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Paddle/paddle/fluid/operators/pull_box_extended_sparse_op.cc

158 lines
6.1 KiB

// Copyright (c) 2020 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_extended_sparse_op.h"
namespace paddle {
namespace operators {
class PullBoxExtendedSparseOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE_GE(
ctx->Inputs("Ids").size(), 1UL,
platform::errors::InvalidArgument(
"Inputs(Ids) of PullBoxExtendedSparseOp should not be empty."));
PADDLE_ENFORCE_GE(
ctx->Outputs("Out").size(), 1UL,
platform::errors::InvalidArgument(
"Outputs(Out) of PullBoxExtendedSparseOp should not be empty."));
PADDLE_ENFORCE_GE(ctx->Outputs("OutExtend").size(), 1UL,
platform::errors::InvalidArgument(
"Outputs(OutExtend) of PullBoxExtendedSparseOp "
"should not be empty."));
auto emb_size = static_cast<int64_t>(ctx->Attrs().Get<int>("emb_size"));
auto emb_extended_size =
static_cast<int64_t>(ctx->Attrs().Get<int>("emb_extended_size"));
auto all_ids_dim = ctx->GetInputsDim("Ids");
const size_t n_ids = all_ids_dim.size();
std::vector<framework::DDim> outs_dims;
std::vector<framework::DDim> outs_extended_dims;
outs_dims.resize(n_ids);
outs_extended_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,
platform::errors::InvalidArgument(
"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(emb_size);
outs_dims[i] = framework::make_ddim(out_dim);
auto out_extended_dim = framework::vectorize(
framework::slice_ddim(ids_dims, 0, ids_rank - 1));
out_extended_dim.push_back(emb_extended_size);
outs_extended_dims[i] = framework::make_ddim(out_extended_dim);
}
ctx->SetOutputsDim("Out", outs_dims);
ctx->SetOutputsDim("OutExtend", outs_extended_dims);
for (size_t i = 0; i < n_ids; ++i) {
ctx->ShareLoD("Ids", "Out", i, i);
ctx->ShareLoD("Ids", "OutExtend", i, i);
}
}
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
return framework::OpKernelType(framework::proto::VarType::FP32,
ctx.device_context());
}
};
class PullBoxExtendedSparseOpMaker : 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();
AddOutput("OutExtend", "The lookup extended results tensors.")
.AsDuplicable();
AddAttr<int>("emb_size", "(int, the embedding hidden size").SetDefault(1);
AddAttr<int>("emb_extended_size",
"(int, the extended_embedding hidden size")
.SetDefault(128);
AddComment(R"DOC(
Pull Box Extended 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");
}
};
template <typename T>
class PushBoxExtendedSparseOpMaker : public framework::SingleGradOpMaker<T> {
public:
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
protected:
void Apply(GradOpPtr<T> op) const override {
op->SetType("push_box_extended_sparse");
op->SetInput("Ids", this->Input("Ids"));
op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
op->SetInput(framework::GradVarName("OutExtend"),
this->OutputGrad("OutExtend"));
op->SetOutput(framework::GradVarName("Out"), this->OutputGrad("Out"));
op->SetAttrMap(this->Attrs());
}
};
class PushBoxExtendedSparseOp : 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_extended_sparse, ops::PullBoxExtendedSparseOp,
ops::PullBoxExtendedSparseOpMaker,
ops::PushBoxExtendedSparseOpMaker<paddle::framework::OpDesc>,
ops::PushBoxExtendedSparseOpMaker<paddle::imperative::OpBase>);
REGISTER_OPERATOR(push_box_extended_sparse, ops::PushBoxExtendedSparseOp);
REGISTER_OP_CPU_KERNEL(pull_box_extended_sparse,
ops::PullBoxExtendedSparseCPUKernel<float>,
ops::PullBoxExtendedSparseCPUKernel<double>);
REGISTER_OP_CPU_KERNEL(push_box_extended_sparse,
ops::PushBoxExtendedSparseCPUKernel<float>,
ops::PushBoxExtendedSparseCPUKernel<double>);