Line data    Source code

       1              : // SPDX-License-Identifier: Apache-2.0
       2              : /**
       3              :  * Copyright (C) 2021 Parichay Kapoor <pk.kapoor@samsung.com>
       4              :  *
       5              :  * @file   lr_scheduler_step.cpp
       6              :  * @date   09 December 2021
       7              :  * @brief  This is Step Learning Rate Scheduler class
       8              :  * @see    https://github.com/nnstreamer/nntrainer
       9              :  * @author Parichay Kapoor <pk.kapoor@samsung.com>
      10              :  * @bug    No known bugs except for NYI items
      11              :  *
      12              :  * @details given the iteration range [it_0, it_1, ... it_n], learning rates
      13              :  * [lr_0, lr_1 ... lr_n_1], and iteration iter, find index i such that
      14              :  * it_i_1 < iter <= it_i and return lr_i_1.
      15              :  */
      16              : 
      17              : #include <cmath>
      18              : 
      19              : #include <common_properties.h>
      20              : #include <lr_scheduler_step.h>
      21              : #include <nntrainer_error.h>
      22              : #include <nntrainer_log.h>
      23              : #include <node_exporter.h>
      24              : 
      25              : namespace nntrainer {
      26              : 
      27           16 : StepLearningRateScheduler::StepLearningRateScheduler() : lr_props({}, {}) {}
      28              : 
      29           11 : void StepLearningRateScheduler::finalize() {
      30           13 :   NNTR_THROW_IF(std::get<std::vector<props::LearningRate>>(lr_props).empty(),
      31              :                 std::invalid_argument)
      32              :     << "[StepLearningRateScheduler] Learning rates are not set";
      33           11 :   NNTR_THROW_IF(std::get<std::vector<props::Iteration>>(lr_props).empty(),
      34              :                 std::invalid_argument)
      35              :     << "[StepLearningRateScheduler] Step iterations are not set";
      36              : 
      37              :   auto const &[learning_rates, iterations] = lr_props;
      38            7 :   if (learning_rates.size() != iterations.size() + 1)
      39              :     throw std::invalid_argument("[StepLearningRateScheduler] learning rates "
      40            2 :                                 "and step iterations count mismatch");
      41              : 
      42              :   /**
      43              :    * provided step iterations must contain monotonically increasing values,
      44              :    * and all values must be unique
      45              :    */
      46            5 :   std::vector<unsigned int> sorted_iterations(iterations.size());
      47              :   std::transform(iterations.begin(), iterations.end(),
      48              :                  sorted_iterations.begin(),
      49           11 :                  [](auto const &val) { return val.get(); });
      50            5 :   std::sort(sorted_iterations.begin(), sorted_iterations.end());
      51            5 :   auto iter = std::unique(sorted_iterations.begin(), sorted_iterations.end());
      52            6 :   NNTR_THROW_IF(iter != sorted_iterations.end(), std::invalid_argument)
      53              :     << "[StepLearningRateScheduler] step iterations should contain unique "
      54              :        "values";
      55           11 :   for (unsigned int idx = 0; idx < sorted_iterations.size(); idx++)
      56            9 :     NNTR_THROW_IF(iterations[idx].get() != sorted_iterations[idx],
      57              :                   std::invalid_argument)
      58              :       << "[StepLearningRateScheduler] step iterations should be in "
      59              :          "monotonically increasing order";
      60            5 : }
      61              : 
      62           37 : void StepLearningRateScheduler::setProperty(
      63              :   const std::vector<std::string> &values) {
      64           37 :   auto left = loadProperties(values, lr_props);
      65           39 :   NNTR_THROW_IF(left.size(), std::invalid_argument)
      66              :     << "[StepLearningRateScheduler] There are unparsed properties";
      67           36 : }
      68              : 
      69            0 : void StepLearningRateScheduler::exportTo(
      70              :   Exporter &exporter, const ml::train::ExportMethods &method) const {
      71            0 :   exporter.saveResult(lr_props, method, this);
      72            0 : }
      73              : 
      74          106 : double StepLearningRateScheduler::getLearningRate(size_t iteration) {
      75              :   auto const &[learning_rates, iterations] = lr_props;
      76              :   auto upper =
      77          106 :     std::lower_bound(iterations.begin(), iterations.end(), iteration);
      78          106 :   if (upper != iterations.end())
      79          102 :     return learning_rates[upper - iterations.begin()];
      80              :   else
      81            4 :     return learning_rates.back().get();
      82              : }
      83              : 
      84              : } // namespace nntrainer