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log "Test exported streaming ONNX CTC models (greedy search) "
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log "------------------------------------------------------------"
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test_wavs=(
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DEV_T0000000000.wav
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DEV_T0000000001.wav
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DEV_T0000000002.wav
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TEST_MEETING_T0000000113.wav
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TEST_MEETING_T0000000219.wav
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TEST_MEETING_T0000000351.wav
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)
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for w in ${test_wavs[@]}; do
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./zipformer/onnx_pretrained-streaming-ctc.py \
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--model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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$repo/test_wavs/$w
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done
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log "Upload onnx CTC models to huggingface"
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url=https://huggingface.co/k2-fsa/sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13
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GIT_LFS_SKIP_SMUDGE=1 git clone $url
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dst=$(basename $url)
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cp -v $repo/exp/ctc*.onnx $dst
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cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
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cp -v $repo/data/lang_bpe_2000/bpe.model $dst
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mkdir -p $dst/test_wavs
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cp -v $repo/test_wavs/*.wav $dst/test_wavs
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cd $dst
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git lfs track "*.onnx" "bpe.model"
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ls -lh
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file bpe.model
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git status
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git add .
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git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
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log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
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rm -rf .git
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rm -fv .gitattributes
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cd ..
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tar cjfv $dst.tar.bz2 $dst
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ls -lh *.tar.bz2
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mv -v $dst.tar.bz2 ../../../
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log "----------------------------------------"
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log "Export streaming ONNX transducer models "
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log "----------------------------------------"
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./zipformer/export-onnx-streaming.py \
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--exp-dir $repo/exp \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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--causal 1 \
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--avg 1 \
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--epoch 20 \
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--use-averaged-model 0 \
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--chunk-size 16 \
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--left-context-frames 128 \
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--use-ctc 0
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ls -lh $repo/exp
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log "------------------------------------------------------------"
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log "Test exported streaming ONNX transducer models (Python code)"
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log "------------------------------------------------------------"
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log "test fp32"
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./zipformer/onnx_pretrained-streaming.py \
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--encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.onnx \
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--decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
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--joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.onnx \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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$repo/test_wavs/DEV_T0000000000.wav
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log "test int8"
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./zipformer/onnx_pretrained-streaming.py \
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--encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
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--decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
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--joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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$repo/test_wavs/DEV_T0000000000.wav
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log "Upload onnx transducer models to huggingface"
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url=https://huggingface.co/k2-fsa/sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12
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GIT_LFS_SKIP_SMUDGE=1 git clone $url
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dst=$(basename $url)
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cp -v $repo/exp/encoder*.onnx $dst
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cp -v $repo/exp/decoder*.onnx $dst
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cp -v $repo/exp/joiner*.onnx $dst
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cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
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cp -v $repo/data/lang_bpe_2000/bpe.model $dst
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mkdir -p $dst/test_wavs
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cp -v $repo/test_wavs/*.wav $dst/test_wavs
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cd $dst
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git lfs track "*.onnx" bpe.model
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git add .
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git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
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log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
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rm -rf .git
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rm -fv .gitattributes
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cd ..
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tar cjfv $dst.tar.bz2 $dst
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ls -lh *.tar.bz2
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mv -v $dst.tar.bz2 ../../../
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756
.github/scripts/multi_zh-hans/ASR/run.sh
vendored
Executable file
756
.github/scripts/multi_zh-hans/ASR/run.sh
vendored
Executable file
@ -0,0 +1,756 @@
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#!/usr/bin/env bash
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set -ex
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git config --global user.name "k2-fsa"
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git config --global user.email "csukuangfj@gmail.com"
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git config --global lfs.allowincompletepush true
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python3 -m pip install onnxmltools==1.13.0 onnx==1.17.0 onnxruntime==1.17.1 sherpa-onnx
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log() {
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# This function is from espnet
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local fname=${BASH_SOURCE[1]##*/}
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echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
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}
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cd egs/multi_zh-hans/ASR
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log "pwd: $PWD"
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function run_2023_9_2() {
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repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-2023-9-2
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log "Downloading pre-trained model from $repo_url"
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GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
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repo=$(basename $repo_url)
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pushd $repo
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cd exp
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git lfs pull --include pretrained.pt
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ln -s pretrained.pt epoch-99.pt
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cd ../data/lang_bpe_2000
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ls -lh
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git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
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git lfs pull --include "*.model"
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ls -lh
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popd
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log "--------------------------------------------"
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log "Export non-streaming ONNX transducer models "
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log "--------------------------------------------"
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./zipformer/export-onnx.py \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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--use-averaged-model 0 \
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--epoch 99 \
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--avg 1 \
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--exp-dir $repo/exp \
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--causal False \
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--fp16 1
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ls -lh $repo/exp
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./zipformer/onnx_pretrained.py \
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--encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.onnx \
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--decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.onnx \
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--joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.onnx \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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$repo/test_wavs/DEV_T0000000000.wav \
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$repo/test_wavs/DEV_T0000000001.wav \
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$repo/test_wavs/DEV_T0000000002.wav \
