svd_op.cc

// Copyright (c) 2021 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 <unordered_map>
#include <vector>

#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/core/ddim.h"
#include "paddle/phi/infermeta/unary.h"

namespace paddle {
namespace operators {

class SvdOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;
};

class SvdOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "(Tensor), The input tensor of svd op.");
    AddOutput("U", "(Tensor), The output U tensor of svd op.");
    AddOutput("S", "(Tensor), The output S tensor of svd op.");
    AddOutput("VH", "(Tensor), The output VH tensor of svd op.");
    AddAttr<bool>("full_matrices",
                  "(bool, default false) Only Compute the thin U and V"
                  "when set as True, the gradient have some random "
                  "attribute.")
        .SetDefault(false);
    AddComment(R"DOC(
Svd Operator.

This operator is used to perform SVD operation for batched matrics $X$.
$$U, S, VH = svd(X)$$

)DOC");
  }
};

class SvdGradOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;
  void InferShape(framework::InferShapeContext* ctx) const override {
    OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("U")),
                   "Input",
                   "U@Grad",
                   "SvdGrad");
    OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("VH")),
                   "Input",
                   "VH@Grad",
                   "SvdGrad");
    OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("S")),
                   "Input",
                   "S@Grad",
                   "SvdGrad");
    OP_INOUT_CHECK(ctx->HasInput("U"), "Input", "U", "SvdGrad");
    OP_INOUT_CHECK(ctx->HasInput("S"), "Input", "S", "SvdGrad");
    OP_INOUT_CHECK(ctx->HasInput("VH"), "Input", "VH", "SvdGrad");
    OP_INOUT_CHECK(ctx->HasOutput(framework::GradVarName("X")),
                   "Output",
                   "X@Grad",
                   "SvdGrad");

    auto d_x = ctx->GetInputDim(("X"));
    ctx->SetOutputDim(framework::GradVarName("X"), d_x);
  }

 protected:
  framework::OpKernelType GetExpectedKernelType(
      const framework::ExecutionContext& ctx) const override {
    auto dtype = OperatorWithKernel::IndicateVarDataType(ctx, "X");
    return framework::OpKernelType(dtype, ctx.GetPlace());
  }
};

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

  void Apply(GradOpPtr<T> retv) const override {
    retv->SetType("svd_grad");
    retv->SetInput(framework::GradVarName("U"), this->OutputGrad("U"));
    retv->SetInput(framework::GradVarName("VH"), this->OutputGrad("VH"));
    retv->SetInput(framework::GradVarName("S"), this->OutputGrad("S"));
    retv->SetInput("U", this->Output("U"));
    retv->SetInput("VH", this->Output("VH"));
    retv->SetInput("S", this->Output("S"));
    retv->SetInput("X", this->Input("X"));
    retv->SetAttrMap(this->Attrs());
    retv->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;

DECLARE_INFER_SHAPE_FUNCTOR(svd,
                            SvdInferShapeFunctor,
                            PD_INFER_META(phi::SvdInferMeta));

REGISTER_OPERATOR(svd,
                  ops::SvdOp,
                  ops::SvdOpMaker,
                  ops::SvdGradMaker<paddle::framework::OpDesc>,
                  ops::SvdGradMaker<paddle::imperative::OpBase>,
                  SvdInferShapeFunctor);

REGISTER_OPERATOR(svd_grad, ops::SvdGradOp);