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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.
*/
/*!
* Copyright (c) 2015 by Contributors
* \file channel_op_common.h
* \brief common function used for concat and split channel
* \author Bing Xu
*/
#ifndef MXNET_OPERATOR_CHANNEL_OP_COMMON_H_
#define MXNET_OPERATOR_CHANNEL_OP_COMMON_H_
#include <dmlc/logging.h>
#include <mxnet/operator.h>
#include <vector>
#include "./operator_common.h"
namespace mxnet {
namespace op {
template<typename xpu, int dim, int cdim, typename DType>
inline void concatenate_helper(const std::vector<mshadow::Tensor<xpu, dim, DType> > &input,
mshadow::Tensor<xpu, dim, DType> *output, const int dimension,
const OpReqType req) {
using mshadow::expr::concat;
using mshadow::expr::slice;
if (dimension == cdim) {
mshadow::Tensor<xpu, dim, DType> out = *output;
size_t size = input.size();
index_t begin = 0;
for (size_t i = 0; i < size; ++i) {
// If input[i] is a zero-size tensor, do nothing.
if (input[i].shape_.Size() == 0) continue;
index_t end = begin + input[i].size(cdim);
Assign(slice<cdim>(out, begin, end), req, input[i]);
begin = end;
}
} else {
concatenate_helper<xpu, dim, (cdim > 0 ? cdim - 1 : 0)>(input, output, dimension, req);
}
}
template<typename xpu, int dim, typename DType>
inline void Concatenate(const std::vector<mshadow::Tensor<xpu, dim, DType> > &input,
mshadow::Tensor<xpu, dim, DType> *output, const int dimension,
const OpReqType req) {
if (dimension < 0) {
LOG(FATAL) << "dimension (" << dimension << ") must be greater than 0";
} else if (dimension >= dim) {
LOG(FATAL) << "dimension (" << dimension << ") must be smaller than dim (" << dim << ")";
} else {
concatenate_helper<xpu, dim, dim-1>(input, output, dimension, req);
}
}
template<typename xpu, int dim, int cdim, typename DType>
void split_helper(const mshadow::Tensor<xpu, dim, DType> &input,
std::vector<mshadow::Tensor<xpu, dim, DType> > *output,
const int dimension, const std::vector<OpReqType> &req) {
using mshadow::expr::concat;
using mshadow::expr::slice;
if (dimension == cdim) {
std::vector<mshadow::Tensor<xpu, dim, DType> > out = *output;
size_t size = out.size();
index_t begin = 0;
for (size_t i = 0; i < size; ++i) {
// If out[i] is a zero-size tensor, do nothing.
if (out[i].shape_.Size() == 0) continue;
index_t end = begin + out[i].size(cdim);
Assign(out[i], req[i], slice<cdim>(input, begin, end));
begin = end;
}
} else {
split_helper<xpu, dim, (cdim > 0 ? cdim - 1 : 0)>(input, output, dimension, req);
}
}
template<typename xpu, int dim, typename DType>
void Split(const mshadow::Tensor<xpu, dim, DType> &input,
std::vector<mshadow::Tensor<xpu, dim, DType> > *output,
const int dimension, const std::vector<OpReqType> &req) {
if (dimension < 0) {
LOG(FATAL) << "dimension (" << dimension << ") must be greater than 0";
} else if (dimension >= dim) {
LOG(FATAL) << "dimension (" << dimension << ") must be smaller than dim (" << dim << ")";
} else {
split_helper<xpu, dim, dim-1>(input, output, dimension, req);
}
}
} // namespace op
} // namespace mxnet
#endif // MXNET_OPERATOR_CHANNEL_OP_COMMON_H_