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$repo/test_wavs/TEST_MEETING_T0000000113.wav \
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$repo/test_wavs/TEST_MEETING_T0000000219.wav \
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$repo/test_wavs/TEST_MEETING_T0000000351.wav
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./zipformer/onnx_pretrained.py \
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--encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.int8.onnx \
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--decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.onnx \
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--joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.int8.onnx \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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$repo/test_wavs/DEV_T0000000000.wav \
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$repo/test_wavs/DEV_T0000000001.wav \
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$repo/test_wavs/DEV_T0000000002.wav \
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$repo/test_wavs/TEST_MEETING_T0000000113.wav \
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$repo/test_wavs/TEST_MEETING_T0000000219.wav \
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$repo/test_wavs/TEST_MEETING_T0000000351.wav
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./zipformer/onnx_pretrained.py \
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--encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.fp16.onnx \
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--decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.fp16.onnx \
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--joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.fp16.onnx \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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$repo/test_wavs/DEV_T0000000000.wav \
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$repo/test_wavs/DEV_T0000000001.wav \
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$repo/test_wavs/DEV_T0000000002.wav \
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$repo/test_wavs/TEST_MEETING_T0000000113.wav \
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$repo/test_wavs/TEST_MEETING_T0000000219.wav \
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$repo/test_wavs/TEST_MEETING_T0000000351.wav
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rm -rf $repo
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}
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function run_2023_11_05_streaming() {
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repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-ctc-streaming-2023-11-05
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log "Downloading pre-trained model from $repo_url"
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GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
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repo=$(basename $repo_url)
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pushd $repo
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cd exp/
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git lfs pull --include pretrained.pt
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rm -fv epoch-20.pt
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rm -fv *.onnx
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ln -s pretrained.pt epoch-20.pt
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cd ../data/lang_bpe_2000
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ls -lh
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git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
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git lfs pull --include "*.model"
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||||
ls -lh
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popd
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log "----------------------------------------"
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log "Export streaming ONNX CTC models "
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log "----------------------------------------"
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||||
./zipformer/export-onnx-streaming-ctc.py \
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--exp-dir $repo/exp \
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--tokens $repo/data/lang_bpe_2000/tokens.txt \
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--causal 1 \
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--avg 1 \
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--epoch 20 \
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--use-averaged-model 0 \
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--chunk-size 16 \
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--left-context-frames 128 \
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--use-ctc 1 \
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--fp16 1
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||||
ls -lh $repo/exp/
|
||||
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log "------------------------------------------------------------"
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||||
log "Test exported streaming ONNX CTC models (greedy search) "
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||||
log "------------------------------------------------------------"
|
||||
|
||||
test_wavs=(
|
||||
DEV_T0000000000.wav
|
||||
DEV_T0000000001.wav
|
||||
DEV_T0000000002.wav
|
||||
TEST_MEETING_T0000000113.wav
|
||||
TEST_MEETING_T0000000219.wav
|
||||
TEST_MEETING_T0000000351.wav
|
||||
)
|
||||
|
||||
for w in ${test_wavs[@]}; do
|
||||
log "----fp32----"
|
||||
./zipformer/onnx_pretrained-streaming-ctc.py \
|
||||
--model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.onnx \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
|
||||
log "----int8----"
|
||||
|
||||
./zipformer/onnx_pretrained-streaming-ctc.py \
|
||||
--model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
|
||||
log "----fp16----"
|
||||
|
||||
./zipformer/onnx_pretrained-streaming-ctc.py \
|
||||
--model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
done
|
||||
|
||||
log "Upload onnx CTC models to huggingface"
|
||||
name=(
|
||||
sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13
|
||||
sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-int8-2023-12-13
|
||||
sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-fp16-2023-12-13
|
||||
)
|
||||
for n in ${name[@]}; do
|
||||
url=https://huggingface.co/k2-fsa/$n
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $url
|
||||
dst=$(basename $url)
|
||||
if [[ $n == sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13 ]]; then
|
||||
cp -v $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-int8-2023-12-13 ]]; then
|
||||
cp -v $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.int8.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-fp16-2023-12-13 ]]; then
|
||||
cp -v $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
|
||||
fi
|
||||
|
||||
cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
|
||||
cp -v $repo/data/lang_bpe_2000/bpe.model $dst
|
||||
mkdir -p $dst/test_wavs
|
||||
cp -v $repo/test_wavs/*.wav $dst/test_wavs
|
||||
cd $dst
|
||||
git lfs track "*.onnx" "bpe.model" "*.wav"
|
||||
ls -lh
|
||||
file bpe.model
|
||||
git status
|
||||
git add .
|
||||
git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
|
||||
|
||||
log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
|
||||
rm -rf .git
|
||||
rm -fv .gitattributes
|
||||
cd ..
|
||||
tar cjfv $dst.tar.bz2 $dst
|
||||
ls -lh *.tar.bz2
|
||||
mv -v $dst.tar.bz2 ../../../
|
||||
done
|
||||
|
||||
log "----------------------------------------"
|
||||
log "Export streaming ONNX transducer models "
|
||||
log "----------------------------------------"
|
||||
|
||||
./zipformer/export-onnx-streaming.py \
|
||||
--exp-dir $repo/exp \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
--causal 1 \
|
||||
--avg 1 \
|
||||
--epoch 20 \
|
||||
--use-averaged-model 0 \
|
||||
--chunk-size 16 \
|
||||
--left-context-frames 128 \
|
||||
--use-ctc 0 \
|
||||
--fp16 1
|
||||
|
||||
ls -lh $repo/exp
|
||||
|
||||
log "------------------------------------------------------------"
|
||||
log "Test exported streaming ONNX transducer models (Python code)"
|
||||
log "------------------------------------------------------------"
|
||||
|
||||
log "test fp32"
|
||||
./zipformer/onnx_pretrained-streaming.py \
|
||||
--encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.onnx \
|
||||
--decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
|
||||
--joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.onnx \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
$repo/test_wavs/DEV_T0000000000.wav
|
||||
|
||||
log "test int8"
|
||||
./zipformer/onnx_pretrained-streaming.py \
|
||||
--encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
|
||||
--decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
|
||||
--joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
$repo/test_wavs/DEV_T0000000000.wav
|
||||
|
||||
log "test fp16"
|
||||
./zipformer/onnx_pretrained-streaming.py \
|
||||
--encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
|
||||
--decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
|
||||
--joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
$repo/test_wavs/DEV_T0000000000.wav
|
||||
|
||||
name=(
|
||||
sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-13
|
||||
sherpa-onnx-streaming-zipformer-multi-zh-hans-int8-2023-12-13
|
||||
sherpa-onnx-streaming-zipformer-multi-zh-hans-fp16-2023-12-13
|
||||
)
|
||||
|
||||
for n in ${name[@]}; do
|
||||
url=https://huggingface.co/csukuangfj/$n
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $url
|
||||
dst=$(basename $url)
|
||||
if [[ $n == sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-13 ]]; then
|
||||
cp -v $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.onnx $dst
|
||||
cp -v $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx $dst
|
||||
cp -v $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-multi-zh-hans-int8-2023-12-13 ]]; then
|
||||
cp -v $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx $dst
|
||||
cp -v $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx $dst
|
||||
cp -v $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-multi-zh-hans-fp16-2023-12-13 ]]; then
|
||||
cp -v $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
|
||||
cp -v $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
|
||||
cp -v $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
|
||||
fi
|
||||
|
||||
cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
|
||||
cp -v $repo/data/lang_bpe_2000/bpe.model $dst
|
||||
mkdir -p $dst/test_wavs
|
||||
cp -v $repo/test_wavs/*.wav $dst/test_wavs
|
||||
cd $dst
|
||||
git lfs track "*.onnx" "bpe.model" "*.wav"
|
||||
ls -lh
|
||||
file bpe.model
|
||||
git status
|
||||
git add .
|
||||
git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
|
||||
|
||||
log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
|
||||
rm -rf .git
|
||||
rm -fv .gitattributes
|
||||
cd ..
|
||||
tar cjfv $dst.tar.bz2 $dst
|
||||
ls -lh *.tar.bz2
|
||||
mv -v $dst.tar.bz2 ../../../
|
||||
done
|
||||
}
|
||||
|
||||
function run_2023_12_12_streaming() {
|
||||
log "Upload onnx transducer models to huggingface"
|
||||
|
||||
url=https://huggingface.co/k2-fsa/sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $url
|
||||
dst=$(basename $url)
|
||||
cp -v $repo/exp/encoder*.onnx $dst
|
||||
cp -v $repo/exp/decoder*.onnx $dst
|
||||
cp -v $repo/exp/joiner*.onnx $dst
|
||||
cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
|
||||
cp -v $repo/data/lang_bpe_2000/bpe.model $dst
|
||||
mkdir -p $dst/test_wavs
|
||||
cp -v $repo/test_wavs/*.wav $dst/test_wavs
|
||||
cd $dst
|
||||
git lfs track "*.onnx" bpe.model "*.wav"
|
||||
git add .
