blob: 2b0e05d21fed66b8476cdbb8ada78ee30685e4bd [file] [log] [blame]
/*!
* Copyright (c) 2015 by Contributors
* \file lrn.cc
* \brief
* \author Bing Xu
*/
#include "./lrn-inl.h"
#if MXNET_USE_CUDNN == 1
#include "./cudnn_lrn-inl.h"
#endif
#if MXNET_USE_MKL2017 == 1
#include <mkl_memory.h>
#include "./mkl/mkl_memory-inl.h"
#include "./mkl/mkl_lrn-inl.h"
#endif
namespace mxnet {
namespace op {
template<>
Operator* CreateOp<cpu>(LRNParam param, int dtype) {
#if MXNET_USE_MKL2017 == 1
return new MKLLRNOp<cpu, float>(param);
#endif
return new LocalResponseNormOp<cpu>(param);
}
// DO_BIND_DISPATCH comes from operator_common.h
Operator* LocalResponseNormProp::CreateOperatorEx(Context ctx, std::vector<TShape> *in_shape,
std::vector<int> *in_type) const {
std::vector<TShape> out_shape, aux_shape;
std::vector<int> out_type, aux_type;
CHECK(InferType(in_type, &out_type, &aux_type));
CHECK(InferShape(in_shape, &out_shape, &aux_shape));
DO_BIND_DISPATCH(CreateOp, param_, (*in_type)[0]);
}
DMLC_REGISTER_PARAMETER(LRNParam);
MXNET_REGISTER_OP_PROPERTY(LRN, LocalResponseNormProp)
.add_argument("data", "Symbol", "Input data to the ConvolutionOp.")
.add_arguments(LRNParam::__FIELDS__())
.describe("Apply convolution to input then add a bias.");
} // namespace op
} // namespace mxnet