// Copyright (c) 2019 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/pull_box_sparse_op.h" namespace paddle { namespace operators { class PullBoxSparseOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override { PADDLE_ENFORCE_GE(ctx->Inputs("Ids").size(), 1UL, "Inputs(Ids) of PullBoxSparseOp should not be empty."); PADDLE_ENFORCE_GE(ctx->Outputs("Out").size(), 1UL, "Outputs(Out) of PullBoxSparseOp should not be empty."); auto hidden_size = static_cast(ctx->Attrs().Get("size")); auto all_ids_dim = ctx->GetInputsDim("Ids"); const size_t n_ids = all_ids_dim.size(); std::vector outs_dims; outs_dims.resize(n_ids); for (size_t i = 0; i < n_ids; ++i) { const auto ids_dims = all_ids_dim[i]; int ids_rank = ids_dims.size(); PADDLE_ENFORCE_EQ(ids_dims[ids_rank - 1], 1, "Shape error in %lu id, the last dimension of the " "'Ids' tensor must be 1.", i); auto out_dim = framework::vectorize( framework::slice_ddim(ids_dims, 0, ids_rank - 1)); out_dim.push_back(hidden_size); outs_dims[i] = framework::make_ddim(out_dim); } ctx->SetOutputsDim("Out", outs_dims); for (size_t i = 0; i < n_ids; ++i) { ctx->ShareLoD("Ids", "Out", i, i); } } protected: framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext& ctx) const override { return framework::OpKernelType(framework::proto::VarType::FP32, ctx.device_context()); } }; class PullBoxSparseOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("Ids", "Input tensors with type int32 or int64 " "contains the ids to be looked up in BoxPS. " "The last dimension size must be 1.") .AsDuplicable(); AddOutput("Out", "The lookup results tensors.").AsDuplicable(); AddAttr("size", "(int, the embedding hidden size").SetDefault(1); AddComment(R"DOC( Pull Box Sparse Operator. This operator is used to perform lookups on the BoxPS, then concatenated into a dense tensor. The input Ids can carry the LoD (Level of Details) information, or not. And the output only shares the LoD information with input Ids. )DOC"); } }; class PushBoxSparseOpDescMaker : public framework::SingleGradOpDescMaker { public: using framework::SingleGradOpDescMaker::SingleGradOpDescMaker; protected: std::unique_ptr Apply() const override { std::unique_ptr op(new framework::OpDesc()); op->SetType("push_box_sparse"); op->SetInput("Ids", Input("Ids")); op->SetInput(framework::GradVarName("Out"), OutputGrad("Out")); op->SetOutput(framework::GradVarName("Out"), OutputGrad("Out")); op->SetAttrMap(Attrs()); return op; } }; class PushBoxSparseOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override {} protected: framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext& ctx) const override { return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( ctx, framework::GradVarName("Out")), ctx.device_context()); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OPERATOR(pull_box_sparse, ops::PullBoxSparseOp, ops::PullBoxSparseOpMaker, ops::PushBoxSparseOpDescMaker); REGISTER_OPERATOR(push_box_sparse, ops::PushBoxSparseOp); REGISTER_OP_CPU_KERNEL(pull_box_sparse, ops::PullBoxSparseCPUKernel) REGISTER_OP_CPU_KERNEL(push_box_sparse, ops::PushBoxSparseCPUKernel)