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129 lines
4.9 KiB
129 lines
4.9 KiB
/* Copyright (c) 2020 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/lookup_table_dequant_op.h"
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#include <memory>
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#include "paddle/fluid/framework/no_need_buffer_vars_inference.h"
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#include "paddle/fluid/framework/var_type_inference.h"
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namespace paddle {
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namespace operators {
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class LookupTableDequantOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE_EQ(
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ctx->HasInput("W"), true,
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platform::errors::InvalidArgument(
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"Input(W) of LookupTableDequantOp should not be null."));
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PADDLE_ENFORCE_EQ(
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ctx->HasInput("Ids"), true,
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platform::errors::InvalidArgument(
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"Input(Ids) of LookupTableDequantOp should not be null."));
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PADDLE_ENFORCE_EQ(
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ctx->HasOutput("Out"), true,
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platform::errors::InvalidArgument(
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"Output(Out) of LookupTableDequantOp 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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int ids_rank = ids_dims.size();
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VLOG(5) << "ids rank is " << ids_rank << std::endl;
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PADDLE_ENFORCE_EQ(
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table_dims.size(), 2,
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platform::errors::InvalidArgument(
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"ShapeError: The dimensions of the 'lookup table' must be 2. "
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"But received lookup table's dimensions = %d, "
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"lookup table's shape = [%s].",
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table_dims.size(), table_dims));
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PADDLE_ENFORCE_EQ(
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ids_dims[ids_rank - 1], 1,
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platform::errors::InvalidArgument(
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"ShapeError: The last dimensions of the 'Ids' tensor must be 1. "
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"But received Ids's last dimensions = %d, Ids's shape = [%s].",
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ids_dims[ids_rank - 1], ids_dims));
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auto output_dims =
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framework::vectorize(framework::slice_ddim(ids_dims, 0, ids_rank - 1));
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PADDLE_ENFORCE_GE(table_dims[1], 2,
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platform::errors::InvalidArgument(
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"the second dim of table_dims should be "
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"greater or equal to 2, but the actual shape "
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"is [%s]",
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table_dims));
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output_dims.push_back((table_dims[1] - 2) * 4);
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ctx->SetOutputDim("Out", framework::make_ddim(output_dims));
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if (ctx->GetOutputsVarType("Out")[0] ==
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framework::proto::VarType::LOD_TENSOR) {
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ctx->ShareLoD("Ids", /*->*/ "Out");
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}
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override {
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auto data_type = OperatorWithKernel::IndicateVarDataType(ctx, "W");
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return framework::OpKernelType(data_type, ctx.device_context());
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}
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};
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class LookupTableDequantOpMaker : 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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"(Tensor) The input represents embedding tensors, "
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"This tensor is a quantized tensor");
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AddInput("Ids",
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"An input with type int64 "
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"contains the ids to be looked up in W. "
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"The last dimension size must be 1.");
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AddOutput("Out", "The lookup results, which have the 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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AddComment(R"DOC(
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Lookup Table Dequant Operator.
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The `W` input is a quantized parameter for the sake of saving memories.
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This operator first index embeddings with `Ids`,
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then dequantizes them and contact them as output (`Out`).
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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 information with input Ids.
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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(
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lookup_table_dequant, ops::LookupTableDequantOp,
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ops::LookupTableDequantOpMaker,
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paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
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paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OP_CPU_KERNEL(lookup_table_dequant,
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ops::LookupTableDequantKernel<float>);
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