hash_op.cc

/* Copyright (c) 2016 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/operators/hash_op.h"
#include <string>

namespace paddle {
namespace operators {

class HashOp : public framework::OperatorWithKernel {
 public:
  HashOp(const std::string &type, const framework::VariableNameMap &inputs,
         const framework::VariableNameMap &outputs,
         const framework::AttributeMap &attrs)
      : OperatorWithKernel(type, inputs, outputs, attrs) {}

  void InferShape(framework::InferShapeContext *ctx) const override {
    PADDLE_ENFORCE(ctx->HasInput("X"),
                   "Input(X) of HashOp should not be null.");
    PADDLE_ENFORCE(ctx->HasOutput("Out"),
                   "Output(Out) of HashOp should not be null.");

    auto dims = ctx->GetInputDim("X");
    PADDLE_ENFORCE_EQ(dims.size(), 2UL,
                      "The input of hash_op's dimensions must be 2");
    std::vector<int64_t> out_dims;
    int num_hash = ctx->Attrs().Get<int>("num_hash");
    HashOutputSize(dims, out_dims, num_hash);

    ctx->SetOutputDim("Out", framework::make_ddim(out_dims));
    ctx->ShareLoD("X", /*->*/ "Out");
  }
};

class HashOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "(Tensor) Input tensor of scale operator.");
    AddOutput("Out", "(Tensor) Output tensor of scale operator.");
    AddComment(R"DOC(
**Hash Operator**
$$Out = scale * X$$
)DOC");
    AddAttr<int>("num_hash", "").SetDefault(1);
    AddAttr<int>("mod_by", "").SetDefault(100000);
    AddAttr<bool>(
        "all_kernels_must_compute_runtime_shape",
        "(boolean, default true) "
        "An attribute to speed up OperatorWithKernel::RunImpl."
        "If true, all the kernels of this Op would compute runtime "
        "shape, but skip infershape in runtime. Note that it is a temporal "
        "attribute, please do DOT set it in python layer.")
        .SetDefault(true);
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;

REGISTER_OP_WITHOUT_GRADIENT(hash, ops::HashOp, ops::HashOpMaker);
REGISTER_OP_CPU_KERNEL(hash, ops::HashKernel<int>, ops::HashKernel<int64_t>);