/* 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 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 out_dims; int num_hash = ctx->Attrs().Get("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("num_hash", "").SetDefault(1); AddAttr("mod_by", "").SetDefault(100000); AddAttr(framework::kAllKernelsMustComputeRuntimeShape, "Skip calling InferShape() function in the runtime.") .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, ops::HashKernel);