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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* 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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/*!
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* \file model.h
* \brief MXNET.cpp model module
* \author Zhang Chen
*/
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# ifndef MXNET_CPP_MODEL_H_
# define MXNET_CPP_MODEL_H_
# include <string>
# include <vector>
# include "mxnet-cpp/base.h"
# include "mxnet-cpp/symbol.h"
# include "mxnet-cpp/ndarray.h"
namespace mxnet {
namespace cpp {
struct FeedForwardConfig {
Symbol symbol ;
std : : vector < Context > ctx = { Context : : cpu ( ) } ;
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int num_epoch = 0 ;
int epoch_size = 0 ;
std : : string optimizer = " sgd " ;
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// TODO(zhangchen-qinyinghua) More implement
// initializer=Uniform(0.01),
// numpy_batch_size=128,
// arg_params=None, aux_params=None,
// allow_extra_params=False,
// begin_epoch=0,
// **kwargs):
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FeedForwardConfig ( const FeedForwardConfig & other ) { }
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FeedForwardConfig ( ) { }
} ;
class FeedForward {
public :
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explicit FeedForward ( const FeedForwardConfig & conf ) : conf_ ( conf ) { }
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void Predict ( ) ;
void Score ( ) ;
void Fit ( ) ;
void Save ( ) ;
void Load ( ) ;
static FeedForward Create ( ) ;
private :
void InitParams ( ) ;
void InitPredictor ( ) ;
void InitIter ( ) ;
void InitEvalIter ( ) ;
FeedForwardConfig conf_ ;
} ;
} // namespace cpp
} // namespace mxnet
# endif // MXNET_CPP_MODEL_H_