|
||||
git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
|
||||
|
||||
log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
|
||||
rm -rf .git
|
||||
rm -fv .gitattributes
|
||||
cd ..
|
||||
tar cjfv $dst.tar.bz2 $dst
|
||||
ls -lh *.tar.bz2
|
||||
mv -v $dst.tar.bz2 ../../../
|
||||
}
|
||||
|
||||
function run_yuekai_large() {
|
||||
repo_url=https://csukuangfj:${HF_TOKEN}@huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-large
|
||||
log "Downloading pre-trained model from $repo_url"
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
|
||||
repo=$(basename $repo_url)
|
||||
pushd $repo
|
||||
git lfs pull --include pretrained.pt
|
||||
mv pretrained.pt epoch-99.pt
|
||||
curl -SL -O https://huggingface.co/pingzxy/icefall-asr-multi-zh-hans-zipformer-large-onnx/resolve/main/tokens.txt
|
||||
popd
|
||||
|
||||
log "----------------------------------------"
|
||||
log "Export streaming ONNX CTC models "
|
||||
log "----------------------------------------"
|
||||
./zipformer/export-onnx-streaming-ctc.py \
|
||||
--exp-dir $repo/ \
|
||||
--tokens $repo/tokens.txt \
|
||||
--causal 1 \
|
||||
--avg 1 \
|
||||
--epoch 99 \
|
||||
--use-averaged-model 0 \
|
||||
--chunk-size 16 \
|
||||
--left-context-frames 128 \
|
||||
--use-ctc 1 \
|
||||
\
|
||||
--num-encoder-layers 2,2,4,5,4,2 \
|
||||
--feedforward-dim 768,1024,1536,2048,1536,768 \
|
||||
--encoder-dim 256,384,512,768,512,256 \
|
||||
--encoder-unmasked-dim 192,192,256,320,256,192 \
|
||||
\
|
||||
--fp16 1 \
|
||||
--use-whisper-features 1
|
||||
|
||||
|
||||
ls -lh $repo/
|
||||
pushd $repo
|
||||
|
||||
cat >README.md <<EOF
|
||||
# Introduction
|
||||
|
||||
This model is converted
|
||||
from
|
||||
https://huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-large
|
||||
|
||||
The training code can be found at
|
||||
https://github.com/k2-fsa/icefall/blob/master/egs/multi_zh-hans/ASR/RESULTS.md#multi-chinese-datasets-char-based-training-results-streaming-on-zipformer-large-model
|
||||
EOF
|
||||
|
||||
mv -v ctc-epoch-99-avg-1-chunk-16-left-128.fp16.onnx model.fp16.onnx
|
||||
mv -v ctc-epoch-99-avg-1-chunk-16-left-128.int8.onnx model.int8.onnx
|
||||
mv -v ctc-epoch-99-avg-1-chunk-16-left-128.onnx model.onnx
|
||||
|
||||
ls -lh *.onnx
|
||||
|
||||
mkdir test_wavs
|
||||
cd test_wavs
|
||||
curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/0.wav
|
||||
curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/1.wav
|
||||
curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/8k.wav
|
||||
popd
|
||||
|
||||
for w in 0.wav 1.wav 8k.wav; do
|
||||
log "---fp32---"
|
||||
sherpa-onnx \
|
||||
--zipformer2-ctc-model=$repo/model.onnx \
|
||||
--tokens=$repo/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
|
||||
log "---int8---"
|
||||
|
||||
sherpa-onnx \
|
||||
--zipformer2-ctc-model=$repo/model.int8.onnx \
|
||||
--tokens=$repo/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
|
||||
log "---fp16---"
|
||||
|
||||
sherpa-onnx \
|
||||
--zipformer2-ctc-model=$repo/model.fp16.onnx \
|
||||
--tokens=$repo/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
done
|
||||
|
||||
name=(
|
||||
sherpa-onnx-streaming-zipformer-ctc-zh-2025-06-30
|
||||
sherpa-onnx-streaming-zipformer-ctc-zh-int8-2025-06-30
|
||||
sherpa-onnx-streaming-zipformer-ctc-zh-fp16-2025-06-30
|
||||
)
|
||||
for n in ${name[@]}; do
|
||||
url=https://huggingface.co/csukuangfj/$n
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $url
|
||||
dst=$(basename $url)
|
||||
if [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-2025-06-30 ]]; then
|
||||
cp -v $repo/model.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-int8-2025-06-30 ]]; then
|
||||
cp -v $repo/model.int8.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-fp16-2025-06-30 ]]; then
|
||||
cp -v $repo/model.fp16.onnx $dst
|
||||
fi
|
||||
|
||||
cp -v $repo/tokens.txt $dst
|
||||
cp -v $repo/README.md $dst
|
||||
mkdir -p $dst/test_wavs
|
||||
cp -v $repo/test_wavs/*.wav $dst/test_wavs
|
||||
cd $dst
|
||||
git lfs track "*.onnx" "*.wav"
|
||||
ls -lh
|
||||
git status
|
||||
git add .
|
||||
git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
|
||||
|
||||
log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
|
||||
rm -rf .git
|
||||
rm -fv .gitattributes
|
||||
cd ..
