wehub-resource-sync
77 lines
2.5 KiB
Python
77 lines
2.5 KiB
Python
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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 nets
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import paddle
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def conv_block(input, num_filter, groups, dropouts):
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return nets.img_conv_group(
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input=input,
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pool_size=2,
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pool_stride=2,
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conv_num_filter=[num_filter] * groups,
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conv_filter_size=3,
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conv_act='relu',
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conv_with_batchnorm=True,
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conv_batchnorm_drop_rate=dropouts,
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pool_type='max',
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)
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class TestLayer(unittest.TestCase):
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def test_dropout_layer(self):
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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images = paddle.static.data(
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name='pixel', shape=[-1, 3, 48, 48], dtype='float32'
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)
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paddle.nn.functional.dropout(x=images, p=0.5)
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print(str(main_program))
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def test_img_conv_group(self):
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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images = paddle.static.data(
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name='pixel', shape=[-1, 3, 48, 48], dtype='float32'
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)
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conv1 = conv_block(images, 64, 2, [0.3, 0])
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conv_block(conv1, 256, 3, [0.4, 0.4, 0])
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print(str(main_program))
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def test_elementwise_add_with_act(self):
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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image1 = paddle.static.data(
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name='pixel1', shape=[-1, 3, 48, 48], dtype='float32'
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)
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image2 = paddle.static.data(
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name='pixel2', shape=[-1, 3, 48, 48], dtype='float32'
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)
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paddle.nn.functional.relu(paddle.add(x=image1, y=image2))
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print(main_program)
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if __name__ == '__main__':
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unittest.main()
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