/* 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. */ #include "paddle/fluid/framework/generator.h" #include #include #include #include #include #include namespace paddle { namespace framework { const std::shared_ptr& DefaultCPUGenerator() { static auto default_cpu_generator = std::make_shared(GetRandomSeed()); VLOG(4) << "initial seed: " << default_cpu_generator->GetCurrentSeed() << ", cpu engine: " << default_cpu_generator->GetCPUEngine().get(); return default_cpu_generator; } std::shared_ptr OpDefaultCPUEngine() { static auto op_default_cpu_engine = std::make_shared(); return op_default_cpu_engine; } // NOTE(zhiqiu): there are 3 conditions: // (1) op seed is not set and DefaultCPUGenerator is inited, use // DefaultCPUGenerator // (2) op seed is not set and DefaultCPUGenerator is not inited, use se // OpDefaultCPUEngine() and set a radnom seed // (3) op seed is set, use OpDefaultCPUEngine() and set the seed std::shared_ptr GetCPURandomEngine(uint64_t seed) { if (DefaultCPUGenerator()->GetIsInitPy() && seed == 0) { VLOG(4) << "Use random engine from generator"; return DefaultCPUGenerator()->GetCPUEngine(); } else { // NOTE(zhiqiu): creating an engine instance everytime instead of using // OpDefaultCPUEngine(), this is the legacy behavior of random operators. // The benefit is that when runing PE with fixed-seed in multiple thrads, // each thread has their own engine, and doesn't affect each other. // // And we need to measure the determinacy of Generator in PE. auto engine = std::make_shared(); if (seed == 0) { seed = GetRandomSeed(); VLOG(4) << "Use default random engine with random seed = " << seed; } else { VLOG(4) << "Use default random engine with fixed random seed = " << seed; } static std::mutex mu_; { std::lock_guard lock(mu_); engine->seed(seed); } return engine; } } GeneratorState Generator::GetState() { std::lock_guard lock(this->mu_); state_.cpu_engine = *engine_; return this->state_; } void Generator::SetState(const GeneratorState& state) { std::lock_guard lock(this->mu_); this->state_ = state; this->engine_ = std::make_shared(state.cpu_engine); } uint64_t Generator::GetCurrentSeed() { std::lock_guard lock(this->mu_); return this->state_.current_seed; } uint64_t Generator::Seed() { std::lock_guard lock(this->mu_); uint64_t seed; std::random_device de; seed = ((((uint64_t)de()) << 32) + de()) & 0x1FFFFFFFFFFFFF; this->state_.current_seed = seed; std::seed_seq seq({seed}); this->engine_->seed(seq); return this->state_.current_seed; } void Generator::SetCurrentSeed(uint64_t seed) { std::lock_guard lock(this->mu_); this->state_.current_seed = seed; std::seed_seq seq({seed}); this->engine_->seed(seq); } std::shared_ptr Generator::GetCPUEngine() { std::lock_guard lock(this->mu_); return this->engine_; } void Generator::SetCPUEngine(std::shared_ptr engine) { std::lock_guard lock(this->mu_); this->engine_ = engine; } uint64_t Generator::Random64() { std::lock_guard lock(this->mu_); auto engine = this->engine_; return (*engine)(); } void Generator::SetIsInitPy(bool is_init_py) { this->is_init_py_ = is_init_py; VLOG(4) << "SetIsInitPy:" << this->is_init_py_; } bool Generator::GetIsInitPy() const { return this->is_init_py_; } } // namespace framework } // namespace paddle