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121 lines
4.5 KiB
121 lines
4.5 KiB
/* Copyright (c) 2016 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 <algorithm>
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#include "paddle/fluid/framework/data_type.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/math_function.h"
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namespace paddle {
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namespace operators {
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constexpr int64_t kNoPadding = -1;
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class LookupSparseTableInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of LookupSparseTableOp should not be null.");
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auto shape_w = ctx->GetInputDim("W");
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auto shape_ids = ctx->GetInputDim("Ids");
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shape_w[0] = shape_ids.size();
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ctx->SetOutputDim("Out", shape_w);
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}
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};
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class LookupSparseTableOp : public framework::OperatorBase {
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public:
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using framework::OperatorBase::OperatorBase;
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private:
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void RunImpl(const framework::Scope &scope,
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const platform::Place &dev_place) const override {
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auto out_var = scope.FindVar(Output("Out"));
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auto w_var = scope.FindVar(Input("W"));
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auto ids_var = scope.FindVar(Input("Ids"));
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auto is_test = Attr<bool>("is_test");
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PADDLE_ENFORCE(out_var->IsType<framework::LoDTensor>(),
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"The type of Out var should be LodTensor.");
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PADDLE_ENFORCE(w_var->IsType<framework::SelectedRows>(),
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"The type of W var should be SelectedRows.");
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PADDLE_ENFORCE(ids_var->IsType<framework::LoDTensor>(),
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"The type of Ids var should be LoDTensor.");
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auto &ids_t = ids_var->Get<framework::LoDTensor>();
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auto out_t = out_var->GetMutable<framework::LoDTensor>();
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auto w_t = w_var->GetMutable<framework::SelectedRows>();
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// TODO(Yancey1989): support CUDA Place for the sparse table
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platform::CPUPlace cpu;
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auto out_shape = w_t->value().dims();
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out_shape[0] = ids_t.numel();
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out_t->Resize(out_shape);
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out_t->mutable_data(cpu, w_t->value().type());
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PADDLE_ENFORCE_EQ(w_t->value().type(), framework::proto::VarType::FP32,
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"The sparse table only support FP32");
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w_t->Get(ids_t, out_t, true, is_test);
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out_t->set_lod(ids_t.lod());
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}
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};
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class LookupSparseTableOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("W",
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"(SelectedRows) The input represents embedding table, "
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"which is a learnable parameter.");
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AddInput("Ids",
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"(LoDTensor) Ids's type should be LoDTensor"
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"THe ids to be looked up in W.");
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AddOutput("Out",
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"(LoDTensor) The lookup results, which have the "
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"same type as W.");
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AddAttr<int64_t>("padding_idx",
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"(int64, default -1) "
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"If the value is -1, it makes no effect to lookup. "
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"Otherwise the given value indicates padding the output "
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"with zeros whenever lookup encounters it in Ids.")
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.SetDefault(kNoPadding);
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AddAttr<bool>("auto_grown_table",
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"(bool default false)"
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"Whether create new value if for nonexistent key.")
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.SetDefault(true);
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AddAttr<bool>("is_test",
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"In test mode, lookup_sparse_table will "
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"return a 0 for unknown id")
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.SetDefault(false);
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AddComment(R"DOC(
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Lookup Sprase Tablel Operator.
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This operator is used to perform lookup on parameter W,
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then concatenated into a sparse tensor.
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The type of Ids(Input) is SelectedRows, the rows of Ids contains
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the ids to be looked up in W;
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if the Id is not in the sparse table, this operator will return a
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random value and set the value into the table for the next looking up.
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)DOC");
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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_OPERATOR(lookup_sparse_table, ops::LookupSparseTableOp,
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ops::LookupSparseTableInferShape,
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ops::LookupSparseTableOpMaker,
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paddle::framework::EmptyGradOpMaker);
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