|
||||
tar cjfv $dst.tar.bz2 $dst
|
||||
ls -lh *.tar.bz2
|
||||
mv -v $dst.tar.bz2 ../../../
|
||||
done
|
||||
|
||||
rm $repo/*.onnx
|
||||
|
||||
log "----------------------------------------"
|
||||
log "Export streaming ONNX transducer models "
|
||||
log "----------------------------------------"
|
||||
|
||||
./zipformer/export-onnx-streaming.py \
|
||||
--exp-dir $repo \
|
||||
--tokens $repo/tokens.txt \
|
||||
--causal 1 \
|
||||
--avg 1 \
|
||||
--epoch 99 \
|
||||
--use-averaged-model 0 \
|
||||
--chunk-size 16 \
|
||||
--left-context-frames 128 \
|
||||
--use-ctc 0 \
|
||||
\
|
||||
--num-encoder-layers 2,2,4,5,4,2 \
|
||||
--feedforward-dim 768,1024,1536,2048,1536,768 \
|
||||
--encoder-dim 256,384,512,768,512,256 \
|
||||
--encoder-unmasked-dim 192,192,256,320,256,192 \
|
||||
\
|
||||
--fp16 1 \
|
||||
--use-whisper-features 1
|
||||
|
||||
ls -lh $repo
|
||||
pushd $repo
|
||||
for m in encoder decoder joiner; do
|
||||
mv -v $m-epoch-99-avg-1-chunk-16-left-128.onnx $m.onnx
|
||||
mv -v $m-epoch-99-avg-1-chunk-16-left-128.fp16.onnx $m.fp16.onnx
|
||||
mv -v $m-epoch-99-avg-1-chunk-16-left-128.int8.onnx $m.int8.onnx
|
||||
done
|
||||
ls -lh *.onnx
|
||||
popd
|
||||
|
||||
for w in 0.wav 1.wav 8k.wav; do
|
||||
log "---fp32---"
|
||||
sherpa-onnx \
|
||||
--encoder=$repo/encoder.onnx \
|
||||
--decoder=$repo/decoder.onnx \
|
||||
--joiner=$repo/joiner.onnx \
|
||||
--tokens=$repo/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
|
||||
log "---int8---"
|
||||
|
||||
sherpa-onnx \
|
||||
--encoder=$repo/encoder.int8.onnx \
|
||||
--decoder=$repo/decoder.onnx \
|
||||
--joiner=$repo/joiner.int8.onnx \
|
||||
--tokens=$repo/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
|
||||
log "---fp16---"
|
||||
|
||||
sherpa-onnx \
|
||||
--encoder=$repo/encoder.fp16.onnx \
|
||||
--decoder=$repo/decoder.fp16.onnx \
|
||||
--joiner=$repo/joiner.fp16.onnx \
|
||||
--tokens=$repo/tokens.txt \
|
||||
$repo/test_wavs/$w
|
||||
done
|
||||
|
||||
name=(
|
||||
sherpa-onnx-streaming-zipformer-zh-2025-06-30
|
||||
sherpa-onnx-streaming-zipformer-zh-int8-2025-06-30
|
||||
sherpa-onnx-streaming-zipformer-zh-fp16-2025-06-30
|
||||
)
|
||||
for n in ${name[@]}; do
|
||||
url=https://huggingface.co/csukuangfj/$n
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $url
|
||||
dst=$(basename $url)
|
||||
if [[ $n == sherpa-onnx-streaming-zipformer-zh-2025-06-30 ]]; then
|
||||
cp -v $repo/encoder.onnx $dst
|
||||
cp -v $repo/decoder.onnx $dst
|
||||
cp -v $repo/joiner.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-zh-int8-2025-06-30 ]]; then
|
||||
cp -v $repo/encoder.int8.onnx $dst
|
||||
cp -v $repo/decoder.onnx $dst
|
||||
cp -v $repo/joiner.int8.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-zh-fp16-2025-06-30 ]]; then
|
||||
cp -v $repo/encoder.fp16.onnx $dst
|
||||
cp -v $repo/decoder.fp16.onnx $dst
|
||||
cp -v $repo/joiner.fp16.onnx $dst
|
||||
fi
|
||||
|
||||
cp -v $repo/tokens.txt $dst
|
||||
cp -v $repo/README.md $dst
|
||||
mkdir -p $dst/test_wavs
|
||||
cp -v $repo/test_wavs/*.wav $dst/test_wavs
|
||||
cd $dst
|
||||
git lfs track "*.onnx" "*.wav"
|
||||
ls -lh
|
||||
git status
|
||||
git add .
|
||||
git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
|
||||
|
||||
log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
|
||||
rm -rf .git
|
||||
rm -fv .gitattributes
|
||||
cd ..
|
||||
tar cjfv $dst.tar.bz2 $dst
|
||||
ls -lh *.tar.bz2
|
||||
mv -v $dst.tar.bz2 ../../../
|
||||
done
|
||||
}
|
||||
|
||||
function run_yuekai_xl() {
|
||||
repo_url=https://csukuangfj:${HF_TOKEN}@huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-xl
|
||||
log "Downloading pre-trained model from $repo_url"
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
|
||||
repo=$(basename $repo_url)
|
||||
|
||||
pushd $repo
|
||||
git lfs pull --include pretrained.pt
|
||||
git lfs pull --include data/lang_bpe_2000/bpe.model
|
||||
mv pretrained.pt epoch-99.pt
|
||||
ls -lh *.pt
|
||||
popd
|
||||
|
||||
log "----------------------------------------"
|
||||
log "Export streaming ONNX CTC models "
|
||||
log "----------------------------------------"
|
||||
./zipformer/export-onnx-streaming-ctc.py \
|
||||
--exp-dir $repo/ \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
--causal 1 \
|
||||
--avg 1 \
|
||||
--epoch 99 \
|
||||
--use-averaged-model 0 \
|
||||
--chunk-size 16 \
|
||||
--left-context-frames 128 \
|
||||
--use-ctc 1 \
|
||||
\
|
||||
--num-encoder-layers 2,3,5,6,5,3 \
|
||||
--feedforward-dim 1536,2048,3072,4096,3072,1536 \
|
||||
--encoder-dim 512,768,1024,1536,1024,512 \
|
||||
--encoder-unmasked-dim 192,192,256,320,256,192 \
|
||||
--decoder-dim 768 --joiner-dim 768 \
|
||||
--value-head-dim 18 \
|
||||
--query-head-dim 48 \
|
||||
--num-heads 4,4,4,8,4,4 \
|
||||
\
|
||||
--fp16 1 \
|
||||
--use-whisper-features 1 \
|
||||
--use-external-data 1
|
||||
|
||||
mv -v ctc-epoch-99-avg-1-chunk-16-left-128.int8.onnx model.int8.onnx
|
||||
mv -v ctc-epoch-99-avg-1-chunk-16-left-128.fp16.onnx model.fp16.onnx
|
||||
|
||||
ls -lh *.onnx
|
||||
|
||||
mkdir test_wavs
|
||||
pushd test_wavs
|
||||
curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/0.wav
|
||||
curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/1.wav
|
||||
curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/8k.wav
|
||||
popd
|
||||
|
||||
for w in 0.wav 1.wav 8k.wav; do
|
||||
log "---int8---"
|
||||
|
||||
sherpa-onnx \
|
||||
--zipformer2-ctc-model=./model.int8.onnx \
|
||||
--tokens=$repo/data/lang_bpe_2000/tokens.txt \
|
||||
test_wavs/$w
|
||||
|
||||
log "---fp16---"
|
||||
|
||||
sherpa-onnx \
|
||||
--zipformer2-ctc-model=./model.fp16.onnx \
|
||||
--tokens=$repo/data/lang_bpe_2000/tokens.txt \
|
||||
test_wavs/$w
|
||||
done
|
||||
|
||||
pushd $repo
|
||||
cat >README.md <<EOF
|
||||
# Introduction
|
||||
|
||||
This model is converted
|
||||
from
|
||||
https://huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-xl
|
||||
|
||||
The training code can be found at
|
||||
https://github.com/k2-fsa/icefall/blob/master/egs/multi_zh-hans/ASR/RESULTS.md#multi-chinese-datasets-char-based-training-results-streaming-on-zipformer-xl-model
|
||||
EOF
|
||||
popd
|
||||
|
||||
name=(
|
||||
sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-int8-2025-06-30
|
||||
sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-fp16-2025-06-30
|
||||
)
|
||||
|
||||
for n in ${name[@]}; do
|
||||
url=https://huggingface.co/csukuangfj/$n
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $url
|
||||
dst=$(basename $url)
|
||||
if [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-fp16-2025-06-30 ]]; then
|
||||
cp -v model.fp16.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-int8-2025-06-30 ]]; then
|
||||
cp -v model.int8.onnx $dst
|
||||
fi
|
||||
|
||||
cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
|
||||
cp -v $repo/data/lang_bpe_2000/bpe.model $dst
|
||||
cp -v $repo/README.md $dst
|
||||
mkdir -p $dst/test_wavs
|
||||
cp -v ./test_wavs/*.wav $dst/test_wavs
|
||||
cd $dst
|
||||
git lfs track "*.onnx" "*.wav" "bpe.model"
|
||||
ls -lh
|
||||
git status
|
||||
git add .
