2 writes to _options
Microsoft.ML.StandardTrainers (2)
Standard\SdcaBinary.cs (2)
1979
_options
= new OptionsBase();
2004
_options
= options;
24 references to _options
Microsoft.ML.StandardTrainers (24)
Standard\SdcaBinary.cs (24)
1949
private protected override bool ShuffleData =>
_options
.Shuffle;
1980
_options
.NumberOfIterations = maxIterations;
1981
_options
.LearningRate = initLearningRate;
1982
_options
.L2Regularization = l2Weight;
1984
_options
.FeatureColumnName = featureColumn;
1985
_options
.LabelColumnName = labelColumn;
1986
_options
.ExampleWeightColumnName = weightColumn;
2035
if (
_options
.NumberOfThreads.HasValue)
2037
numThreads =
_options
.NumberOfThreads.Value;
2038
ch.CheckUserArg(numThreads > 0, nameof(
_options
.NumberOfThreads), "The number of threads must be either null or a positive integer.");
2044
int checkFrequency =
_options
.CheckFrequency ?? numThreads;
2047
var l2Weight =
_options
.L2Regularization;
2050
var positiveInstanceWeight =
_options
.PositiveInstanceWeight;
2072
if (e % checkFrequency == 0 && e !=
_options
.NumberOfIterations)
2098
pch.Checkpoint(loss, improvement, e,
_options
.NumberOfIterations);
2099
converged = improvement <
_options
.ConvergenceTolerance;
2108
var trainingTasks = new Action<Random, IProgressChannel>[
_options
.NumberOfIterations];
2109
var rands = new Random[
_options
.NumberOfIterations];
2110
var ilr =
_options
.LearningRate;
2112
for (int epoch = 1; epoch <=
_options
.NumberOfIterations; epoch++)
2118
using (var cursor =
_options
.Shuffle ? cursorFactory.Create(rand) : cursorFactory.Create())
2173
entry => entry.SetProgress(0, iter,
_options
.NumberOfIterations));
2175
for (int i = 0; i <
_options
.NumberOfIterations; i++)
2193
Parallel.For(0,
_options
.NumberOfIterations, pOptions, i => trainingTasks[i](rands[i], pch));