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51 lines
1.6 KiB
51 lines
1.6 KiB
8 years ago
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# 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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is_predict = get_config_arg("is_predict", bool, False)
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####################Data Configuration ##################
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if not is_predict:
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data_dir = './data/'
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define_py_data_sources2(
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train_list=data_dir + 'train.list',
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test_list=data_dir + 'test.list',
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module='mnist_provider',
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obj='process')
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######################Algorithm Configuration #############
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settings(
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batch_size=128,
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learning_rate=0.1 / 128.0,
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learning_method=MomentumOptimizer(0.9),
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regularization=L2Regularization(0.0005 * 128))
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#######################Network Configuration #############
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data_size = 1 * 28 * 28
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label_size = 10
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img = data_layer(name='pixel', size=data_size)
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# small_vgg is predined in trainer_config_helpers.network
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predict = small_vgg(input_image=img, num_channels=1, num_classes=label_size)
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if not is_predict:
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lbl = data_layer(name="label", size=label_size)
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inputs(img, lbl)
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outputs(classification_cost(input=predict, label=lbl))
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else:
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outputs(predict)
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