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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.
*/
/*!
* \file model.h
* \brief MXNET.cpp model module
* \author Zhang Chen
*/
#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()};
int num_epoch = 0;
int epoch_size = 0;
std::string optimizer = "sgd";
// 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):
FeedForwardConfig(const FeedForwardConfig& other) {}
FeedForwardConfig() {}
};
class FeedForward {
public:
explicit FeedForward(const FeedForwardConfig& conf) : conf_(conf) {}
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_