junrushao1994 commented on a change in pull request #8642: URL: https://github.com/apache/tvm/pull/8642#discussion_r683005336
########## File path: include/tvm/support/random_engine.h ########## @@ -0,0 +1,117 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you 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. + */ + +/*! + * \file random_engine.h + * \brief Random number generator, for Sampler and Sampling functions. + */ + +#ifndef TVM_SUPPORT_RANDOM_ENGINE_H_ +#define TVM_SUPPORT_RANDOM_ENGINE_H_ + +#include <tvm/runtime/logging.h> + +#include <cstdint> // for uint64_t + +namespace tvm { +namespace support { + +/*! + * \brief This linear congruential engine is a drop-in replacement for std::minstd_rand. It strictly + * corresponds to std::minstd_rand and is designed to be platform-independent. + * \note Our linear congruential engine is a complete implementation of + * std::uniform_random_bit_generator so it can be used as generator for any STL random number + * distribution. However, parts of std::linear_congruential_engine's member functions are not + * included for simplification. For full member functions of std::minstd_rand, please check out the + * following link: https://en.cppreference.com/w/cpp/numeric/random/linear_congruential_engine + */ +class LinearCongruentialEngine { + public: + /*! + * \brief The result type is defined as int64_t here for meta_schedule sampler usage. + * \note The type name is not in Google style because it is used in STL's distribution inferface. + */ + using result_type = uint64_t; + + /*! \brief The multiplier */ + static constexpr result_type multiplier = 48271; + + /*! \brief The increment */ + static constexpr result_type increment = 0; + + /*! \brief The modulus */ + static constexpr result_type modulus = 2147483647; + + /*! + * \brief The minimum possible value of random state here. + * \note The function name is uncapilized because it is used in STL's distribution inferface. + */ + result_type min() { return 0; } + + /*! + * \brief The maximum possible value of random state here. + * \note The function name is uncapilized because it is used in STL's distribution inferface. + */ + result_type max() { return modulus - 1; } + + /*! + * \brief Operator to move the random state to the next and return the new random state. According + * to definition of linear congruential engine, the new random state value is computed as + * new_random_state = (current_random_state * multiplier + increment) % modulus. + * \return The next current random state value in the type of result_type. + * \note In order for better efficiency, the implementation here has a few assumptions: + * 1. The multiplication and addition won't overflow. + * 2. The given random state pointer `rand_state_ptr` is not nullptr. + * 3. The given random state *(rand_state_ptr) is in the range of [0, modulus - 1]. + */ + result_type operator()() { + (*rand_state_ptr_) = ((*rand_state_ptr_) * multiplier + increment) % modulus; + return *rand_state_ptr_; + } + + /*! + * \brief Change the start random state of RNG with the seed of a new random state value. + * \param rand_state The random state given in result_type. + */ + void Seed(result_type rand_state = 1) { Review comment: This API is used to interface with TVM codebase, so let's use TRandState ```suggestion void Seed(TRandState rand_state = 1) { ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
