public void TestOldSavingAndLoading()
{
var data = new[] { new TestClass()
{
A = 1, B = 2, C = 3,
}, new TestClass()
{
A = 4, B = 5, C = 6
} };
var dataView = ComponentCreation.CreateDataView(Env, data);
var pipe = new HashingEstimator(Env, new[] {
new HashingTransformer.ColumnInfo("A", "HashA", hashBits: 4, invertHash: -1),
new HashingTransformer.ColumnInfo("B", "HashB", hashBits: 3, ordered: true),
new HashingTransformer.ColumnInfo("C", "HashC", seed: 42),
new HashingTransformer.ColumnInfo("A", "HashD"),
});
var result = pipe.Fit(dataView).Transform(dataView);
var resultRoles = new RoleMappedData(result);
using (var ms = new MemoryStream())
{
TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles);
ms.Position = 0;
var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);
}
}
internal static ITransformer Create(IHostEnvironment env, Options options, IDataView input)
{
Contracts.CheckValue(env, nameof(env));
var h = env.Register(LoaderSignature);
h.CheckValue(options, nameof(options));
h.CheckValue(input, nameof(input));
h.CheckUserArg(Utils.Size(options.Columns) > 0, nameof(options.Columns), "Columns must be specified");
var chain = new TransformerChain <ITransformer>();
// To each input column to the NgramHashExtractorArguments, a HashTransform using 31
// bits (to minimize collisions) is applied first, followed by an NgramHashTransform.
var hashColumns = new List <HashingEstimator.ColumnOptions>();
var ngramHashColumns = new NgramHashingEstimator.ColumnOptions[options.Columns.Length];
var colCount = options.Columns.Length;
// The NGramHashExtractor has a ManyToOne column type. To avoid stepping over the source
// column name when a 'name' destination column name was specified, we use temporary column names.
string[][] tmpColNames = new string[colCount][];
for (int iinfo = 0; iinfo < colCount; iinfo++)
{
var column = options.Columns[iinfo];
h.CheckUserArg(!string.IsNullOrWhiteSpace(column.Name), nameof(column.Name));
h.CheckUserArg(Utils.Size(column.Source) > 0 &&
column.Source.All(src => !string.IsNullOrWhiteSpace(src)), nameof(column.Source));
int srcCount = column.Source.Length;
tmpColNames[iinfo] = new string[srcCount];
for (int isrc = 0; isrc < srcCount; isrc++)
{
var tmpName = input.Schema.GetTempColumnName(column.Source[isrc]);
tmpColNames[iinfo][isrc] = tmpName;
hashColumns.Add(new HashingEstimator.ColumnOptions(tmpName, column.Source[isrc],
30, column.Seed ?? options.Seed, false, column.MaximumNumberOfInverts ?? options.MaximumNumberOfInverts));
}
ngramHashColumns[iinfo] =
new NgramHashingEstimator.ColumnOptions(column.Name, tmpColNames[iinfo],
column.NgramLength ?? options.NgramLength,
column.SkipLength ?? options.SkipLength,
column.UseAllLengths ?? options.UseAllLengths,
column.NumberOfBits ?? options.NumberOfBits,
column.Seed ?? options.Seed,
column.Ordered ?? options.Ordered,
column.MaximumNumberOfInverts ?? options.MaximumNumberOfInverts);
ngramHashColumns[iinfo].FriendlyNames = column.FriendlyNames;
}
var hashing = new HashingEstimator(h, hashColumns.ToArray()).Fit(input);
return(chain.Append(hashing)
.Append(new NgramHashingEstimator(h, ngramHashColumns).Fit(hashing.Transform(input)))
.Append(new ColumnSelectingTransformer(h, null, tmpColNames.SelectMany(cols => cols).ToArray())));
}
public static string CreateStratificationColumn(IHost host, ref IDataView data, string stratificationColumn = null)
{
host.CheckValue(data, nameof(data));
host.CheckValueOrNull(stratificationColumn);
// Pick a unique name for the stratificationColumn.
const string stratColName = "StratificationKey";
string stratCol = data.Schema.GetTempColumnName(stratColName);
// Construct the stratification column. If user-provided stratification column exists, use HashJoin
// of it to construct the strat column, otherwise generate a random number and use it.
if (stratificationColumn == null)
{
data = new GenerateNumberTransform(host,
new GenerateNumberTransform.Options
{
Columns = new[] { new GenerateNumberTransform.Column {
Name = stratCol
} }
}, data);
}
else
{
var col = data.Schema.GetColumnOrNull(stratificationColumn);
if (col == null)
{
throw host.ExceptSchemaMismatch(nameof(stratificationColumn), "Stratification", stratificationColumn);
}
var type = col.Value.Type;
if (!RangeFilter.IsValidRangeFilterColumnType(host, type))
{
// HashingEstimator currently handles all primitive types except for DateTime, DateTimeOffset and TimeSpan.
