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Add benchmark.

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pull/1548/head
KP 2 years ago
parent 48167eb909
commit 7c3a11ccef
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45
paddleaudio/tests/benchmark/README.md
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# 1. Prepare
First, install `line_profiler` via pip.
```sh
pip install line_profiler
```
# 2. Run
Run the specific script for profiling.
```sh
kernprof -l features/mel_spectrogram.py
python -m line_profiler -u 1e-3 mel_spectrogram.py.lprof
```
Result:
```sh
Timer unit: 0.001 s
Total time: 22.1208 s
File: features/mel_spectrogram.py
Function: test_melspect_cpu at line 13
Line # Hits Time Per Hit % Time Line Contents
==============================================================
13 @profile
14 def test_melspect_cpu(input_shape, times):
15 1 0.1 0.1 0.0 paddle.set_device('cpu')
16 1 234.5 234.5 1.1 x = paddle.randn(input_shape)
17 1 85.3 85.3 0.4 feature_extractor = paddleaudio.features.MelSpectrogram(**feat_conf, dtype=x.dtype)
18 101 0.5 0.0 0.0 for i in range(times):
19 100 21800.5 218.0 98.6 y = feature_extractor(x)
Total time: 4.80543 s
File: features/mel_spectrogram.py
Function: test_melspect_gpu at line 22
Line # Hits Time Per Hit % Time Line Contents
==============================================================
22 @profile
23 def test_melspect_gpu(input_shape, times):
24 1 0.5 0.5 0.0 paddle.set_device('gpu')
25 1 4144.8 4144.8 86.3 x = paddle.randn(input_shape)
26 1 41.9 41.9 0.9 feature_extractor = paddleaudio.features.MelSpectrogram(**feat_conf, dtype=x.dtype)
27 101 0.2 0.0 0.0 for i in range(times):
28 100 618.1 6.2 12.9 y = feature_extractor(x)
```

13
paddleaudio/tests/benchmark/features/__init__.py
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# 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.

50
paddleaudio/tests/benchmark/features/log_mel_spectrogram.py
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# 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 paddle
import paddleaudio
feat_conf = {
'sr': 16000,
'n_fft': 512,
'hop_length': 128,
'n_mels': 40,
'f_min': 0.0,
}
@profile
def test_log_melspect_cpu(input_shape, times):
paddle.set_device('cpu')
x = paddle.randn(input_shape)
feature_extractor = paddleaudio.features.LogMelSpectrogram(
**feat_conf, dtype=x.dtype)
for i in range(times):
y = feature_extractor(x)
@profile
def test_log_melspect_gpu(input_shape, times):
paddle.set_device('gpu')
x = paddle.randn(input_shape)
feature_extractor = paddleaudio.features.LogMelSpectrogram(
**feat_conf, dtype=x.dtype)
for i in range(times):
y = feature_extractor(x)
input_shape = (16, 48000) # (N, T)
times = 100
test_log_melspect_cpu(input_shape, times)
test_log_melspect_gpu(input_shape, times)

50
paddleaudio/tests/benchmark/features/mel_spectrogram.py
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# 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 paddle
import paddleaudio
feat_conf = {
'sr': 16000,
'n_fft': 512,
'hop_length': 128,
'n_mels': 40,
'f_min': 0.0,
}
@profile
def test_melspect_cpu(input_shape, times):
paddle.set_device('cpu')
x = paddle.randn(input_shape)
feature_extractor = paddleaudio.features.MelSpectrogram(
**feat_conf, dtype=x.dtype)
for i in range(times):
y = feature_extractor(x)
@profile
def test_melspect_gpu(input_shape, times):
paddle.set_device('gpu')
x = paddle.randn(input_shape)
feature_extractor = paddleaudio.features.MelSpectrogram(
**feat_conf, dtype=x.dtype)
for i in range(times):
y = feature_extractor(x)
input_shape = (16, 48000) # (N, T)
times = 100
test_melspect_cpu(input_shape, times)
test_melspect_gpu(input_shape, times)

50
paddleaudio/tests/benchmark/features/mfcc.py
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# 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 paddle
import paddleaudio
feat_conf = {
'sr': 16000,
'n_mfcc': 20,
'n_fft': 512,
'hop_length': 128,
'n_mels': 40,
'f_min': 0.0,
'top_db': 80.0,
}
@profile
def test_mfcc_cpu(input_shape, times):
paddle.set_device('cpu')
x = paddle.randn(input_shape)
feature_extractor = paddleaudio.features.MFCC(**feat_conf, dtype=x.dtype)
for i in range(times):
y = feature_extractor(x)
@profile
def test_mfcc_gpu(input_shape, times):
paddle.set_device('gpu')
x = paddle.randn(input_shape)
feature_extractor = paddleaudio.features.MFCC(**feat_conf, dtype=x.dtype)
for i in range(times):
y = feature_extractor(x)
input_shape = (16, 48000) # (N, T)
times = 100
test_mfcc_cpu(input_shape, times)
test_mfcc_gpu(input_shape, times)
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