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54 lines
1.5 KiB
54 lines
1.5 KiB
9 years ago
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#edit-mode: -*- python -*-
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# Copyright (c) 2016 Baidu, Inc. 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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TrainData(SimpleData(
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files = "trainer/tests/sample_filelist.txt",
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feat_dim = 3,
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context_len = 0,
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buffer_capacity = 1000000,
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))
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settings(batch_size = 100)
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data = data_layer(name='input', size=3)
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fc1 = fc_layer(input=data, size=12,
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bias_attr=False,
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act=SigmoidActivation())
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fc2 = fc_layer(input=data, size=19,
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bias_attr=False,
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act=LinearActivation())
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fc3 = fc_layer(input=data, size=5,
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bias_attr=False,
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act=TanhActivation())
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fc4 = fc_layer(input=data, size=5,
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bias_attr=False,
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act=LinearActivation())
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# This is for training the neural network.
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# We need to have another data layer for label
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# and a layer for calculating cost
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lbl = data_layer(name='label', size=1)
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outputs(hsigmoid(input=[fc1, fc2, fc3, fc4],
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label=lbl,
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num_classes=3))
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