提交 60b84856 编写于 作者: T tensor-tang

refine the conf files, combine in one file

上级 b487c62a
...@@ -15,31 +15,42 @@ ...@@ -15,31 +15,42 @@
from paddle.trainer_config_helpers import * from paddle.trainer_config_helpers import *
settings(batch_size=16) settings(batch_size=16)
channels = get_config_arg("channels", int, 2)
data = data_layer(name ="input", size=32*16*16) def two_conv(input, group_name):
out1 = img_conv_layer(input=input,
name=group_name+'_conv1',
filter_size=1,
num_filters=channels,
padding=0,
shared_biases=True,
act=ReluActivation())
conv = img_conv_layer(input=data, out2 = img_conv_layer(input=input,
num_channels=32, name=group_name+'_conv2',
filter_size=3, filter_size=3,
num_filters=32, num_filters=channels,
padding=1, padding=1,
shared_biases=True, shared_biases=True,
act=ReluActivation()) act=ReluActivation())
return out1, out2
b1 = img_conv_layer(input=conv, data = data_layer(name ="input", size=channels*16*16)
filter_size=1,
num_filters=32,
padding=0,
shared_biases=True,
act=ReluActivation())
b2 = img_conv_layer(input=conv, conv = img_conv_layer(input=data,
num_channels=channels,
filter_size=3, filter_size=3,
num_filters=32, num_filters=channels,
padding=1, padding=1,
shared_biases=True, shared_biases=True,
act=ReluActivation()) act=ReluActivation())
concat = addto_layer(input=[b1, b2]) a1, a2 = two_conv(input=conv, group_name='a')
concat = concat_layer(input=[a1, a2])
b1, b2 = two_conv(input=conv, group_name='b')
addto = addto_layer(input=[b1, b2])
outputs(concat) outputs([concat, addto])
# 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=2)
data = data_layer(name ="input", size=3*4*4)
conv = img_conv_layer(input=data,
num_channels=1,
filter_size=3,
num_filters=2,
padding=1,
shared_biases=True,
act=ReluActivation())
b1 = img_conv_layer(input=conv,
filter_size=1,
num_filters=2,
padding=0,
shared_biases=True,
act=ReluActivation())
b2 = img_conv_layer(input=conv,
filter_size=3,
num_filters=2,
padding=1,
shared_biases=True,
act=ReluActivation())
concat = addto_layer(input=[b1, b2])
outputs(concat)
# 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=2)
data = data_layer(name ="input", size=3*4*4)
conv = img_conv_layer(input=data,
num_channels=1,
filter_size=3,
num_filters=2,
padding=1,
shared_biases=True,
act=ReluActivation())
b1 = img_conv_layer(input=conv,
filter_size=1,
num_filters=2,
padding=0,
shared_biases=True,
act=ReluActivation())
b2 = img_conv_layer(input=conv,
filter_size=3,
num_filters=2,
padding=1,
shared_biases=True,
act=ReluActivation())
concat = concat_layer(input=[b1, b2])
outputs(concat)
# 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)
data = data_layer(name ="input", size=32*16*16)
conv = img_conv_layer(input=data,
num_channels=32,
filter_size=3,
num_filters=32,
padding=1,
shared_biases=True,
act=ReluActivation())
b1 = img_conv_layer(input=conv,
filter_size=1,
num_filters=32,
padding=0,
shared_biases=True,
act=ReluActivation())
b2 = img_conv_layer(input=conv,
filter_size=3,
num_filters=32,
padding=1,
shared_biases=True,
act=ReluActivation())
concat = concat_layer(input=[b1, b2])
outputs(concat)
...@@ -248,14 +248,17 @@ TEST(MKLDNNActivation, Activations) { ...@@ -248,14 +248,17 @@ TEST(MKLDNNActivation, Activations) {
} }
} }
DECLARE_string(config_args);
TEST(MKLDNNLayer, branches) { TEST(MKLDNNLayer, branches) {
std::vector<std::string> cases = {"conv_conv_concat", std::vector<std::string> cases = {"conv"};
"conv_conv_concat_32c",
"conv_conv_addto",
"conv_conv_addto_32c"};
for (auto name : cases) { for (auto name : cases) {
std::string config = "./gserver/tests/mkldnn_branches_" + name + ".conf"; std::string config = "./gserver/tests/mkldnn_branches_" + name + ".conf";
MKLDNNTester::runBranchesTest(config); for (auto channels : {2, 32}) {
std::ostringstream oss;
oss << "channels=" << channels;
FLAGS_config_args = oss.str();
MKLDNNTester::runBranchesTest(config);
}
} }
} }
......
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