wehub-resource-sync
96 lines
3.3 KiB
C++
96 lines
3.3 KiB
C++
// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/funcs/math/sampler.h"
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#include <glog/logging.h>
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#include "paddle/phi/core/generator.h"
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namespace phi::math {
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Sampler::~Sampler() = default;
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UniformSampler::UniformSampler(int64_t range, unsigned int seed)
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: Sampler(range, seed), inv_range_(1.0f / (range + 1)) { // NOLINT
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random_engine_ = phi::GetCPURandomEngine(seed_);
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dist_ = std::make_shared<std::uniform_int_distribution<>>(0, range);
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}
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int64_t UniformSampler::Sample() const { return (*dist_)(*random_engine_); }
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float UniformSampler::Probability(int64_t value) const { return inv_range_; }
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LogUniformSampler::LogUniformSampler(int64_t range, unsigned int seed)
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: Sampler(range, seed), log_range_(log(range + 1)) { // NOLINT
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random_engine_ = phi::GetCPURandomEngine(seed_);
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dist_ = std::make_shared<std::uniform_real_distribution<>>(0, 1);
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}
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int64_t LogUniformSampler::Sample() const {
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// Got Log Uniform distribution from uniform distribution by
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// inverse_transform_sampling method
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// More details:
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// https://wanghaoshuang.github.io/2017/11/Log-uniform-distribution-sampler/
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auto cur_random = (*dist_)(*random_engine_);
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const int64_t value = static_cast<int64_t>(exp(cur_random * log_range_)) - 1;
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// Mathematically, value should be <= range_, but might not be due to some
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// floating point roundoff, so we mod by range_.
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return value % range_;
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}
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float LogUniformSampler::Probability(int64_t value) const {
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// Given f(x) = 1/[(x+1) * log_range_]
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// The value's probability is integral of f(x) from value to (value + 1)
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// More details:
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// https://wanghaoshuang.github.io/2017/11/Log-uniform-distribution-sampler
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return (log((value + 2.0) / (value + 1.0))) / log_range_; // NOLINT
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}
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CustomSampler::CustomSampler(int64_t range,
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const float *probabilities,
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const int *alias,
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const float *alias_probabilities,
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unsigned int seed)
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: Sampler(range, seed) {
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random_engine_ = phi::GetCPURandomEngine(seed_);
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real_dist_ = std::make_shared<std::uniform_real_distribution<>>(0, 1);
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int_dist_ = std::make_shared<std::uniform_int_distribution<>>(0, range);
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alias_probs_ = alias_probabilities;
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probs_ = probabilities;
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alias_ = alias;
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}
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int64_t CustomSampler::Sample() const {
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auto index = (*int_dist_)(*random_engine_);
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auto p = (*real_dist_)(*random_engine_);
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if (p > alias_probs_[index]) {
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int alias = alias_[index];
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if (alias == exceptional_val) {
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LOG(WARNING) << "WARNING: CustomSampler get alias " << exceptional_val;
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return index;
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}
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return alias;
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} else {
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return index;
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}
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}
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float CustomSampler::Probability(int64_t value) const { return probs_[value]; }
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} // namespace phi::math
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