// 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. #pragma once #include #include #include // NOLINT #include #include #include #include "paddle/fluid/distributed/table/accessor.h" #include "paddle/fluid/framework/program_desc.h" #include "paddle/fluid/framework/scope.h" #include "paddle/fluid/platform/device_context.h" #include "paddle/fluid/platform/place.h" #include "paddle/fluid/string/string_helper.h" namespace paddle { namespace distributed { class Table { public: Table() {} virtual ~Table() {} virtual int32_t initialize(const TableParameter &config, const FsClientParameter &fs_config) final; virtual int32_t pull_dense(float *values, size_t num) = 0; virtual int32_t push_dense(const float *values, size_t num) = 0; // for push global_step virtual int32_t push_dense(const int64_t *values, const int32_t trainer_id) { return 0; } virtual int32_t push_dense_param(const float *values, size_t num) { return 0; } virtual int32_t pull_sparse(float *values, const uint64_t *keys, size_t num) = 0; virtual int32_t push_sparse(const uint64_t *keys, const float *values, size_t num) = 0; virtual int32_t push_sparse_param(const uint64_t *keys, const float *values, size_t num) { return 0; } // only for sparse geo table virtual int32_t pull_geo_param(const uint32_t trainer_id, std::vector *values, std::vector *keys) { return 0; } // only for barrier virtual int32_t barrier(const uint32_t trainer_id, const std::string barrier_type) { return 0; } // only for barrier table virtual int32_t set_table_map( std::unordered_map> *table_map) { return 0; } // only for tensor table virtual int32_t set_program_env( framework::Scope *scope, platform::Place place, const std::vector *sub_program) { return 0; } virtual int32_t set_global_lr(float *lr) { _global_lr = lr; return 0; } virtual int32_t pour() { return 0; } virtual void clear() = 0; virtual int32_t flush() = 0; virtual int32_t shrink() = 0; //指定加载路径 virtual int32_t load(const std::string &path, const std::string &converter) = 0; //指定保存路径 virtual int32_t save(const std::string &path, const std::string &converter) = 0; virtual int32_t set_shard(size_t shard_idx, size_t shard_num) final { _shard_idx = shard_idx; _shard_num = shard_num; return initialize_shard(); } inline std::shared_ptr value_accesor() { return _value_accesor; } virtual void *get_shard(size_t shard_idx) = 0; virtual std::pair print_table_stat() { return {0, 0}; } protected: virtual int32_t initialize() = 0; virtual int32_t initialize_accessor() final; virtual int32_t initialize_shard() = 0; virtual std::string table_dir(const std::string &model_dir) { return paddle::string::format_string("%s/%03d/", model_dir.c_str(), _config.table_id()); } size_t _shard_idx; // table 分片编号 size_t _shard_num; // table 分片总数 TableParameter _config; float *_global_lr = nullptr; std::shared_ptr _value_accesor; }; REGISTER_REGISTERER(Table); class TableManager { public: static TableManager &instance() { static TableManager manager; return manager; } int32_t initialize(); private: TableManager() {} ~TableManager() {} }; } // namespace distributed } // namespace paddle