/* Copyright (c) 2016 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 #include #include #include #include "paddle/fluid/framework/data_type.h" #include "paddle/fluid/framework/data_type_transform.h" #include "paddle/fluid/framework/framework.pb.h" #include "paddle/fluid/framework/lod_tensor.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/selected_rows.h" #include "paddle/fluid/framework/variable.h" #include "paddle/fluid/platform/device_context.h" namespace paddle { namespace operators { // TODO(yuyang18): If the functions below are needed by other files, move them // to paddle::filesystem namespace. constexpr char kSEP = '/'; static bool FileExists(const std::string &filepath) { struct stat buffer; return (stat(filepath.c_str(), &buffer) == 0); } static std::string DirName(const std::string &filepath) { auto pos = filepath.rfind(kSEP); if (pos == std::string::npos) { return ""; } return filepath.substr(0, pos); } static void MkDir(const char *path) { if (mkdir(path, 0755)) { PADDLE_ENFORCE_EQ(errno, EEXIST, "%s mkdir failed!", path); } } static void MkDirRecursively(const char *fullpath) { if (*fullpath == '\0') return; // empty string if (FileExists(fullpath)) return; MkDirRecursively(DirName(fullpath).c_str()); MkDir(fullpath); } class SaveOp : public framework::OperatorBase { public: SaveOp(const std::string &type, const framework::VariableNameMap &inputs, const framework::VariableNameMap &outputs, const framework::AttributeMap &attrs) : OperatorBase(type, inputs, outputs, attrs) {} private: void RunImpl(const framework::Scope &scope, const platform::Place &place) const override { auto iname = Input("X"); auto *var = scope.FindVar(iname); PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s for save_op", iname); if (var->IsType()) { SaveLodTensor(place, var); } else if (var->IsType()) { SaveSelectedRows(scope, place, var); } else { PADDLE_ENFORCE( false, "SaveOp only support LoDTensor and SelectedRows, %s has wrong type", iname); } } void SaveLodTensor( const platform::Place &place, framework::Variable *var) const { auto filename = Attr("file_path"); auto overwrite = Attr("overwrite"); if (FileExists(filename) && !overwrite) { PADDLE_THROW("%s is existed, cannot save to it when overwrite=false", filename, overwrite); } MkDirRecursively(DirName(filename).c_str()); auto &tensor = var->Get(); // get device context from pool platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance(); auto &dev_ctx = *pool.Get(place); // FIXME(yuyang18): We save variable to local file now, but we should change // it to save an output stream. std::ofstream fout(filename); PADDLE_ENFORCE(static_cast(fout), "Cannot open %s to write", filename); auto save_as_fp16 = Attr("save_as_fp16"); auto in_dtype = framework::ToDataType(tensor.type()); auto out_dtype = save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype; if (in_dtype != out_dtype) { auto in_kernel_type = framework::OpKernelType(in_dtype, place); auto out_kernel_type = framework::OpKernelType(out_dtype, place); framework::LoDTensor out; framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out); // copy LoD info to the new tensor out.set_lod(tensor.lod()); framework::SerializeToStream(fout, out, dev_ctx); } else { framework::SerializeToStream(fout, tensor, dev_ctx); } fout.close(); } void SaveSelectedRows(const framework::Scope &scope, const platform::Place &place, framework::Variable *var) const { auto lt_varname = string::Sprintf("%s.path", Input("X")); auto *lt_var = scope.FindVar(lt_varname)->GetMutable(); PADDLE_ENFORCE(lt_var != nullptr, "Cannot find variable %s for SaveSelectedRows", lt_varname); std::string filename = lt_var->data(); VLOG(4) << "SaveSelectedRows get File name: " << filename; auto &selectedRows = var->Get(); // get device context from pool platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance(); auto &dev_ctx = *pool.Get(place); // FIXME(yuyang18): We save variable to local file now, but we should change // it to save an output stream. std::ofstream fout(filename); PADDLE_ENFORCE(static_cast(fout), "Cannot open %s to write", filename); framework::SerializeToStream(fout, selectedRows, dev_ctx); fout.close(); } }; class SaveOpProtoMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("X", "(Tensor ) Input LoDTensor and SelectedRows to be saved"); AddComment(R"DOC( Save operator This operator will serialize and write a tensor/selected rows variable to file on disk. )DOC"); AddAttr("overwrite", "(boolean, default true)" "Overwrite the output file if exist") .SetDefault(true); AddAttr("save_as_fp16", "(boolean, default false)" "If true, the tensor will be converted to float16 data " "type and then saved. Otherwise, the tensor will be " "directly saved without data type conversion.") .SetDefault(false); AddAttr("file_path", "(string)" "The \"file_path\" where the variable will be saved.") .AddCustomChecker( [](const std::string &path) { return !path.empty(); }); } }; class SaveOpVarTypeInference : public framework::VarTypeInference { public: void operator()(const framework::OpDesc &op_desc, framework::BlockDesc *block) const override { auto out_var_name = op_desc.Output("loopup_table_path").front(); auto &out_var = block->FindRecursiveOrCreateVar(out_var_name); auto var_type = framework::proto::VarType::RAW; out_var.SetType(var_type); } }; class SaveOpShapeInference : public framework::InferShapeBase { public: void operator()(framework::InferShapeContext *ctx) const override {} }; } } // namespace operators // namespace paddle namespace ops = paddle::operators; REGISTER_OPERATOR(save, ops::SaveOp, paddle::framework::EmptyGradOpMaker, ops::SaveOpProtoMaker, ops::SaveOpVarTypeInference, ops::SaveOpShapeInference);