mkldnn_branches_pool.conf

# Copyright (c) 2017 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.

from paddle.trainer_config_helpers import *

settings(batch_size=16)
channels = get_config_arg("channels", int, 2)

def two_pool(input, group_name):
  out1 = img_pool_layer(input=input,
            name=group_name+'_pool1',
            pool_size=3,
            stride=2,
            padding=0,
            pool_type=MaxPooling())

  out2 = img_pool_layer(input=input,
            name=group_name+'_pool2',
            pool_size=5,
            stride=2,
            padding=1,
            pool_type=MaxPooling())
  return out1, out2

data = data_layer(name ="input", size=channels*16*16)

conv = img_conv_layer(input=data,
            num_channels=channels,
            filter_size=3,
            num_filters=channels,
            padding=1,
            shared_biases=True,
            act=LinearActivation())

pool = img_pool_layer(input=conv,
            pool_size=3,
            stride=1,
            padding=1,
            pool_type=AvgPooling())

a1, a2 = two_pool(input=pool, group_name='a')

concat = concat_layer(input=[a1, a2])

b1, b2 = two_pool(input=pool, group_name='b')

addto = addto_layer(input=[b1, b2])

outputs([concat, addto])