|
||||
git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
|
||||
|
||||
log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
|
||||
rm -rf .git
|
||||
rm -fv .gitattributes
|
||||
cd ..
|
||||
|
||||
ls -lh $dst
|
||||
tar cjfv $dst.tar.bz2 $dst
|
||||
ls -lh *.tar.bz2
|
||||
mv -v $dst.tar.bz2 ../../../
|
||||
done
|
||||
|
||||
rm -fv *.onnx *.weights
|
||||
|
||||
log "----------------------------------------"
|
||||
log "Export streaming ONNX transducer models "
|
||||
log "----------------------------------------"
|
||||
|
||||
./zipformer/export-onnx-streaming.py \
|
||||
--exp-dir $repo/ \
|
||||
--tokens $repo/data/lang_bpe_2000/tokens.txt \
|
||||
--causal 1 \
|
||||
--avg 1 \
|
||||
--epoch 99 \
|
||||
--use-averaged-model 0 \
|
||||
--chunk-size 16 \
|
||||
--left-context-frames 128 \
|
||||
--use-ctc 0 \
|
||||
\
|
||||
--num-encoder-layers 2,3,5,6,5,3 \
|
||||
--feedforward-dim 1536,2048,3072,4096,3072,1536 \
|
||||
--encoder-dim 512,768,1024,1536,1024,512 \
|
||||
--encoder-unmasked-dim 192,192,256,320,256,192 \
|
||||
--decoder-dim 768 --joiner-dim 768 \
|
||||
--value-head-dim 18 \
|
||||
--query-head-dim 48 \
|
||||
--num-heads 4,4,4,8,4,4 \
|
||||
\
|
||||
--fp16 1 \
|
||||
--use-whisper-features 1 \
|
||||
--use-external-data 1
|
||||
|
||||
ls -lh *.onnx
|
||||
ls -lh *.weights
|
||||
|
||||
mv encoder-epoch-99-avg-1-chunk-16-left-128.fp16.onnx encoder.fp16.onnx
|
||||
mv encoder-epoch-99-avg-1-chunk-16-left-128.int8.onnx encoder.int8.onnx
|
||||
|
||||
mv $repo/decoder-epoch-99-avg-1-chunk-16-left-128.onnx decoder.onnx
|
||||
mv $repo/decoder-epoch-99-avg-1-chunk-16-left-128.fp16.onnx decoder.fp16.onnx
|
||||
|
||||
mv $repo/joiner-epoch-99-avg-1-chunk-16-left-128.int8.onnx joiner.int8.onnx
|
||||
mv $repo/joiner-epoch-99-avg-1-chunk-16-left-128.fp16.onnx joiner.fp16.onnx
|
||||
|
||||
name=(
|
||||
sherpa-onnx-streaming-zipformer-zh-xlarge-int8-2025-06-30
|
||||
sherpa-onnx-streaming-zipformer-zh-xlarge-fp16-2025-06-30
|
||||
)
|
||||
|
||||
for n in ${name[@]}; do
|
||||
url=https://huggingface.co/csukuangfj/$n
|
||||
GIT_LFS_SKIP_SMUDGE=1 git clone $url
|
||||
dst=$(basename $url)
|
||||
if [[ $n == sherpa-onnx-streaming-zipformer-zh-xlarge-fp16-2025-06-30 ]]; then
|
||||
cp -v encoder.fp16.onnx $dst
|
||||
cp -v decoder.fp16.onnx $dst
|
||||
cp -v joiner.fp16.onnx $dst
|
||||
elif [[ $n == sherpa-onnx-streaming-zipformer-zh-xlarge-int8-2025-06-30 ]]; then
|
||||
cp -v encoder.int8.onnx $dst
|
||||
cp -v decoder.onnx $dst
|
||||
cp -v joiner.int8.onnx $dst
|
||||
fi
|
||||
|
||||
cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
|
||||
cp -v $repo/data/lang_bpe_2000/bpe.model $dst
|
||||
cp -v $repo/README.md $dst
|
||||
mkdir -p $dst/test_wavs
|
||||
cp -v ./test_wavs/*.wav $dst/test_wavs
|
||||
cd $dst
|
||||
git lfs track "*.onnx" "*.wav" "bpe.model"
|
||||
ls -lh
|
||||
git status
|
||||
git add .
|
||||
git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
|
||||
|
||||
log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
|
||||
rm -rf .git
|
||||
rm -fv .gitattributes
|
||||
cd ..
|
||||
|
||||
ls -lh $dst
|
||||
tar cjfv $dst.tar.bz2 $dst
|
||||
ls -lh *.tar.bz2
|
||||
mv -v $dst.tar.bz2 ../../../
|
||||
done
|
||||
|
||||
rm -fv *.onnx *.weights
|
||||
}
|
||||
|
||||
# run_yuekai_large
|
||||
# run_yuekai_xl
|
||||
# run_2023_9_2
|
||||
run_2023_11_05_streaming
|
||||
# run_2023_12_12_streaming
|
||||
85
.github/workflows/multi-zh-hans.yml
vendored
85
.github/workflows/multi-zh-hans.yml
vendored
@ -1,4 +1,4 @@
|
||||
name: run-multi-zh-hans
|
||||
name: multi-zh-hans
|
||||
|
||||
on:
|
||||
push:
|
||||
@ -8,65 +8,72 @@ on:
|
||||
workflow_dispatch:
|
||||
|
||||
concurrency:
|
||||
group: run-multi-zh-hans-${{ github.ref }}
|
||||
group: multi-zh-hans-${{ github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
jobs:
|
||||
generate_build_matrix:
|
||||
if: github.repository_owner == 'csukuangfj' || github.repository_owner == 'k2-fsa'
|
||||
# see https://github.com/pytorch/pytorch/pull/50633
|
||||
runs-on: ubuntu-latest
|
||||
outputs:
|
||||
matrix: ${{ steps.set-matrix.outputs.matrix }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
- name: Generating build matrix
|
||||
id: set-matrix
|
||||
run: |
|
||||
# outputting for debugging purposes
|
||||
python ./.github/scripts/docker/generate_build_matrix.py --torch-version "2.7.0" --python-version "3.11"
|
||||
MATRIX=$(python ./.github/scripts/docker/generate_build_matrix.py --torch-version "2.7.0" --python-version "3.11")
|
||||
echo "::set-output name=matrix::${MATRIX}"
|
||||
multi-zh-hans:
|
||||
runs-on: ${{ matrix.os }}
|
||||
needs: generate_build_matrix
|
||||
name: py${{ matrix.python-version }} torch${{ matrix.torch-version }} v${{ matrix.version }}
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
os: [ubuntu-latest]
|
||||
python-version: [3.8]
|
||||
${{ fromJson(needs.generate_build_matrix.outputs.matrix) }}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Setup Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
