src/operator/tensor/elemwise_binary_broadcast_op_extended.cc

/*
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 * 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 elemwise_binary_broadcast_op_extended.cc
 * \brief CPU Implementation of extended functions for elementwise binary broadcast operator.
 */
#include "./elemwise_unary_op.h"
#include "./elemwise_binary_op.h"
#include "./elemwise_binary_broadcast_op.h"

namespace mxnet {
namespace op {
MXNET_OPERATOR_REGISTER_BINARY_BROADCAST(broadcast_power)
    .describe(
        R"code(Returns result of first array elements raised to powers from second array, element-wise with broadcasting.

Example::

   x = [[ 1.,  1.,  1.],
        [ 1.,  1.,  1.]]

   y = [[ 0.],
        [ 1.]]

   broadcast_power(x, y) = [[ 2.,  2.,  2.],
                            [ 4.,  4.,  4.]]

)code" ADD_FILELINE)
    .set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::power>)
    .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_broadcast_power"});

NNVM_REGISTER_OP(_backward_broadcast_power)
    .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::power_grad, mshadow_op::power_rgrad>);

MXNET_OPERATOR_REGISTER_BINARY_BROADCAST(broadcast_maximum)
    .add_alias("_npi_maximum")
    .describe(R"code(Returns element-wise maximum of the input arrays with broadcasting.

This function compares two input arrays and returns a new array having the element-wise maxima.

Example::

   x = [[ 1.,  1.,  1.],
        [ 1.,  1.,  1.]]

   y = [[ 0.],
        [ 1.]]

   broadcast_maximum(x, y) = [[ 1.,  1.,  1.],
                              [ 1.,  1.,  1.]]

)code" ADD_FILELINE)
    .set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::maximum>)
    .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_broadcast_maximum"});

NNVM_REGISTER_OP(_backward_broadcast_maximum)
    .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::ge, mshadow_op::lt>);

MXNET_OPERATOR_REGISTER_BINARY_BROADCAST(broadcast_minimum)
    .add_alias("_npi_minimum")
    .describe(R"code(Returns element-wise minimum of the input arrays with broadcasting.

This function compares two input arrays and returns a new array having the element-wise minima.

Example::

   x = [[ 1.,  1.,  1.],
        [ 1.,  1.,  1.]]

   y = [[ 0.],
        [ 1.]]

   broadcast_maximum(x, y) = [[ 0.,  0.,  0.],
                              [ 1.,  1.,  1.]]

)code" ADD_FILELINE)
    .set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::minimum>)
    .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_broadcast_minimum"});

NNVM_REGISTER_OP(_backward_broadcast_minimum)
    .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::le, mshadow_op::gt>);

MXNET_OPERATOR_REGISTER_BINARY_BROADCAST(broadcast_hypot)
    .describe(R"code( Returns the hypotenuse of a right angled triangle, given its "legs"
with broadcasting.

It is equivalent to doing :math:`sqrt(x_1^2 + x_2^2)`.

Example::

   x = [[ 3.,  3.,  3.]]

   y = [[ 4.],
        [ 4.]]

   broadcast_hypot(x, y) = [[ 5.,  5.,  5.],
                            [ 5.,  5.,  5.]]

   z = [[ 0.],
        [ 4.]]

   broadcast_hypot(x, z) = [[ 3.,  3.,  3.],
                            [ 5.,  5.,  5.]]

)code" ADD_FILELINE)
    .set_attr<FCompute>("FCompute<cpu>", BinaryBroadcastCompute<cpu, mshadow_op::hypot>)
    .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseIn{"_backward_broadcast_hypot"});

NNVM_REGISTER_OP(_backward_broadcast_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>);

}  // namespace op
}  // namespace mxnet