shared_fc.py 1.4 KB
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#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# 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
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

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from paddle.trainer_config_helpers import *

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settings(learning_rate=1e-4, batch_size=1000)
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a = data_layer(name='feature_a', size=200)
b = data_layer(name='feature_b', size=200)

fc_param = ParamAttr(name='fc_param', initial_max=1.0, initial_min=-1.0)
bias_param = ParamAttr(name='bias_param', initial_mean=0.0, initial_std=0.0)

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softmax_param = ParamAttr(
    name='softmax_param', initial_max=1.0, initial_min=-1.0)
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hidden_a = fc_layer(
    input=a, size=200, param_attr=fc_param, bias_attr=bias_param)
hidden_b = fc_layer(
    input=b, size=200, param_attr=fc_param, bias_attr=bias_param)
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predict = fc_layer(
    input=[hidden_a, hidden_b],
    param_attr=[softmax_param, softmax_param],
    bias_attr=False,
    size=10,
    act=SoftmaxActivation())
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outputs(
    classification_cost(
        input=predict, label=data_layer(
            name='label', size=10)))