cache: 'pip'
|
||||
cache-dependency-path: '**/requirements-ci.txt'
|
||||
|
||||
- name: Install Python dependencies
|
||||
run: |
|
||||
grep -v '^#' ./requirements-ci.txt | xargs -n 1 -L 1 pip install
|
||||
pip uninstall -y protobuf
|
||||
pip install --no-binary protobuf protobuf==3.20.*
|
||||
|
||||
- name: Cache kaldifeat
|
||||
id: my-cache
|
||||
uses: actions/cache@v2
|
||||
with:
|
||||
path: |
|
||||
~/tmp/kaldifeat
|
||||
key: cache-tmp-${{ matrix.python-version }}-2023-05-22
|
||||
|
||||
- name: Install kaldifeat
|
||||
if: steps.my-cache.outputs.cache-hit != 'true'
|
||||
- name: Free space
|
||||
shell: bash
|
||||
run: |
|
||||
.github/scripts/install-kaldifeat.sh
|
||||
df -h
|
||||
rm -rf /opt/hostedtoolcache
|
||||
df -h
|
||||
echo "pwd: $PWD"
|
||||
echo "github.workspace ${{ github.workspace }}"
|
||||
|
||||
- name: export-model
|
||||
- name: Test with multi_zh-hans
|
||||
uses: addnab/docker-run-action@v3
|
||||
with:
|
||||
image: ghcr.io/${{ github.repository_owner }}/icefall:cpu-py${{ matrix.python-version }}-torch${{ matrix.torch-version }}-v${{ matrix.version }}
|
||||
options: |
|
||||
--volume ${{ github.workspace }}/:/icefall
|
||||
shell: bash
|
||||
run: |
|
||||
export PYTHONPATH=/icefall:$PYTHONPATH
|
||||
export HF_TOKEN=${{ secrets.HF_TOKEN }}
|
||||
cd /icefall
|
||||
git config --global --add safe.directory /icefall
|
||||
|
||||
.github/scripts/multi_zh-hans/ASR/run.sh
|
||||
|
||||
- name: Show models
|
||||
shell: bash
|
||||
env:
|
||||
HF_TOKEN: ${{ secrets.HF_TOKEN }}
|
||||
run: |
|
||||
sudo apt-get -qq install git-lfs tree
|
||||
export PYTHONPATH=$PWD:$PYTHONPATH
|
||||
export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
|
||||
export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
|
||||
|
||||
.github/scripts/multi-zh-hans.sh
|
||||
ls -lh
|
||||
ls -lh *.tar.bz2
|
||||
|
||||
- name: upload model to https://github.com/k2-fsa/sherpa-onnx
|
||||
uses: svenstaro/upload-release-action@v2
|
||||
|
||||
@ -153,6 +153,13 @@ def get_parser():
|
||||
help="The context size in the decoder. 1 means bigram; 2 means tri-gram",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--fp16",
|
||||
type=str2bool,
|
||||
default=False,
|
||||
help="Whether to export models in fp16",
|
||||
)
|
||||
|
||||
add_model_arguments(parser)
|
||||
|
||||
return parser
|
||||
@ -176,6 +183,15 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
|
||||
onnx.save(model, filename)
|
||||
|
||||
|
||||
def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
|
||||
import onnxmltools
|
||||
from onnxmltools.utils.float16_converter import convert_float_to_float16
|
||||
|
||||
onnx_fp32_model = onnxmltools.utils.load_model(onnx_fp32_path)
|
||||
onnx_fp16_model = convert_float_to_float16(onnx_fp32_model, keep_io_types=True)
|
||||
onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
|
||||
|
||||
|
||||
class OnnxModel(nn.Module):
|
||||
"""A wrapper for encoder_embed, Zipformer, and ctc_output layer"""
|
||||
|
||||
@ -407,7 +423,7 @@ def main():
|
||||
opset_version = 13
|
||||
|
||||
logging.info("Exporting ctc model")
|
||||
filename = params.exp_dir / f"model.onnx"
|
||||
filename = params.exp_dir / "model.onnx"
|
||||
export_ctc_model_onnx(
|
||||
model,
|
||||
filename,
|
||||
@ -420,7 +436,7 @@ def main():
|
||||
|
||||
logging.info("Generate int8 quantization models")
|
||||
|
||||
filename_int8 = params.exp_dir / f"model.int8.onnx"
|
||||
filename_int8 = params.exp_dir / "model.int8.onnx"
|
||||
quantize_dynamic(
|
||||
model_input=filename,
|
||||
model_output=filename_int8,
|
||||
@ -428,6 +444,10 @@ def main():
|
||||
weight_type=QuantType.QInt8,
|
||||
)
|
||||
|
||||
if params.fp16:
|
||||
filename_fp16 = params.exp_dir / "model.fp16.onnx"
|
||||
export_onnx_fp16(filename, filename_fp16)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
|
||||
|
||||
@ -136,12 +136,35 @@ def get_parser():
|
||||
help="The context size in the decoder. 1 means bigram; 2 means tri-gram",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--use-whisper-features",
|
||||
type=str2bool,
|
||||
default=False,
|
||||
help="True to use whisper features. Must match the one used in training",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--fp16",
|
||||
type=str2bool,
|
||||
default=False,
|
||||
help="Whether to export models in fp16",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--use-external-data",
|
||||
type=str2bool,
|
||||
default=False,
|
||||
help="Set it to true for model file size > 2GB",
|
||||
)
|
||||
|
||||
add_model_arguments(parser)
|
||||
|
||||
return parser
|
||||
|
||||
|
||||
def add_meta_data(filename: str, meta_data: Dict[str, str]):
|
||||
def add_meta_data(
|
||||
filename: str, meta_data: Dict[str, str], use_external_data: bool = False
|
||||
):
|
||||
"""Add meta data to an ONNX model. It is changed in-place.
|
||||
|
||||
Args:
|
||||
@ -150,13 +173,46 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
|
||||
meta_data:
|
||||
Key-value pairs.
