/*
 * 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 np_elemwise_binary_op_extended.cc
 * \brief CPU Implementation of extended functions for elementwise numpy binary broadcast operator.
 */

#include <dmlc/strtonum.h>
#include "../../common/utils.h"
#include "./np_elemwise_broadcast_op.h"

namespace mxnet {
namespace op {

#define MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(name)                    \
  NNVM_REGISTER_OP(name)                                                  \
  .set_num_inputs(1)                                                      \
  .set_num_outputs(1)                                                     \
  .set_attr_parser(ParamParser<NumpyBinaryScalarParam>)                   \
  .set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>)       \
  .set_attr<nnvm::FInferType>("FInferType", NumpyBinaryScalarType)        \
  .set_attr<FResourceRequest>("FResourceRequest",                         \
    [](const NodeAttrs& attrs) {                                          \
      return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};   \
    })                                                                    \
  .add_argument("data", "NDArray-or-Symbol", "source input")              \
  .add_arguments(NumpyBinaryScalarParam::__FIELDS__())

MXNET_OPERATOR_REGISTER_BINARY_BROADCAST(_npi_copysign)
.describe(R"code()code" ADD_FILELINE)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::copysign>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_copysign"});

NNVM_REGISTER_OP(_backward_npi_copysign)
.set_num_inputs(3)
.set_num_outputs(2)
.set_attr<nnvm::TIsBackward>("TIsBackward", true)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs){
    return std::vector<std::pair<int, int> >{{0, 1}};
  })
.set_attr<FResourceRequest>("FResourceRequest",
  [](const NodeAttrs& attrs) {
    return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};
  })
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastBackwardUseIn<cpu, mshadow_op::copysign_grad,
                                                                  mshadow_op::copysign_rgrad>);

NNVM_REGISTER_OP(_npi_lcm)
.set_num_inputs(2)
.set_num_outputs(1)
.set_attr<nnvm::FListInputNames>("FListInputNames",
[](const NodeAttrs& attrs) {
     return std::vector<std::string>{"lhs", "rhs"};
})
.set_attr<mxnet::FInferShape>("FInferShape", BinaryBroadcastShape)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<2, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
[](const NodeAttrs& attrs){
     return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};
})
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastIntCompute<cpu, mshadow_op::lcm>)
.add_argument("lhs", "NDArray-or-Symbol", "First input to the function")
.add_argument("rhs", "NDArray-or-Symbol", "Second input to the function");

NNVM_REGISTER_OP(_npi_lcm_scalar)
.set_num_inputs(1)
.set_num_outputs(1)
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<1, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs){
    return std::vector<std::pair<int, int> >{{0, 0}};
  })
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.add_argument("data", "NDArray-or-Symbol", "source input")
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu, mshadow_op::lcm>);

NNVM_REGISTER_OP(_npi_bitwise_and)
.set_num_inputs(2)
.set_num_outputs(1)
.set_attr<nnvm::FListInputNames>("FListInputNames",
[](const NodeAttrs& attrs) {
     return std::vector<std::string>{"lhs", "rhs"};
})
.set_attr<mxnet::FInferShape>("FInferShape", BinaryBroadcastShape)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<2, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
[](const NodeAttrs& attrs){
     return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};
})
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastIntCompute<cpu, mshadow_op::bitwise_and>)
.add_argument("lhs", "NDArray-or-Symbol", "First input to the function")
.add_argument("rhs", "NDArray-or-Symbol", "Second input to the function");

NNVM_REGISTER_OP(_npi_bitwise_and_scalar)
.set_num_inputs(1)
.set_num_outputs(1)
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<1, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs){
    return std::vector<std::pair<int, int> >{{0, 0}};
  })
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.add_argument("data", "NDArray-or-Symbol", "source input")
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::ComputeInt<cpu, mshadow_op::bitwise_and>);

