From 548153260b27b28bfdc880472e382e3418a05be3 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 02 三月 2023 20:20:44 +0800
Subject: [PATCH] torchscripts
---
funasr/export/test_torchscripts.py | 2 +-
funasr/runtime/python/libtorch/setup.py | 4 ++--
funasr/runtime/python/libtorch/torch_paraformer/paraformer_bin.py | 11 ++++++-----
3 files changed, 9 insertions(+), 8 deletions(-)
diff --git a/funasr/export/test_torchscripts.py b/funasr/export/test_torchscripts.py
index 11be763..9afec74 100644
--- a/funasr/export/test_torchscripts.py
+++ b/funasr/export/test_torchscripts.py
@@ -2,7 +2,7 @@
import numpy as np
if __name__ == '__main__':
- onnx_path = "/mnt/workspace/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/model.torchscripts"
+ onnx_path = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/model.torchscripts"
loaded = torch.jit.load(onnx_path)
x = torch.rand([2, 21, 560])
diff --git a/funasr/runtime/python/libtorch/setup.py b/funasr/runtime/python/libtorch/setup.py
index 99d8b52..0f9e40d 100644
--- a/funasr/runtime/python/libtorch/setup.py
+++ b/funasr/runtime/python/libtorch/setup.py
@@ -1,7 +1,7 @@
# -*- encoding: utf-8 -*-
from pathlib import Path
import setuptools
-
+from setuptools import find_packages
def get_readme():
root_dir = Path(__file__).resolve().parent
@@ -29,7 +29,7 @@
"scipy", "numpy>=1.19.3",
"typeguard", "kaldi-native-fbank",
"PyYAML>=5.1.2"],
- packages=['torch_paraformer'],
+ packages=find_packages(include=["torch_paraformer*"]),
keywords=[
'funasr,paraformer'
],
diff --git a/funasr/runtime/python/libtorch/torch_paraformer/paraformer_bin.py b/funasr/runtime/python/libtorch/torch_paraformer/paraformer_bin.py
index ca90558..159e394 100644
--- a/funasr/runtime/python/libtorch/torch_paraformer/paraformer_bin.py
+++ b/funasr/runtime/python/libtorch/torch_paraformer/paraformer_bin.py
@@ -27,7 +27,7 @@
if not Path(model_dir).exists():
raise FileNotFoundError(f'{model_dir} does not exist.')
- model_file = os.path.join(model_dir, 'model.onnx')
+ model_file = os.path.join(model_dir, 'model.torchscripts')
config_file = os.path.join(model_dir, 'config.yaml')
cmvn_file = os.path.join(model_dir, 'am.mvn')
config = read_yaml(config_file)
@@ -52,9 +52,8 @@
feats, feats_len = self.extract_feat(waveform_list[beg_idx:end_idx])
try:
- outputs = self.infer(feats, feats_len)
- outs = outputs[0], outputs[1]
- am_scores, valid_token_lens = outs[0], outs[1]
+ outputs = self.ort_infer(feats, feats_len)
+ am_scores, valid_token_lens = outputs[0], outputs[1]
if len(outputs) == 4:
# for BiCifParaformer Inference
us_alphas, us_cif_peak = outputs[2], outputs[3]
@@ -65,7 +64,7 @@
logging.warning("input wav is silence or noise")
preds = ['']
else:
- am_scores, valid_token_lens = am_scores.cpu().numpy(), valid_token_lens.cpu().numpy()
+ am_scores, valid_token_lens = am_scores.detach().cpu().numpy(), valid_token_lens.detach().cpu().numpy()
preds, raw_token = self.decode(am_scores, valid_token_lens)[0]
res['preds'] = preds
if us_cif_peak is not None:
@@ -105,6 +104,8 @@
feats = self.pad_feats(feats, np.max(feats_len))
feats_len = np.array(feats_len).astype(np.int32)
+ feats = torch.from_numpy(feats).type(torch.float32)
+ feats_len = torch.from_numpy(feats_len).type(torch.int32)
return feats, feats_len
@staticmethod
--
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