meshgrid_op.cc

// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed 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.

#include <memory>
#include <string>
#include <vector>

#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/multiary.h"

namespace paddle {
namespace operators {

class MeshgridOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

 protected:
  phi::KernelKey GetExpectedKernelType(
      const framework::ExecutionContext& ctx) const override {
    auto inputs = ctx.MultiInput<phi::DenseTensor>("X");
    auto input_data_type = framework::proto::VarType::Type(0);
    bool flag = 0;
    for (auto* input : inputs) {
      if (input->IsInitialized() && input->numel() > 0) {
        input_data_type = framework::TransToProtoVarType(input->dtype());
        flag = 1;
        break;
      }
    }
    if (flag == 0) {
      PADDLE_THROW(platform::errors::InvalidArgument(
          "All Inputs of Meshgrid OP are Empty!"));
    }

    return phi::KernelKey(input_data_type, ctx.GetPlace());
  }
};

class MeshgridOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "(Tensor, default Tensor<float>).").AsDuplicable();
    AddOutput("Out", "(Tensor, default Tensor<float>.)").AsDuplicable();

    AddComment(R"DOC(
Meshgrid Operator.
Take: N tensors, each of which can be either scalr or 1-dimensional vector, and create
N-dimensional grids.

Args:
  tensors (list of tensor): if the input k tensors has (N1,), (N2,),..., (Nk,), then
  the output tensors are all of size (N1, N2, ...., Nk).

Example::
>>> x = fluid.data(name='x', shape=[10], dtype='float64')
>>> y = fluid.data(name='y', shape=[20], dtype='float64')
>>> grid_x, grid_y = fluid.layers.meshgrid([x, y])
>>> grid_x.shape
(10,20)
>>> grid_y.shape
(10,20)
)DOC");
  }
};

class MeshgridGradOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

 protected:
  void InferShape(framework::InferShapeContext* ctx) const override {
    PADDLE_ENFORCE_GT(ctx->Inputs(framework::GradVarName("Out")).size(),
                      1,
                      platform::errors::InvalidArgument(
                          "Number of Inputs(Out@Grad) should be larger than 1."
                          "But received Inputs(Out@Grad)' size = %d .",
                          ctx->Inputs(framework::GradVarName("Out")).size()));
    ctx->SetOutputsDim(framework::GradVarName("X"), ctx->GetInputsDim("X"));
  }

 protected:
  phi::KernelKey GetExpectedKernelType(
      const framework::ExecutionContext& ctx) const override {
    return phi::KernelKey(OperatorWithKernel::IndicateVarDataType(
                              ctx, framework::GradVarName("Out")),
                          ctx.device_context().GetPlace());
  }
};

template <typename T>
class MeshgridGradOpMaker : public framework::SingleGradOpMaker<T> {
 public:
  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;

 protected:
  void Apply(GradOpPtr<T> op) const override {
    op->SetType("meshgrid_grad");
    op->SetInput("X", this->Input("X"));
    op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
    op->SetOutput(framework::GradVarName("X"), this->InputGrad("X", false));
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
DECLARE_INFER_SHAPE_FUNCTOR(meshgrid,
                            MeshgridInferShapeFunctor,
                            PD_INFER_META(phi::MeshgridInferMeta));
REGISTER_OPERATOR(meshgrid,
                  ops::MeshgridOp,
                  ops::MeshgridOpMaker,
                  ops::MeshgridGradOpMaker<paddle::framework::OpDesc>,
                  ops::MeshgridGradOpMaker<paddle::imperative::OpBase>,
                  MeshgridInferShapeFunctor);
REGISTER_OPERATOR(meshgrid_grad, ops::MeshgridGradOp);