parent
c90be85398
commit
17a96cd6ea
@ -0,0 +1,86 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||||
|
#
|
||||||
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||||
|
# you may not use this file except in compliance with the License.
|
||||||
|
# You may obtain a copy of the License at
|
||||||
|
#
|
||||||
|
# http://www.apache.org/licenses/LICENSE-2.0
|
||||||
|
#
|
||||||
|
# Unless required by applicable law or agreed to in writing, software
|
||||||
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||||
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||||
|
# See the License for the specific language governing permissions and
|
||||||
|
# limitations under the License.
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import numpy as np
|
||||||
|
import onnxruntime
|
||||||
|
import paddle
|
||||||
|
import os
|
||||||
|
import pickle
|
||||||
|
|
||||||
|
def parse_args():
|
||||||
|
parser = argparse.ArgumentParser(description=__doc__)
|
||||||
|
parser.add_argument(
|
||||||
|
'--input_file',
|
||||||
|
type=str,
|
||||||
|
default="static_ds2online_inputs.pickle",
|
||||||
|
help="ds2 input pickle file.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
'--model_dir',
|
||||||
|
type=str,
|
||||||
|
default=".",
|
||||||
|
help="paddle model dir."
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
'--onnx_model',
|
||||||
|
type=str,
|
||||||
|
default='./model.old.onnx',
|
||||||
|
help="onnx model."
|
||||||
|
)
|
||||||
|
|
||||||
|
return parser.parse_args()
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
FLAGS = parse_args()
|
||||||
|
|
||||||
|
# input and output
|
||||||
|
with open(FLAGS.input_file, 'rb') as f:
|
||||||
|
iodict = pickle.load(f)
|
||||||
|
print(iodict.keys())
|
||||||
|
|
||||||
|
audio_chunk = iodict['audio_chunk']
|
||||||
|
audio_chunk_lens = iodict['audio_chunk_lens']
|
||||||
|
chunk_state_h_box = iodict['chunk_state_h_box']
|
||||||
|
chunk_state_c_box = iodict['chunk_state_c_bos']
|
||||||
|
|
||||||
|
# paddle
|
||||||
|
model = paddle.jit.load(os.path.join(FLAGS.model_dir, "avg_1.jit"))
|
||||||
|
res_chunk, res_lens, chunk_state_h, chunk_state_c = model(
|
||||||
|
paddle.to_tensor(audio_chunk),
|
||||||
|
paddle.to_tensor(audio_chunk_lens),
|
||||||
|
paddle.to_tensor(chunk_state_h_box),
|
||||||
|
paddle.to_tensor(chunk_state_c_box),
|
||||||
|
)
|
||||||
|
|
||||||
|
# onnxruntime
|
||||||
|
options = onnxruntime.SessionOptions()
|
||||||
|
options.enable_profiling=True
|
||||||
|
sess = onnxruntime.InferenceSession(FLAGS.onnx_model, sess_options=options)
|
||||||
|
ort_res_chunk, ort_res_lens, ort_chunk_state_h, ort_chunk_state_c = sess.run(
|
||||||
|
['softmax_0.tmp_0', 'tmp_5', 'concat_0.tmp_0', 'concat_1.tmp_0'],
|
||||||
|
{"audio_chunk": audio_chunk,
|
||||||
|
"audio_chunk_lens":audio_chunk_lens,
|
||||||
|
"chunk_state_h_box": chunk_state_h_box,
|
||||||
|
"chunk_state_c_box":chunk_state_c_box})
|
||||||
|
|
||||||
|
print(sess.end_profiling())
|
||||||
|
|
||||||
|
# assert paddle equal ort
|
||||||
|
print(np.allclose(ort_res_chunk, res_chunk, atol=1e-6))
|
||||||
|
print(np.allclose(ort_res_lens, res_lens, atol=1e-6))
|
||||||
|
print(np.allclose(ort_chunk_state_h, chunk_state_h, atol=1e-6))
|
||||||
|
print(np.allclose(ort_chunk_state_c, chunk_state_c, atol=1e-6))
|
Loading…
Reference in new issue