/* Copyright (c) 2018 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 "framework/loader.h" #include "framework/lod_tensor.h" #include "framework/program/program-optimize/program_optimize.h" #ifdef PADDLE_MOBILE_CL #include "framework/cl/cl_image.h" #endif namespace paddle_mobile { namespace framework { template void Loader::InitMemoryFromProgram( const std::shared_ptr &originProgramDesc, const std::shared_ptr &scope) { for (const auto &block : originProgramDesc.get()->Blocks()) { for (const auto &var_desc : block->Vars()) { auto var = scope.get()->Var(var_desc->Name()); if (var_desc->Type() == VARTYPE_TYPE_LOD_TENSOR) { if (var_desc->Persistable()) { auto dim = var_desc->Tensor_desc().Dims(); auto tensor = var->GetMutable(); tensor->Resize(make_ddim(dim)); } else { auto dim = var_desc->Tensor_desc().Dims(); if (dim.size() == 0) { auto tensor = var->GetMutable(); framework::DDim dDim = {0}; tensor->Resize(dDim); } else { for (auto &d : dim) { if (d < 0) { d *= -1; } } auto tensor = var->GetMutable(); tensor->Resize(make_ddim(dim)); } } } else { // TODO(codeWorm) } } } } #ifdef PADDLE_MOBILE_CL template <> void Loader::InitMemoryFromProgram( const std::shared_ptr &originProgramDesc, const std::shared_ptr &scope) { for (const auto &block : originProgramDesc.get()->Blocks()) { for (const auto &var_desc : block->Vars()) { auto var = scope.get()->Var(var_desc->Name()); if (var_desc->Type() == VARTYPE_TYPE_LOD_TENSOR) { if (var_desc->Persistable()) { auto dim = var_desc->Tensor_desc().Dims(); auto cl_image = var->GetMutable(); cl_image->Resize(make_ddim(dim)); } else { auto dim = var_desc->Tensor_desc().Dims(); PADDLE_MOBILE_ENFORCE(dim.size() > 0, "dim size is 0"); dim[0] = 1; auto cl_image = var->GetMutable(); cl_image->Resize(make_ddim(dim)); } } else { // TODO(codeWorm) } } } } template <> const Program Loader::LoadCombinedMemory( size_t read_size, const uint8_t *buf, size_t combined_params_len, uint8_t *combined_params_buf, bool optimize, bool quantification) { bool can_add_split = false; PaddleMobile__Framework__Proto__ProgramDesc *c_program; PADDLE_MOBILE_ENFORCE(buf != nullptr, "read from __model__ is null"); c_program = paddle_mobile__framework__proto__program_desc__unpack( nullptr, read_size, buf); // PADDLE_MOBILE_ENFORCE(c_program != nullptr, "program is null"); // DLOG << "n_ops: " << (*c_program->blocks)->n_ops; // auto originProgramDesc = std::make_shared(c_program); Program program; program.combined = true; program.originProgram = originProgramDesc; program.quantification = quantification; program.combined_params_len = combined_params_len; program.combined_params_buf = combined_params_buf; auto scope = std::make_shared(); program.scope = scope; InitMemoryFromProgram(originProgramDesc, scope); if (optimize) { ProgramOptimize program_optimize; program.optimizeProgram = program_optimize.FusionOptimize(originProgramDesc, can_add_split); if (!program.optimizeProgram) { program.optimizeProgram = originProgramDesc; } } if (optimize) { program.optimizeProgram->Description("optimize: "); } else { originProgramDesc->Description("program: "); } paddle_mobile__framework__proto__program_desc__free_unpacked(c_program, nullptr); return program; } #endif /** * fusion and print someinfos * @tparam Device * @tparam P * @param optimize * @param can_add_split * @param program * @param originProgramDesc */ template void FusionAndPrintInfos( bool optimize, bool can_add_split, Program *program, const std::shared_ptr &originProgramDesc) { if (optimize) { ProgramOptimize program_optimize; program->optimizeProgram = program_optimize.FusionOptimize(originProgramDesc, can_add_split); if (!program->optimizeProgram) { program->optimizeProgram = originProgramDesc; } } if (optimize) { program->optimizeProgram->Description("optimize: "); } else { originProgramDesc->Description("program: "); } } static size_t ReadBuffer(const char *file_name, uint8_t **out) { FILE *fp; fp = fopen(file_name, "rb"); PADDLE_MOBILE_ENFORCE(fp != NULL, " %s open failed !", file_name); fseek(fp, 0, SEEK_END); size_t size = ftell(fp); rewind(fp); DLOG << "model size: " << size; *out = reinterpret_cast(malloc(size)); size_t cur_len = 0; size_t nread; while ((nread = fread(*out + cur_len, 1, size - cur_len, fp)) != 0) { cur_len += nread; } fclose(fp); return cur_len; } template const Program Loader::Load(const std::string &dirname, bool optimize, bool quantification, bool can_add_split) { auto program = this->LoadProgram(dirname + "/__model__", optimize, quantification, can_add_split); program.model_path = dirname; return program; } template const Program Loader::Load(const std::string &model_path, const std::string ¶_path, bool optimize, bool quantification) { auto program = this->LoadProgram(model_path, optimize, quantification); program.para_path = para_path; program.combined = true; program.quantification = quantification; return program; } template const Program Loader::LoadProgram( const std::string &model_path, bool optimize, bool quantification, bool can_add_split) { std::string model_filename = model_path; PaddleMobile__Framework__Proto__ProgramDesc *c_program; uint8_t *buf = NULL; size_t read_size = ReadBuffer(model_filename.c_str(), &buf); PADDLE_MOBILE_ENFORCE(buf != NULL, "read from __model__ is null"); c_program = paddle_mobile__framework__proto__program_desc__unpack( NULL, read_size, buf); // PADDLE_MOBILE_ENFORCE(c_program != NULL, "program is null"); // DLOG << "n_ops: " << (*c_program->blocks)->n_ops; // auto originProgramDesc = std::make_shared(c_program); Program program; program.originProgram = originProgramDesc; program.quantification = quantification; program.combined_params_len = 0; program.combined_params_buf = nullptr; auto scope = std::make_shared(); program.scope = scope; // use originProgramDesc and scope to init tensors InitMemoryFromProgram(originProgramDesc, scope); // perform fusion and print infos FusionAndPrintInfos(optimize, can_add_split, &program, originProgramDesc); paddle_mobile__framework__proto__program_desc__free_unpacked(c_program, NULL); return program; } template const Program Loader::LoadCombinedMemory( size_t read_size, const uint8_t *buf, size_t combined_params_len, uint8_t *combined_params_buf, bool optimize, bool quantification) { bool can_add_split = false; PaddleMobile__Framework__Proto__ProgramDesc *c_program; PADDLE_MOBILE_ENFORCE(buf != nullptr, "read from __model__ is null"); c_program = paddle_mobile__framework__proto__program_desc__unpack( nullptr, read_size, buf); // PADDLE_MOBILE_ENFORCE(c_program != nullptr, "program is null"); // DLOG << "n_ops: " << (*c_program->blocks)->n_ops; // auto originProgramDesc = std::make_shared(c_program); Program program; program.combined = true; program.originProgram = originProgramDesc; program.quantification = quantification; program.combined_params_len = combined_params_len; program.combined_params_buf = combined_params_buf; auto scope = std::make_shared(); program.scope = scope; InitMemoryFromProgram(originProgramDesc, scope); FusionAndPrintInfos(optimize, can_add_split, &program, originProgramDesc); paddle_mobile__framework__proto__program_desc__free_unpacked(c_program, nullptr); return program; } template class Loader; template class Loader; template class Loader; template class Loader; } // namespace framework } // namespace paddle_mobile