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44 lines
2.6 KiB
44 lines
2.6 KiB
# 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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#Todo(luotao02) This config is only used for unitest. It is out of date now, and will be updated later.
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################################### Data Configuration ###################################
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TrainData(ProtoData(files = "train.list"))
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################################### Algorithm Configuration ###################################
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Settings(
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learning_rate_decay_a = 0.0,
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learning_rate_decay_b = 0.0,
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learning_rate = 1e-03,
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batch_size = 1000,
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algorithm = 'sgd',
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num_batches_per_send_parameter = 1,
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num_batches_per_get_parameter = 1,
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learning_method='momentum',
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)
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default_momentum(0.5)
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################################### Network Configuration ###################################
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Layer(type = "data", name = "input", size = 784)
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Layer(inputs = [Input("input", parameter_name = "_layer1.w")], name = "layer1", bias = Bias(parameter_name = "_layer1.bias"), active_type = "sigmoid", type = "fc", size = 800)
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Layer(inputs = [Input("layer1", parameter_name = "_layer2.w")], name = "layer2", bias = Bias(parameter_name = "_layer2.bias"), active_type = "sigmoid", type = "fc", size = 800)
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#Layer(inputs = [Input("layer2", parameter_name = "_layer_output.w", decay_rate = 0.02)], name = "output", bias = Bias(parameter_name = "_layer_output.bias"), active_type = "margin", type = "fc", size = 10)
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#Layer(inputs = [Input("layer2", parameter_name = "_layer_output.w", decay_rate = 0.02)], name = "output", bias = Bias(parameter_name = "_layer_output.bias"), type = "fc", size = 10)
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Layer(inputs = [Input("layer2", parameter_name = "_layer_output.w")], name = "output", bias = Bias(parameter_name = "_layer_output.bias"), active_type = "softmax", type = "fc", size = 10)
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Layer(type = "data", name = "label", size = 1)
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Layer(inputs = [Input("output"), Input("label")], type = "multi-class-cross-entropy", name = "cost")
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#Layer(inputs = [Input("output"), Input("label")], type = "huber", name = "cost")
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Evaluator(inputs=["output", "label"], type = "classification_error", name = "classification_error")
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Inputs("input", "label")
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Outputs("cost")
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