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183 lines
6.6 KiB
183 lines
6.6 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 <stdint.h>
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#include <fstream>
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#include <numeric>
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#include "paddle/fluid/framework/data_type.h"
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#include "paddle/fluid/framework/data_type_transform.h"
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#include "paddle/fluid/framework/framework.pb.h"
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/selected_rows.h"
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#include "paddle/fluid/framework/variable.h"
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#include "paddle/fluid/platform/device_context.h"
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#include "paddle/fluid/platform/port.h"
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namespace paddle {
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namespace operators {
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// define LOOKUP_TABLE_PATH for checkpoint notify to save lookup table variables
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// to directory specified.
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constexpr char LOOKUP_TABLE_PATH[] = "kLookupTablePath";
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class SaveOp : public framework::OperatorBase {
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public:
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SaveOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorBase(type, inputs, outputs, attrs) {}
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private:
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void RunImpl(const framework::Scope &scope,
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const platform::Place &place) const override {
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auto iname = Input("X");
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auto *var = scope.FindVar(iname);
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PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s for save_op",
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iname);
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if (var->IsType<framework::LoDTensor>()) {
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SaveLodTensor(place, var);
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} else if (var->IsType<framework::SelectedRows>()) {
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SaveSelectedRows(scope, place, var);
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} else {
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PADDLE_ENFORCE(
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false,
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"SaveOp only support LoDTensor and SelectedRows, %s has wrong type",
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iname);
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}
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}
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void SaveLodTensor(const platform::Place &place,
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framework::Variable *var) const {
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auto filename = Attr<std::string>("file_path");
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auto overwrite = Attr<bool>("overwrite");
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if (FileExists(filename) && !overwrite) {
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PADDLE_THROW("%s is existed, cannot save to it when overwrite=false",
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filename, overwrite);
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}
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MkDirRecursively(DirName(filename).c_str());
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auto &tensor = var->Get<framework::LoDTensor>();
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// get device context from pool
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platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
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auto &dev_ctx = *pool.Get(place);
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// FIXME(yuyang18): We save variable to local file now, but we should change
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// it to save an output stream.
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std::ofstream fout(filename, std::ios::binary);
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PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
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filename);
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auto save_as_fp16 = Attr<bool>("save_as_fp16");
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auto in_dtype = tensor.type();
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auto out_dtype = save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
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if (in_dtype != out_dtype) {
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auto in_kernel_type = framework::OpKernelType(in_dtype, place);
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auto out_kernel_type = framework::OpKernelType(out_dtype, place);
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framework::LoDTensor out;
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framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out);
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// copy LoD info to the new tensor
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out.set_lod(tensor.lod());
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framework::SerializeToStream(fout, out, dev_ctx);
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} else {
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framework::SerializeToStream(fout, tensor, dev_ctx);
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}
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fout.close();
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}
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void SaveSelectedRows(const framework::Scope &scope,
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const platform::Place &place,
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framework::Variable *var) const {
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auto *lt_var = scope.FindVar(LOOKUP_TABLE_PATH)->GetMutable<std::string>();
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PADDLE_ENFORCE(
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lt_var != nullptr,
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"Can not find variable kLookupTablePath for SaveSelectedRows");
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std::string filename = lt_var->data();
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VLOG(4) << "SaveSelectedRows get File name: " << filename;
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MkDirRecursively(DirName(filename).c_str());
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auto &selectedRows = var->Get<framework::SelectedRows>();
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// get device context from pool
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platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
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auto &dev_ctx = *pool.Get(place);
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// FIXME(yuyang18): We save variable to local file now, but we should change
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// it to save an output stream.
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std::ofstream fout(filename, std::ios::binary);
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PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
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filename);
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framework::SerializeToStream(fout, selectedRows, dev_ctx);
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fout.close();
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}
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};
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class SaveOpProtoMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "(Tensor ) Input LoDTensor and SelectedRows to be saved");
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AddComment(R"DOC(
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Save operator
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This operator will serialize and write LoDTensor / SelectedRows variable to file on disk.
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)DOC");
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AddAttr<bool>("overwrite",
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"(boolean, default true)"
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"Overwrite the output file if exist")
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.SetDefault(true);
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AddAttr<bool>("save_as_fp16",
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"(boolean, default false)"
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"If true, the tensor will be converted to float16 data "
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"type and then saved. Otherwise, the tensor will be "
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"directly saved 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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"The \"file_path\" where the variable will be saved.")
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.AddCustomChecker(
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[](const std::string &path) { return !path.empty(); });
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}
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};
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class SaveOpVarTypeInference : public framework::VarTypeInference {
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public:
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void operator()(const framework::OpDesc &op_desc,
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framework::BlockDesc *block) const override {
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auto out_var_name = op_desc.Output(LOOKUP_TABLE_PATH).front();
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auto &out_var = block->FindRecursiveOrCreateVar(out_var_name);
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auto var_type = framework::proto::VarType::RAW;
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out_var.SetType(var_type);
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}
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};
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class SaveOpShapeInference : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *ctx) const override {}
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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(save, ops::SaveOp, paddle::framework::EmptyGradOpMaker,
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ops::SaveOpProtoMaker, ops::SaveOpVarTypeInference,
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ops::SaveOpShapeInference);
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