NNVM_REGISTER_OP(_npi_bitwise_xor)
.set_num_inputs(2)
.set_num_outputs(1)
.set_attr<nnvm::FListInputNames>("FListInputNames",
[](const NodeAttrs& attrs) {
     return std::vector<std::string>{"lhs", "rhs"};
})
.set_attr<mxnet::FInferShape>("FInferShape", BinaryBroadcastShape)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<2, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
[](const NodeAttrs& attrs){
     return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};
})
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastIntCompute<cpu, mshadow_op::bitwise_xor>)
.add_argument("lhs", "NDArray-or-Symbol", "First input to the function")
.add_argument("rhs", "NDArray-or-Symbol", "Second input to the function");

NNVM_REGISTER_OP(_npi_bitwise_or)
.set_num_inputs(2)
.set_num_outputs(1)
.set_attr<nnvm::FListInputNames>("FListInputNames",
[](const NodeAttrs& attrs) {
     return std::vector<std::string>{"lhs", "rhs"};
})
.set_attr<mxnet::FInferShape>("FInferShape", BinaryBroadcastShape)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<2, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
[](const NodeAttrs& attrs){
     return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};
})
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastIntCompute<cpu, mshadow_op::bitwise_or>)
.add_argument("lhs", "NDArray-or-Symbol", "First input to the function")
.add_argument("rhs", "NDArray-or-Symbol", "Second input to the function");

NNVM_REGISTER_OP(_npi_bitwise_xor_scalar)
.set_num_inputs(1)
.set_num_outputs(1)
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<1, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs){
    return std::vector<std::pair<int, int> >{{0, 0}};
  })
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.add_argument("data", "NDArray-or-Symbol", "source input")
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::ComputeInt<cpu, mshadow_op::bitwise_xor>);

NNVM_REGISTER_OP(_npi_bitwise_or_scalar)
.set_num_inputs(1)
.set_num_outputs(1)
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseIntType<1, 1>)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs){
    return std::vector<std::pair<int, int> >{{0, 0}};
  })
.set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes)
.add_argument("data", "NDArray-or-Symbol", "source input")
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::ComputeInt<cpu, mshadow_op::bitwise_or>);

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_copysign_scalar)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu, mshadow_op::copysign>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_copysign_scalar"});

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_rcopysign_scalar)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu, mshadow_op::rcopysign>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_rcopysign_scalar"});

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_backward_npi_copysign_scalar)
.set_attr<FCompute>("FCompute<cpu>",
                    BinaryScalarOp::Backward<cpu, mshadow_op::copysign_grad>);

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_backward_npi_rcopysign_scalar)
.set_attr<FCompute>("FCompute<cpu>",
                    BinaryScalarOp::Backward<cpu, mshadow_op::rcopysign_grad>);

inline bool Arctan2OpType(const nnvm::NodeAttrs& attrs,
                          std::vector<int>* in_attrs,
                          std::vector<int>* out_attrs) {
  CHECK_EQ(in_attrs->size(), 2U);
  CHECK_EQ(out_attrs->size(), 1U);

  TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0));
  TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1));
  TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0));
  TYPE_ASSIGN_CHECK(*in_attrs, 1, out_attrs->at(0));
  // check if it is float16, float32 or float64. If not, raise error.
  CHECK(common::is_float(in_attrs->at(0))) << "Do not support `int` as input.\n";
  return out_attrs->at(0) != -1;
}

NNVM_REGISTER_OP(_npi_arctan2)
.set_num_inputs(2)
.set_num_outputs(1)
.set_attr<nnvm::FListInputNames>("FListInputNames",
  [](const NodeAttrs& attrs) {
    return std::vector<std::string>{"x1", "x2"};
  })
.set_attr<mxnet::FInferShape>("FInferShape", BinaryBroadcastShape)
.set_attr<nnvm::FInferType>("FInferType", Arctan2OpType)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::arctan2>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_arctan2"})
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs) {
    return std::vector<std::pair<int, int> >{{0, 0}};
  })
.add_argument("x1", "NDArray-or-Symbol", "The input array")
.add_argument("x2", "NDArray-or-Symbol", "The input array");

NNVM_REGISTER_OP(_backward_npi_arctan2)
.set_num_inputs(3)
.set_num_outputs(2)
.set_attr<nnvm::TIsBackward>("TIsBackward", true)
.set_attr<FResourceRequest>("FResourceRequest",
  [](const NodeAttrs& attrs) {
    return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};
  })
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastBackwardUseIn<cpu, mshadow_op::arctan2_grad,
                                                                  mshadow_op::arctan2_rgrad>);

