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Paddle/paddle/trainer/tests/sample_trainer_config_opt_b...

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# Copyright (c) 2016 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 *
################################### Data Configuration ###################################
TrainData(ProtoData(files = "trainer/tests/mnist.list"))
################################### Algorithm Configuration ###################################
settings(batch_size = 1000,
learning_method = MomentumOptimizer(momentum=0.5, sparse=False))
################################### Network Configuration ###################################
data = data_layer(name ="input", size=784)
fc1 = fc_layer(input=data, size=800,
bias_attr=True,
act=SigmoidActivation())
fc2 = fc_layer(input=fc1, size=800,
bias_attr=True,
act=SigmoidActivation())
output = fc_layer(input=[fc1, fc2], size=10,
bias_attr=True,
act=SoftmaxActivation())
lbl = data_layer(name ="label", size=1)
cost = classification_cost(input=output, label=lbl)
outputs(cost)