67 lines
1.9 KiB
67 lines
1.9 KiB
# Copyright (c) 2017 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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from paddle.trainer_config_helpers import *
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settings(batch_size=16)
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channels = get_config_arg("channels", int, 2)
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data = data_layer(name ="input", size=channels*16*16)
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tmp = img_conv_layer(input=data,
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num_channels=channels,
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filter_size=3,
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num_filters=channels,
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padding=1,
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shared_biases=True,
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act=ReluActivation())
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tmp = img_pool_layer(input=tmp,
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pool_size=3,
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stride=1,
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padding=0,
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pool_type=AvgPooling())
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tmp = img_conv_layer(input=tmp,
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filter_size=3,
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num_filters=channels,
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padding=1,
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shared_biases=True,
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act=LinearActivation(),
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bias_attr=False)
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tmp = batch_norm_layer(input=tmp,
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use_global_stats=False,
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act=ReluActivation())
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tmp = img_pool_layer(input=tmp,
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pool_size=3,
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stride=2,
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padding=1,
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pool_type=MaxPooling())
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tmp = img_cmrnorm_layer(input=tmp, size=5, scale=0.0001, power=0.75)
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tmp = fc_layer(input=tmp,
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size=channels,
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bias_attr=False,
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act=ReluActivation())
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out = fc_layer(input=tmp,
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size=10,
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bias_attr=True,
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act=SoftmaxActivation())
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outputs(out)
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