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68 lines
2.5 KiB
68 lines
2.5 KiB
/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/hash_op.h"
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#include <string>
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namespace paddle {
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namespace operators {
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class HashOp : public framework::OperatorWithKernel {
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public:
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HashOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorWithKernel(type, inputs, outputs, attrs) {}
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void InferShape(framework::InferShapeContext *ctx) const override {
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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Hash");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Hash");
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auto dims = ctx->GetInputDim("X");
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PADDLE_ENFORCE_EQ(dims.size(), 2UL,
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platform::errors::InvalidArgument(
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"The input of hash_op's dimensions must be 2"));
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std::vector<int64_t> out_dims;
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int num_hash = ctx->Attrs().Get<int>("num_hash");
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HashOutputSize(dims, out_dims, num_hash);
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ctx->SetOutputDim("Out", framework::make_ddim(out_dims));
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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};
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class HashOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "(Tensor) Input tensor of hash operator.");
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AddOutput("Out", "(Tensor) Output tensor of hash operator.");
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AddComment(R"DOC(
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Execute `num_hash` times xxHash algorithm on all elements on second dimension of input.
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)DOC");
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AddAttr<int>("num_hash", "").SetDefault(1);
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AddAttr<int64_t>("mod_by", "").SetDefault(100000);
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AddAttr<bool>(framework::kAllKernelsMustComputeRuntimeShape,
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"Skip calling InferShape() function in the runtime.")
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.SetDefault(true);
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_WITHOUT_GRADIENT(hash, ops::HashOp, ops::HashOpMaker);
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REGISTER_OP_CPU_KERNEL(hash, ops::HashKernel<int>, ops::HashKernel<int64_t>);
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