top_k_op.cc

/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

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/operators/top_k_op.h"

namespace paddle {
namespace operators {

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

 protected:
  void InferShape(const framework::InferShapeContext &ctx) const override {
    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
                            "Input(X) of TopkOp should not be null.");
    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
                            "Output(Out) of TopkOp should not be null.");
    PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Indices"),
                            "Output(Indices) of TopkOp should not be null.");

    auto *input = ctx.Input<framework::Tensor>("X");
    const int k = static_cast<int>(ctx.Attr<int>("k"));

    PADDLE_ENFORCE_GE(k, 1, "k must >= 1");
    PADDLE_ENFORCE_GE(input->dims().size(), 1, "input must have >= 1d shape");
    PADDLE_ENFORCE_GE(input->dims()[input->dims().size() - 1], k,
                      "input must have >= k columns");

    framework::DDim dims = input->dims();
    dims[dims.size() - 1] = k;
    ctx.Output<framework::LoDTensor>("Out")->Resize(dims);
    ctx.Output<framework::LoDTensor>("Indices")->Resize(dims);
  }
};

class TopkOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  TopkOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("X", "The input of Topk op");
    AddOutput("Out", "The output tensor of Topk op");
    AddOutput("Indices", "The indices of Topk elements of input");
    AddComment(
        R"DOC(If the input is a vector (1d tensor), finds the k largest entries in the vector and outputs their values and indices as vectors. Thus values[j] is the j-th largest entry in input, and its index is indices[j].

    For matrices, computes the top k entries in each row. )DOC");
    AddAttr<int>("k",
                 "Number of top elements to look for along the last "
                 "dimension (along each row for matrices).")
        .SetDefault(1);
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT(top_k, ops::TopkOp, ops::TopkOpMaker);
REGISTER_OP_CPU_KERNEL(top_k,
                       ops::TopkKernel<paddle::platform::CPUPlace, float>);