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93 lines
3.3 KiB
93 lines
3.3 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/operators/lookup_table_op.h"
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namespace paddle {
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namespace operators {
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class LookupTableOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContextBase* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("W"),
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"Input(W) of LookupTableOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Ids"),
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"Input(Ids) of LookupTableOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of LookupTableOp should not be null.");
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auto table_dims = ctx->GetInputDim("W");
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auto ids_dims = ctx->GetInputDim("Ids");
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ctx->SetOutputDim("Out", {ids_dims[0], table_dims[1]});
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ctx->ShareLoD("Ids", /*->*/ "Out");
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}
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framework::DataType IndicateDataType(
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const framework::ExecutionContext& ctx) const override {
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return framework::ToDataType(ctx.Input<Tensor>("W")->type());
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}
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};
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class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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LookupTableOpMaker(framework::OpProto* proto,
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framework::OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("W",
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"An input represents embedding tensors,"
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" which is a learnable parameter.");
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AddInput("Ids",
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"An input with type int32 or int64"
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"contains the ids to be looked up in W.");
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AddOutput("Out", "The lookup results, which have the same type with W.");
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AddComment(R"DOC(
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This operator is used to perform lookups on the parameter W,
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then concatenated into a dense tensor.
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The input `Ids` can carry the LoD (Level of Details) information,
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or not. And the output only shares the LoD with input `Ids`.
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)DOC");
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}
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};
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class LookupTableOpGrad : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContextBase* ctx) const override {
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auto table_dims = ctx->GetInputDim("W");
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ctx->SetOutputDim(framework::GradVarName("W"), table_dims);
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}
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framework::DataType IndicateDataType(
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const framework::ExecutionContext& ctx) const override {
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return framework::ToDataType(ctx.Input<Tensor>("W")->type());
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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(lookup_table, ops::LookupTableOp, ops::LookupTableOpMaker,
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lookup_table_grad, ops::LookupTableOpGrad);
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REGISTER_OP_CPU_KERNEL(lookup_table, ops::LookupTableKernel<float>);
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REGISTER_OP_CPU_KERNEL(lookup_table_grad, ops::LookupTableGradKernel<float>);
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