45 lines
1.5 KiB
45 lines
1.5 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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#
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#Licensed under the Apache License, Version 2.0 (the "License");
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#you may not use this file except in compliance with the License.
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#You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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#Unless required by applicable law or agreed to in writing, software
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#distributed under the License is distributed on an "AS IS" BASIS,
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#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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#See the License for the specific language governing permissions and
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#limitations under the License.
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import unittest
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import numpy as np
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import paddle.v2.fluid as fluid
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import paddle.v2.fluid.profiler as profiler
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import paddle.v2.fluid.layers as layers
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import os
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class TestProfiler(unittest.TestCase):
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def test_nvprof(self):
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if not fluid.core.is_compile_gpu():
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return
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epoc = 8
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dshape = [4, 3, 28, 28]
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data = layers.data(name='data', shape=[3, 28, 28], dtype='float32')
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conv = layers.conv2d(data, 20, 3, stride=[1, 1], padding=[1, 1])
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place = fluid.CUDAPlace(0)
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exe = fluid.Executor(place)
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exe.run(fluid.default_startup_program())
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output_file = 'cuda_profiler.txt'
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with profiler.cuda_profiler(output_file, 'csv') as nvprof:
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for i in range(epoc):
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input = np.random.random(dshape).astype('float32')
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exe.run(fluid.default_main_program(), feed={'data': input})
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os.remove(output_file)
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if __name__ == '__main__':
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unittest.main()
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