gather_p_op.cc

// Copyright (c) 2022 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 "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"

namespace paddle {
namespace framework {
class InferShapeContext;
class VarDesc;
}  // namespace framework
}  // namespace paddle

namespace paddle {
namespace operators {
class GatherPrimOp : public framework::OperatorBase {
 public:
  GatherPrimOp(const std::string &type,
               const framework::VariableNameMap &inputs,
               const framework::VariableNameMap &outputs,
               const framework::AttributeMap &attrs)
      : framework::OperatorBase(type, inputs, outputs, attrs) {}
  void RunImpl(const framework::Scope &scope,
               const platform::Place &dev_place) const override {
    PADDLE_THROW(platform::errors::Unimplemented(
        "Prim operator gather_p should not be excuted directly"));
  }
};

class GatherPrimOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "(Tensor), The input tensor of gather_p op.");
    AddInput("IndexTensor",
             "(Tensor), The index tensor of gather_p op, which is a 1D tensor.")
        .AsDispensable();
    AddOutput("Y", "(Tensor), The output tensor of gather_p op.");
    AddAttr<int64_t>("axis", "(int64_t), The axis along which to gather.");
    AddAttr<std::vector<int64_t>>(
        "index", "(std::vector<int64_t>) The index of gather_p op")
        .SetDefault({0});
    AddComment(R"DOC(
Autograd primitive gather_p operator.
)DOC");
  }
};

class GatherPrimOpShapeInference : public framework::InferShapeBase {
 public:
  void operator()(framework::InferShapeContext *ctx) const override {
    framework::InferShapeVarPtr x_var_ptr = ctx->GetInputVarPtrs("X")[0];
    framework::InferShapeVarPtr y_var_ptr = ctx->GetOutputVarPtrs("Y")[0];
    int64_t num_index = 0;
    if (ctx->HasInput("IndexTensor")) {
      framework::InferShapeVarPtr index_var_ptr =
          ctx->GetInputVarPtrs("IndexTensor")[0];
      framework::VarDesc *index_var =
          BOOST_GET(framework::VarDesc *, index_var_ptr);
      auto index_shape = index_var->GetShape();
      PADDLE_ENFORCE_EQ(index_shape.size(), 1,
                        platform::errors::InvalidArgument(
                            "The index tensor should be a 1D tensor,"
                            "but get rank %d",
                            index_shape.size()));
      num_index = index_shape[0];
    } else {
      num_index = ctx->Attrs().Get<std::vector<int64_t>>("index").size();
    }
    auto axis = ctx->Attrs().Get<int64_t>("axis");

    framework::VarDesc *x_var = BOOST_GET(framework::VarDesc *, x_var_ptr);
    auto x_shape = x_var->GetShape();
    x_shape[axis] = num_index;

    BOOST_GET(framework::VarDesc *, y_var_ptr)->SetShape(x_shape);
  }
};

class GatherPrimOpVarTypeInference
    : public framework::StaticGraphVarTypeInference {
 public:
  void operator()(framework::InferVarTypeContext *ctx) const override {
    auto x_name = Input(ctx, "X")[0];
    auto y_name = Output(ctx, "Y")[0];
    if (ctx->HasInput("IndexTensor")) {
      auto index_name = Input(ctx, "IndexTensor")[0];
      auto index_dtype = GetDataType(ctx, index_name);
      PADDLE_ENFORCE_EQ(
          index_dtype, framework::proto::VarType_Type_INT32,
          platform::errors::InvalidArgument(
              "The datatype of input tensor should be VarType_Type_INT32(%d), "
              "but get %d",
              framework::proto::VarType_Type_INT32, index_dtype));
    }
    SetType(ctx, y_name, GetType(ctx, x_name));
    SetDataType(ctx, y_name, GetDataType(ctx, x_name));
  }
};

}  // namespace operators
}  // namespace paddle

REGISTER_OPERATOR(gather_p, paddle::operators::GatherPrimOp,
                  paddle::operators::GatherPrimOpMaker,
                  paddle::operators::GatherPrimOpShapeInference,
                  paddle::operators::GatherPrimOpVarTypeInference);