|
||||
"""
|
||||
filename = str(filename)
|
||||
|
||||
model = onnx.load(filename)
|
||||
for key, value in meta_data.items():
|
||||
meta = model.metadata_props.add()
|
||||
meta.key = key
|
||||
meta.value = value
|
||||
|
||||
onnx.save(model, filename)
|
||||
if use_external_data:
|
||||
# For models file size > 2GB
|
||||
external_filename = Path(filename).stem
|
||||
|
||||
onnx.save(
|
||||
model,
|
||||
filename,
|
||||
save_as_external_data=True,
|
||||
all_tensors_to_one_file=True,
|
||||
location=external_filename + ".weights",
|
||||
)
|
||||
else:
|
||||
onnx.save(model, filename)
|
||||
|
||||
|
||||
def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
|
||||
import onnxmltools
|
||||
from onnxmltools.utils.float16_converter import convert_float_to_float16
|
||||
|
||||
onnx_fp32_model = onnxmltools.utils.load_model(onnx_fp32_path)
|
||||
onnx_fp16_model = convert_float_to_float16(onnx_fp32_model, keep_io_types=True)
|
||||
onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
|
||||
|
||||
|
||||
def export_onnx_fp16_large_2gb(onnx_fp32_path, onnx_fp16_path):
|
||||
import onnxmltools
|
||||
from onnxmltools.utils.float16_converter import convert_float_to_float16_model_path
|
||||
|
||||
onnx_fp16_model = convert_float_to_float16_model_path(
|
||||
onnx_fp32_path, keep_io_types=True
|
||||
)
|
||||
onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
|
||||
|
||||
|
||||
class OnnxModel(nn.Module):
|
||||
@ -270,6 +326,8 @@ def export_streaming_ctc_model_onnx(
|
||||
model: OnnxModel,
|
||||
encoder_filename: str,
|
||||
opset_version: int = 11,
|
||||
use_whisper_features: bool = False,
|
||||
use_external_data: bool = False,
|
||||
) -> None:
|
||||
model.encoder.__class__.forward = model.encoder.__class__.streaming_forward
|
||||
|
||||
@ -367,6 +425,10 @@ def export_streaming_ctc_model_onnx(
|
||||
"value_head_dims": value_head_dims,
|
||||
"num_heads": num_heads,
|
||||
}
|
||||
|
||||
if use_whisper_features:
|
||||
meta_data["feature"] = "whisper"
|
||||
|
||||
logging.info(f"meta_data: {meta_data}")
|
||||
|
||||
for i in range(len(init_state[:-2]) // 6):
|
||||
@ -411,7 +473,11 @@ def export_streaming_ctc_model_onnx(
|
||||
},
|
||||
)
|
||||
|
||||
add_meta_data(filename=encoder_filename, meta_data=meta_data)
|
||||
add_meta_data(
|
||||
filename=encoder_filename,
|
||||
meta_data=meta_data,
|
||||
use_external_data=use_external_data,
|
||||
)
|
||||
|
||||
|
||||
@torch.no_grad()
|
||||
@ -542,11 +608,18 @@ def main():
|
||||
opset_version = 13
|
||||
|
||||
logging.info("Exporting model")
|
||||
model_filename = params.exp_dir / f"ctc-{suffix}.onnx"
|
||||
|
||||
if params.use_external_data:
|
||||
model_filename = f"ctc-{suffix}.onnx"
|
||||
else:
|
||||
model_filename = params.exp_dir / f"ctc-{suffix}.onnx"
|
||||
|
||||
export_streaming_ctc_model_onnx(
|
||||
model,
|
||||
model_filename,
|
||||
str(model_filename),
|
||||
opset_version=opset_version,
|
||||
use_whisper_features=params.use_whisper_features,
|
||||
use_external_data=params.use_external_data,
|
||||
)
|
||||
logging.info(f"Exported model to {model_filename}")
|
||||
|
||||
@ -555,7 +628,11 @@ def main():
|
||||
|
||||
logging.info("Generate int8 quantization models")
|
||||
|
||||
model_filename_int8 = params.exp_dir / f"ctc-{suffix}.int8.onnx"
|
||||
if params.use_external_data:
|
||||
model_filename_int8 = f"ctc-{suffix}.int8.onnx"
|
||||
else:
|
||||
model_filename_int8 = params.exp_dir / f"ctc-{suffix}.int8.onnx"
|
||||
|
||||
quantize_dynamic(
|
||||
model_input=model_filename,
|
||||
model_output=model_filename_int8,
|
||||
@ -563,6 +640,14 @@ def main():
|
||||
weight_type=QuantType.QInt8,
|
||||
)
|
||||
|
||||
if params.fp16:
|
||||
if params.use_external_data:
|
||||
model_filename_fp16 = f"ctc-{suffix}.fp16.onnx"
|
||||
export_onnx_fp16_large_2gb(model_filename, model_filename_fp16)
|
||||
else:
|
||||
model_filename_fp16 = params.exp_dir / f"ctc-{suffix}.fp16.onnx"
|
||||
export_onnx_fp16(model_filename, model_filename_fp16)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
|
||||
|
||||
@ -162,12 +162,47 @@ def get_parser():
|
||||
help="Whether to export models in fp16",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--use-whisper-features",
|
||||
type=str2bool,
|
||||
default=False,
|
||||
help="True to use whisper features. Must match the one used in training",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--use-external-data",
|
||||
type=str2bool,
|
||||
default=False,
|
||||
help="Set it to true for model file size > 2GB",
|
||||
)
|
||||
|
||||
add_model_arguments(parser)
|
||||
|
||||
return parser
|
||||
|
||||
|
||||
def add_meta_data(filename: str, meta_data: Dict[str, str]):
|
||||
def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
|
||||
import onnxmltools
|
||||
from onnxmltools.utils.float16_converter import convert_float_to_float16
|
||||
|
||||
onnx_fp32_model = onnxmltools.utils.load_model(onnx_fp32_path)
|
||||
onnx_fp16_model = convert_float_to_float16(onnx_fp32_model, keep_io_types=True)
|
||||
onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
|
||||
|
||||
|
||||
def export_onnx_fp16_large_2gb(onnx_fp32_path, onnx_fp16_path):
|
||||
import onnxmltools
|
||||
from onnxmltools.utils.float16_converter import convert_float_to_float16_model_path
|
||||
|
||||
onnx_fp16_model = convert_float_to_float16_model_path(
|
||||
onnx_fp32_path, keep_io_types=True
|
||||
)
|
||||
onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
|
||||
|
||||
|
||||
def add_meta_data(
|
||||
filename: str, meta_data: Dict[str, str], use_external_data: bool = False
|
||||
):
|
||||
"""Add meta data to an ONNX model. It is changed in-place.