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_arctan2_scalar)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu, mshadow_op::arctan2>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_arctan2_scalar"});

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_rarctan2_scalar)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu, mshadow_op::rarctan2>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_rarctan2_scalar"});

MXNET_OPERATOR_REGISTER_BINARY(_backward_npi_arctan2_scalar)
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<FCompute>("FCompute<cpu>",
                    BinaryScalarOp::Backward<cpu, mshadow_op::arctan2_grad>);

MXNET_OPERATOR_REGISTER_BINARY(_backward_npi_rarctan2_scalar)
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<FCompute>("FCompute<cpu>",
                    BinaryScalarOp::Backward<cpu, mshadow_op::arctan2_rgrad>);

bool HypotOpType(const nnvm::NodeAttrs& attrs,
                 std::vector<int>* in_attrs,
                 std::vector<int>* out_attrs) {
  CHECK_EQ(in_attrs->size(), 2U);
  CHECK_EQ(out_attrs->size(), 1U);

  TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0));
  TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1));
  TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0));
  TYPE_ASSIGN_CHECK(*in_attrs, 1, out_attrs->at(0));

  CHECK(common::is_float(in_attrs->at(0))) << "Do not support `int` as input.\n";
  return out_attrs->at(0) != -1;
}

// rigister hypot that do not support int here
NNVM_REGISTER_OP(_npi_hypot)
.set_num_inputs(2)
.set_num_outputs(1)
.set_attr<nnvm::FListInputNames>("FListInputNames",
  [](const NodeAttrs& attrs) {
    return std::vector<std::string>{"x1", "x2"};
  })
.set_attr<mxnet::FInferShape>("FInferShape", BinaryBroadcastShape)
.set_attr<nnvm::FInferType>("FInferType", HypotOpType)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::hypot>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_hypot"})
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs) {
    return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};
  })
.add_argument("x1", "NDArray-or-Symbol", "The input array")
.add_argument("x2", "NDArray-or-Symbol", "The input array");

NNVM_REGISTER_OP(_backward_npi_hypot)
.set_num_inputs(3)
.set_num_outputs(2)
.set_attr<nnvm::TIsBackward>("TIsBackward", true)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs) {
    return std::vector<std::pair<int, int> > {{0, 1}};
  })
.set_attr<FResourceRequest>("FResourceRequest",
  [](const NodeAttrs& attrs) {
    return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};
  })
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastBackwardUseIn<cpu, mshadow_op::hypot_grad_left,
                                                                  mshadow_op::hypot_grad_right>);

MXNET_OPERATOR_REGISTER_BINARY_BROADCAST(_npi_ldexp)
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::ldexp>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_ldexp"});

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_ldexp_scalar)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu, mshadow_op::ldexp>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_ldexp_scalar"});

MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_rldexp_scalar)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu, mshadow_op::rldexp>)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_npi_rldexp_scalar"});

NNVM_REGISTER_OP(_backward_npi_ldexp)
.set_num_inputs(3)
.set_num_outputs(2)
.set_attr<nnvm::TIsBackward>("TIsBackward", true)
.set_attr<nnvm::FInplaceOption>("FInplaceOption",
  [](const NodeAttrs& attrs){
    return std::vector<std::pair<int, int> >{{0, 1}};
  })
.set_attr<FResourceRequest>("FResourceRequest",
  [](const NodeAttrs& attrs) {
    return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};
  })
.set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastBackwardUseIn<cpu, mshadow_op::ldexp_grad,
                                                                  mshadow_op::ldexp_rgrad>);

MXNET_OPERATOR_REGISTER_BINARY(_backward_npi_ldexp_scalar)
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Backward<cpu, mshadow_op::ldexp_grad>);

MXNET_OPERATOR_REGISTER_BINARY(_backward_npi_rldexp_scalar)
.add_arguments(NumpyBinaryScalarParam::__FIELDS__())
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Backward<cpu, mshadow_op::rldexp_grad>);

}  // namespace op
}  // namespace mxnet