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# 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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def two_fc(input, group_name):
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out1 = fc_layer(input=input,
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name=group_name+'_fc1',
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size=channels,
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bias_attr=False,
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act=LinearActivation())
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out2 = fc_layer(input=input,
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name=group_name+'_fc2',
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size=channels,
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bias_attr=False,
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act=LinearActivation())
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return out1, out2
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data = data_layer(name ="input", size=channels*16*16)
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conv = 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=LinearActivation())
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pool = img_pool_layer(input=conv,
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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=AvgPooling())
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a1, a2 = two_fc(input=pool, group_name='a')
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concat = concat_layer(input=[a1, a2])
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b1, b2 = two_fc(input=pool, group_name='b')
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addto = addto_layer(input=[b1, b2])
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outputs([concat, addto])
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@ -0,0 +1,60 @@
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# 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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def two_pool(input, group_name):
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out1 = img_pool_layer(input=input,
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name=group_name+'_pool1',
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pool_size=3,
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stride=2,
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padding=0,
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pool_type=MaxPooling())
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out2 = img_pool_layer(input=input,
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name=group_name+'_pool2',
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pool_size=5,
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stride=2,
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padding=1,
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pool_type=MaxPooling())
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return out1, out2
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data = data_layer(name ="input", size=channels*16*16)
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conv = 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=LinearActivation())
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pool = img_pool_layer(input=conv,
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pool_size=3,
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stride=1,
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padding=1,
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pool_type=AvgPooling())
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a1, a2 = two_pool(input=pool, group_name='a')
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concat = concat_layer(input=[a1, a2])
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b1, b2 = two_pool(input=pool, group_name='b')
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addto = addto_layer(input=[b1, b2])
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outputs([concat, addto])
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