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