|
||||
|
||||
Args:
|
||||
@ -182,7 +217,19 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
|
||||
meta.key = key
|
||||
meta.value = value
|
||||
|
||||
onnx.save(model, filename)
|
||||
if use_external_data:
|
||||
# For models file size > 2GB
|
||||
external_filename = Path(filename).stem
|
||||
|
||||
onnx.save(
|
||||
model,
|
||||
filename,
|
||||
save_as_external_data=True,
|
||||
all_tensors_to_one_file=True,
|
||||
location=external_filename + ".weights",
|
||||
)
|
||||
else:
|
||||
onnx.save(model, filename)
|
||||
|
||||
|
||||
class OnnxEncoder(nn.Module):
|
||||
@ -342,6 +389,8 @@ def export_encoder_model_onnx(
|
||||
encoder_filename: str,
|
||||
opset_version: int = 11,
|
||||
feature_dim: int = 80,
|
||||
use_whisper_features: bool = False,
|
||||
use_external_data: bool = False,
|
||||
) -> None:
|
||||
encoder_model.encoder.__class__.forward = (
|
||||
encoder_model.encoder.__class__.streaming_forward
|
||||
@ -441,6 +490,9 @@ def export_encoder_model_onnx(
|
||||
"value_head_dims": value_head_dims,
|
||||
"num_heads": num_heads,
|
||||
}
|
||||
if use_whisper_features:
|
||||
meta_data["feature"] = "whisper"
|
||||
|
||||
logging.info(f"meta_data: {meta_data}")
|
||||
|
||||
for i in range(len(init_state[:-2]) // 6):
|
||||
@ -485,7 +537,11 @@ def export_encoder_model_onnx(
|
||||
},
|
||||
)
|
||||
|
||||
add_meta_data(filename=encoder_filename, meta_data=meta_data)
|
||||
add_meta_data(
|
||||
filename=encoder_filename,
|
||||
meta_data=meta_data,
|
||||
use_external_data=use_external_data,
|
||||
)
|
||||
|
||||
|
||||
def export_decoder_model_onnx(
|
||||
@ -728,12 +784,17 @@ def main():
|
||||
opset_version = 13
|
||||
|
||||
logging.info("Exporting encoder")
|
||||
encoder_filename = params.exp_dir / f"encoder-{suffix}.onnx"
|
||||
if params.use_external_data:
|
||||
encoder_filename = f"encoder-{suffix}.onnx"
|
||||
else:
|
||||
encoder_filename = params.exp_dir / f"encoder-{suffix}.onnx"
|
||||
export_encoder_model_onnx(
|
||||
encoder,
|
||||
encoder_filename,
|
||||
str(encoder_filename),
|
||||
opset_version=opset_version,
|
||||
feature_dim=params.feature_dim,
|
||||
use_whisper_features=params.use_whisper_features,
|
||||
use_external_data=params.use_external_data,
|
||||
)
|
||||
logging.info(f"Exported encoder to {encoder_filename}")
|
||||
|
||||
@ -756,31 +817,31 @@ def main():
|
||||
logging.info(f"Exported joiner to {joiner_filename}")
|
||||
|
||||
if params.fp16:
|
||||
from onnxconverter_common import float16
|
||||
|
||||
logging.info("Generate fp16 models")
|
||||
|
||||
encoder = onnx.load(encoder_filename)
|
||||
encoder_fp16 = float16.convert_float_to_float16(encoder, keep_io_types=True)
|
||||
encoder_filename_fp16 = params.exp_dir / f"encoder-{suffix}.fp16.onnx"
|
||||
onnx.save(encoder_fp16, encoder_filename_fp16)
|
||||
if params.use_external_data:
|
||||
encoder_filename_fp16 = f"encoder-{suffix}.fp16.onnx"
|
||||
export_onnx_fp16_large_2gb(encoder_filename, encoder_filename_fp16)
|
||||
else:
|
||||
encoder_filename_fp16 = params.exp_dir / f"encoder-{suffix}.fp16.onnx"
|
||||
export_onnx_fp16(encoder_filename, encoder_filename_fp16)
|
||||
|
||||
decoder = onnx.load(decoder_filename)
|
||||
decoder_fp16 = float16.convert_float_to_float16(decoder, keep_io_types=True)
|
||||
decoder_filename_fp16 = params.exp_dir / f"decoder-{suffix}.fp16.onnx"
|
||||
onnx.save(decoder_fp16, decoder_filename_fp16)
|
||||
export_onnx_fp16(decoder_filename, decoder_filename_fp16)
|
||||
|
||||
joiner = onnx.load(joiner_filename)
|
||||
joiner_fp16 = float16.convert_float_to_float16(joiner, keep_io_types=True)
|
||||
joiner_filename_fp16 = params.exp_dir / f"joiner-{suffix}.fp16.onnx"
|
||||
onnx.save(joiner_fp16, joiner_filename_fp16)
|
||||
export_onnx_fp16(joiner_filename, joiner_filename_fp16)
|
||||
|
||||
# Generate int8 quantization models
|
||||
# See https://onnxruntime.ai/docs/performance/model-optimizations/quantization.html#data-type-selection
|
||||
|
||||
logging.info("Generate int8 quantization models")
|
||||
|
||||
encoder_filename_int8 = params.exp_dir / f"encoder-{suffix}.int8.onnx"
|
||||
if params.use_external_data:
|
||||
encoder_filename_int8 = f"encoder-{suffix}.int8.onnx"
|
||||
else:
|
||||
encoder_filename_int8 = params.exp_dir / f"encoder-{suffix}.int8.onnx"
|
||||
|
||||
quantize_dynamic(
|
||||
model_input=encoder_filename,
|
||||
model_output=encoder_filename_int8,
|
||||
|
||||
@ -70,7 +70,6 @@ import onnx
|
||||
import torch
|
||||
import torch.nn as nn
|
||||
from decoder import Decoder
|
||||
from onnxconverter_common import float16
|
||||
from onnxruntime.quantization import QuantType, quantize_dynamic
|
||||
from scaling_converter import convert_scaled_to_non_scaled
|
||||
from train import add_model_arguments, get_model, get_params
|
||||
@ -182,6 +181,15 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
|
||||
onnx.save(model, filename)
|
||||
|
||||
|
||||
def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
|
||||
import onnxmltools
|
||||
from onnxmltools.utils.float16_converter import convert_float_to_float16
|
||||
|
||||
onnx_fp32_model = onnxmltools.utils.load_model(onnx_fp32_path)
|
||||
onnx_fp16_model = convert_float_to_float16(onnx_fp32_model, keep_io_types=True)
|
||||
onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
|
||||
|
||||
|
||||
class OnnxEncoder(nn.Module):
|
||||
"""A wrapper for Zipformer and the encoder_proj from the joiner"""
|
||||
|
||||
@ -595,20 +603,14 @@ def main():
|
||||
if params.fp16:
|
||||
logging.info("Generate fp16 models")
|
||||
|
||||
encoder = onnx.load(encoder_filename)
|
||||
encoder_fp16 = float16.convert_float_to_float16(encoder, keep_io_types=True)
|
||||
encoder_filename_fp16 = params.exp_dir / f"encoder-{suffix}.fp16.onnx"
|
||||
onnx.save(encoder_fp16, encoder_filename_fp16)
|
||||
export_onnx_fp16(encoder_filename, encoder_filename_fp16)
|
||||
|
||||
decoder = onnx.load(decoder_filename)
|
||||
decoder_fp16 = float16.convert_float_to_float16(decoder, keep_io_types=True)
|
||||
decoder_filename_fp16 = params.exp_dir / f"decoder-{suffix}.fp16.onnx"
|
||||
onnx.save(decoder_fp16, decoder_filename_fp16)
|
||||
export_onnx_fp16(decoder_filename, decoder_filename_fp16)
|
||||
|
||||
joiner = onnx.load(joiner_filename)
|
||||
joiner_fp16 = float16.convert_float_to_float16(joiner, keep_io_types=True)
|
||||
joiner_filename_fp16 = params.exp_dir / f"joiner-{suffix}.fp16.onnx"
|
||||
onnx.save(joiner_fp16, joiner_filename_fp16)
|
||||
export_onnx_fp16(joiner_filename, joiner_filename_fp16)
|
||||
|
||||
# Generate int8 quantization models
|
||||
# See https://onnxruntime.ai/docs/performance/model-optimizations/quantization.html#data-type-selection
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user