# 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(SimpleData(
            files = "trainer/tests/sample_filelist.txt",
            feat_dim = 3,
            context_len = 0,
            buffer_capacity = 1000000))
################################### Algorithm Configuration ###################################
settings(batch_size = 1000,
         learning_method = MomentumOptimizer(momentum=0.5, sparse=False))
################################### Network Configuration ###################################
data = data_layer(name ="input", size=3)

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)