42 lines
1.3 KiB
42 lines
1.3 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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# 1. read data. Suppose you saved above python code as dataprovider.py
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data_file = 'empty.list'
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with open(data_file, 'w') as f:
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f.writelines(' ')
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define_py_data_sources2(
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train_list=data_file,
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test_list=None,
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module='dataprovider',
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obj='process',
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args={})
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# 2. learning algorithm
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settings(batch_size=12, learning_rate=1e-3, learning_method=MomentumOptimizer())
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# 3. Network configuration
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x = data_layer(name='x', size=1)
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y = data_layer(name='y', size=1)
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y_predict = fc_layer(
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input=x,
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param_attr=ParamAttr(name='w'),
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size=1,
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act=LinearActivation(),
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bias_attr=ParamAttr(name='b'))
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cost = regression_cost(input=y_predict, label=y)
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outputs(cost)
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