quadratic_op.cc

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 * to you under the Apache License, Version 2.0 (the
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 *
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/*!
 * \file quadratic_op.cc
 * \brief CPU Implementation of quadratic op
 */
#include "./quadratic_op-inl.h"

namespace mxnet {
namespace op {

DMLC_REGISTER_PARAMETER(QuadraticParam);

NNVM_REGISTER_OP(_contrib_quadratic)
.describe(R"code(This operators implements the quadratic function.

.. math::
    f(x) = ax^2+bx+c

where :math:`x` is an input tensor and all operations
in the function are element-wise.

Example::

  x = [[1, 2], [3, 4]]
  y = quadratic(data=x, a=1, b=2, c=3)
  y = [[6, 11], [18, 27]]

The storage type of ``quadratic`` output depends on storage types of inputs
  - quadratic(csr, a, b, 0) = csr
  - quadratic(default, a, b, c) = default

)code" ADD_FILELINE)
.set_attr_parser(ParamParser<QuadraticParam>)
.set_num_inputs(1)
.set_num_outputs(1)
.set_attr<nnvm::FListInputNames>("FListInputNames",
  [](const NodeAttrs& attrs) {
    return std::vector<std::string>{"data"};
  })
.set_attr<nnvm::FInferShape>("FInferShape", QuadraticOpShape)
.set_attr<nnvm::FInferType>("FInferType", QuadraticOpType)
.set_attr<FInferStorageType>("FInferStorageType", QuadraticOpStorageType)
.set_attr<FCompute>("FCompute<cpu>", QuadraticOpForward<cpu>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_contrib_backward_quadratic"})
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs) {
    return std::vector<std::pair<int, int> >{{0, 0}};
  })
.add_argument("data", "NDArray-or-Symbol", "Input ndarray")
.add_arguments(QuadraticParam::__FIELDS__());

NNVM_REGISTER_OP(_contrib_backward_quadratic)
.set_attr_parser(ParamParser<QuadraticParam>)
.set_num_inputs(2)
.set_num_outputs(1)
.set_attr<nnvm::TIsBackward>("TIsBackward", true)
.set_attr<FCompute>("FCompute<cpu>", QuadraticOpBackward<cpu>)
.set_attr<FComputeEx>("FComputeEx<cpu>", QuadraticOpForwardEx<cpu>);

}  // namespace op
}  // namespace mxnet