wehub-resource-sync
82 lines
2.9 KiB
C++
82 lines
2.9 KiB
C++
/* Copyright (c) 2018 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/load_combine_op.h"
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#include <string>
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#include <vector>
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namespace paddle::operators {
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class LoadCombineOp : 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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protected:
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phi::KernelKey GetExpectedKernelType(
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const framework::ExecutionContext &ctx) const override {
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return phi::KernelKey(framework::proto::VarType::FP32, ctx.GetPlace());
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}
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};
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class LoadCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddOutput("Out",
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"(vector) The output DenseTensors that will be read from the "
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"input file.")
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.AsDuplicable();
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AddAttr<bool>(
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"load_as_fp16",
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"(boolean, default false)"
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"If true, the tensor will be first loaded and then "
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"converted to float16 data type. Otherwise, the tensor will be "
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"directly loaded without data type conversion.")
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.SetDefault(false);
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AddAttr<std::string>("file_path",
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"(string) "
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"DenseTensors will be loaded from \"file_path\".")
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.AddCustomChecker(
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[](const std::string &path) { return !path.empty(); });
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AddAttr<bool>("model_from_memory",
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"(boolean, default false)"
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"If true, file_path is in memory, and DenseTensors will be "
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"loaded directly from memory")
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.SetDefault(false);
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AddComment(R"DOC(
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LoadCombine Operator.
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LoadCombine operator loads DenseTensor variables from a file, which could be
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loaded in memory already. The file should contain one or more DenseTensors
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serialized using the SaveCombine operator. The
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LoadCombine operator applies a deserialization strategy to appropriately load
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the DenseTensors, and this strategy complements the serialization strategy used
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in the SaveCombine operator. Hence, the LoadCombine operator is tightly coupled
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with the SaveCombine operator, and can only deserialize one or more DenseTensors
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that were saved using the SaveCombine operator.
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)DOC");
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}
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};
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} // namespace paddle::operators
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namespace ops = paddle::operators; // NOLINT
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REGISTER_OPERATOR(load_combine,
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ops::LoadCombineOp,
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ops::LoadCombineOpProtoMaker);
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