1 write to _parent
Microsoft.ML.Transforms (1)
Dracula\CountTableTransformer.cs (1)
605
_parent
= parent;
22 references to _parent
Microsoft.ML.Transforms (22)
Dracula\CountTableTransformer.cs (22)
611
var outputCols = new DataViewSchema.DetachedColumn[
_parent
.ColumnPairs.Length];
612
for (int i = 0; i <
_parent
.ColumnPairs.Length; i++)
614
var inputCol = InputSchema[
_parent
.ColumnPairs[i].inputColumnName];
616
Host.Check((long)valueCount *
_parent
.Featurizer.NumFeatures < int.MaxValue, "Too large output size");
617
var type = new VectorDataViewType(NumberDataViewType.Single, valueCount,
_parent
.Featurizer.NumFeatures);
625
outputCols[i] = new DataViewSchema.DetachedColumn(
_parent
.ColumnPairs[i].outputColumnName, type, builder.ToAnnotations());
628
outputCols[i] = new DataViewSchema.DetachedColumn(
_parent
.ColumnPairs[i].outputColumnName, type);
635
Host.Assert(0 <= iinfo && iinfo <
_parent
.ColumnPairs.Length);
652
_parent
.Featurizer.GetFeatureNames(
_parent
._labelClassNames, ref featureNames);
675
if (input.Schema[
_parent
.ColumnPairs[iinfo].inputColumnName].Type is VectorDataViewType)
682
Host.Assert(
_parent
.Featurizer.SlotCount[iinfo] == 1);
684
var srcGetter = input.GetGetter<uint>(input.Schema[
_parent
.ColumnPairs[iinfo].inputColumnName]);
685
var outputLength =
_parent
.Featurizer.NumFeatures;
686
var rand = _addNoise ? new Random(
_parent
.Seeds[iinfo]) : null;
687
var featurizer =
_parent
.Featurizer;
699
var inputCol = input.Schema[
_parent
.ColumnPairs[iinfo].inputColumnName];
701
Host.Assert(
_parent
.Featurizer.SlotCount[iinfo] == n);
704
var outputLength =
_parent
.Featurizer.NumFeatures;
706
var rand = _addNoise ? new Random(
_parent
.Seeds[iinfo]) : null;
715
_parent
.Featurizer.GetFeatures(iinfo, i, rand, srcValues[i], editor.Values.Slice(i * outputLength, outputLength));
725
_parent
.Featurizer.GetFeatures(iinfo, index, rand, srcValues[i], editor.Values.Slice(index * outputLength, outputLength));