From 012903e42ec890ab5c50137beb365c3d94e731d1 Mon Sep 17 00:00:00 2001
From: nichongjia-2007 <nichongjia@gmail.com>
Date: 星期五, 30 六月 2023 11:21:28 +0800
Subject: [PATCH] Merge branch 'main' of https://github.com/alibaba-damo-academy/FunASR
---
funasr/export/export_model.py | 65 ++++++++++++++++++--------------
1 files changed, 36 insertions(+), 29 deletions(-)
diff --git a/funasr/export/export_model.py b/funasr/export/export_model.py
index c02c299..f31f960 100644
--- a/funasr/export/export_model.py
+++ b/funasr/export/export_model.py
@@ -1,7 +1,6 @@
import json
from typing import Union, Dict
from pathlib import Path
-from typeguard import check_argument_types
import os
import logging
@@ -10,7 +9,7 @@
from funasr.export.models import get_model
import numpy as np
import random
-from funasr.utils.types import str2bool
+from funasr.utils.types import str2bool, str2triple_str
# torch_version = float(".".join(torch.__version__.split(".")[:2]))
# assert torch_version > 1.9
@@ -24,8 +23,8 @@
fallback_num: int = 0,
audio_in: str = None,
calib_num: int = 200,
+ model_revision: str = None,
):
- assert check_argument_types()
self.set_all_random_seed(0)
self.cache_dir = cache_dir
@@ -41,6 +40,7 @@
self.frontend = None
self.audio_in = audio_in
self.calib_num = calib_num
+ self.model_revision = model_revision
def _export(
@@ -171,7 +171,7 @@
model_dir = tag_name
if model_dir.startswith('damo'):
from modelscope.hub.snapshot_download import snapshot_download
- model_dir = snapshot_download(model_dir, cache_dir=self.cache_dir)
+ model_dir = snapshot_download(model_dir, cache_dir=self.cache_dir, revision=self.model_revision)
self.cache_dir = model_dir
if mode is None:
@@ -192,6 +192,7 @@
config, model_file, cmvn_file, 'cpu'
)
self.frontend = model.frontend
+ self.export_config["feats_dim"] = 560
elif mode.startswith('offline'):
from funasr.tasks.vad import VADTask
config = os.path.join(model_dir, 'vad.yaml')
@@ -229,40 +230,42 @@
# model_script = torch.jit.script(model)
model_script = model #torch.jit.trace(model)
model_path = os.path.join(path, f'{model.model_name}.onnx')
-
- torch.onnx.export(
- model_script,
- dummy_input,
- model_path,
- verbose=verbose,
- opset_version=14,
- input_names=model.get_input_names(),
- output_names=model.get_output_names(),
- dynamic_axes=model.get_dynamic_axes()
- )
+ if not os.path.exists(model_path):
+ torch.onnx.export(
+ model_script,
+ dummy_input,
+ model_path,
+ verbose=verbose,
+ opset_version=14,
+ input_names=model.get_input_names(),
+ output_names=model.get_output_names(),
+ dynamic_axes=model.get_dynamic_axes()
+ )
if self.quant:
from onnxruntime.quantization import QuantType, quantize_dynamic
import onnx
quant_model_path = os.path.join(path, f'{model.model_name}_quant.onnx')
- onnx_model = onnx.load(model_path)
- nodes = [n.name for n in onnx_model.graph.node]
- nodes_to_exclude = [m for m in nodes if 'output' in m]
- quantize_dynamic(
- model_input=model_path,
- model_output=quant_model_path,
- op_types_to_quantize=['MatMul'],
- per_channel=True,
- reduce_range=False,
- weight_type=QuantType.QUInt8,
- nodes_to_exclude=nodes_to_exclude,
- )
+ if not os.path.exists(quant_model_path):
+ onnx_model = onnx.load(model_path)
+ nodes = [n.name for n in onnx_model.graph.node]
+ nodes_to_exclude = [m for m in nodes if 'output' in m]
+ quantize_dynamic(
+ model_input=model_path,
+ model_output=quant_model_path,
+ op_types_to_quantize=['MatMul'],
+ per_channel=True,
+ reduce_range=False,
+ weight_type=QuantType.QUInt8,
+ nodes_to_exclude=nodes_to_exclude,
+ )
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser()
- parser.add_argument('--model-name', type=str, required=True)
+ # parser.add_argument('--model-name', type=str, required=True)
+ parser.add_argument('--model-name', type=str, action="append", required=True, default=[])
parser.add_argument('--export-dir', type=str, required=True)
parser.add_argument('--type', type=str, default='onnx', help='["onnx", "torch"]')
parser.add_argument('--device', type=str, default='cpu', help='["cpu", "cuda"]')
@@ -270,6 +273,7 @@
parser.add_argument('--fallback-num', type=int, default=0, help='amp fallback number')
parser.add_argument('--audio_in', type=str, default=None, help='["wav", "wav.scp"]')
parser.add_argument('--calib_num', type=int, default=200, help='calib max num')
+ parser.add_argument('--model_revision', type=str, default=None, help='model_revision')
args = parser.parse_args()
export_model = ModelExport(
@@ -280,5 +284,8 @@
fallback_num=args.fallback_num,
audio_in=args.audio_in,
calib_num=args.calib_num,
+ model_revision=args.model_revision,
)
- export_model.export(args.model_name)
+ for model_name in args.model_name:
+ print("export model: {}".format(model_name))
+ export_model.export(model_name)
--
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