var itemType = type.GetItemType();
if (itemType is DateTimeDataViewType || itemType is DateTimeOffsetDataViewType || itemType is TimeSpanDataViewType)
{
data = new TypeConvertingTransformer(host, stratificationColumn, DataKind.Int64, stratificationColumn).Transform(data);
}
var columnOptions = new HashingEstimator.ColumnOptions(stratCol, stratificationColumn, 30, combine: true);
data = new HashingEstimator(host, columnOptions).Fit(data).Transform(data);
}
else
{
if (data.Schema[stratificationColumn].IsNormalized() || (type != NumberDataViewType.Single && type != NumberDataViewType.Double))
{
return(stratificationColumn);
}
data = new NormalizingEstimator(host,
new NormalizingEstimator.MinMaxColumnOptions(stratCol, stratificationColumn, ensureZeroUntouched: true))
.Fit(data).Transform(data);
}
}
return(stratCol);
}
internal CountTargetEncodingEstimator(IHostEnvironment env, Options options)
{
Contracts.CheckValue(env, nameof(env));
_host = env.Register(nameof(CountTargetEncodingEstimator));
_host.CheckValue(options, nameof(options));
_host.CheckUserArg(Utils.Size(options.Columns) > 0, nameof(options.Columns), "Columns must be specified");
_host.CheckUserArg(!string.IsNullOrWhiteSpace(options.LabelColumn), nameof(options.LabelColumn), "Must specify the label column name");
if (!string.IsNullOrEmpty(options.InitialCountsModel))
{
_countTableEstimator = LoadFromFile(env, options.InitialCountsModel, options.LabelColumn,
options.Columns.Select(col => new InputOutputColumnPair(col.Name)).ToArray());
if (_countTableEstimator == null)
{
throw env.Except($"The file {options.InitialCountsModel} does not contain a CountTableTransformer");
}
}
else if (options.SharedTable)
{
var columns = new CountTableEstimator.SharedColumnOptions[options.Columns.Length];
for (int i = 0; i < options.Columns.Length; i++)
{
var column = options.Columns[i];
columns[i] = new CountTableEstimator.SharedColumnOptions(
column.Name,
column.Name,
column.PriorCoefficient ?? options.PriorCoefficient,
column.LaplaceScale ?? options.LaplaceScale,
column.Seed ?? options.Seed);
}
var builder = options.CountTable;
_host.CheckValue(builder, nameof(options.CountTable));
_countTableEstimator = new CountTableEstimator(_host, options.LabelColumn, builder.CreateComponent(_host), columns);
}
else
{
var columns = new CountTableEstimator.ColumnOptions[options.Columns.Length];
for (int i = 0; i < options.Columns.Length; i++)
{
var column = options.Columns[i];
var builder = column.CountTable ?? options.CountTable;
_host.CheckValue(builder, nameof(options.CountTable));
columns[i] = new CountTableEstimator.ColumnOptions(
column.Name,
column.Name,
builder.CreateComponent(_host),
column.PriorCoefficient ?? options.PriorCoefficient,
column.LaplaceScale ?? options.LaplaceScale,
column.Seed ?? options.Seed);
}
_countTableEstimator = new CountTableEstimator(_host, options.LabelColumn, columns);
}
_hashingColumns = InitializeHashingColumnOptions(options);
_hashingEstimator = new HashingEstimator(_host, _hashingColumns);
}
private CountTargetEncodingEstimator(IHostEnvironment env, CountTableEstimator estimator, CountTableEstimator.ColumnOptionsBase[] columns,
int numberOfBits, bool combine, uint hashingSeed)
{
Contracts.CheckValue(env, nameof(env));
_host = env.Register(nameof(CountTargetEncodingEstimator));
_hashingColumns = InitializeHashingColumnOptions(columns, numberOfBits, combine, hashingSeed);
_hashingEstimator = new HashingEstimator(_host, _hashingColumns);
_countTableEstimator = estimator;
}
internal OneHotHashEncodingTransformer(HashingEstimator hash, IEstimator <ITransformer> keyToVector, IDataView input)
{
if (keyToVector != null)
{
_transformer = hash.Append(keyToVector).Fit(input);
}
else
{
_transformer = new TransformerChain <ITransformer>(hash.Fit(input));
}
}
internal CountTargetEncodingEstimator(IHostEnvironment env, string labelColumnName, CountTargetEncodingTransformer initialCounts, params InputOutputColumnPair[] columns)
{
Contracts.CheckValue(env, nameof(env));
_host = env.Register(nameof(CountTargetEncodingEstimator));
_host.CheckValue(initialCounts, nameof(initialCounts));
_host.CheckNonEmpty(columns, nameof(columns));
_host.Check(initialCounts.VerifyColumns(columns), nameof(columns));
_hashingEstimator = new HashingEstimator(_host, initialCounts.HashingTransformer.Columns.ToArray());
_countTableEstimator = new CountTableEstimator(_host, labelColumnName, initialCounts.CountTable,
columns.Select(c => new InputOutputColumnPair(c.OutputColumnName, c.OutputColumnName)).ToArray());
}
/// <summary>
/// Ensures the provided <paramref name="samplingKeyColumn"/> is valid for <see cref="RangeFilter"/>, hashing it if necessary, or creates a new column <paramref name="samplingKeyColumn"/> is null.
/// </summary>
internal static void EnsureGroupPreservationColumn(IHostEnvironment env, ref IDataView data, ref string samplingKeyColumn, int?seed = null)
{
Contracts.CheckValue(env, nameof(env));
// We need to handle two cases: if samplingKeyColumn is provided, we use hashJoin to
// build a single hash of it. If it is not, we generate a random number.
if (samplingKeyColumn == null)
{
samplingKeyColumn = data.Schema.GetTempColumnName("SamplingKeyColumn");
data = new GenerateNumberTransform(env, data, samplingKeyColumn, (uint?)(seed ?? ((ISeededEnvironment)env).Seed));
}
else
{
if (!data.Schema.TryGetColumnIndex(samplingKeyColumn, out int stratCol))
{
throw env.ExceptSchemaMismatch(nameof(samplingKeyColumn), "SamplingKeyColumn", samplingKeyColumn);
}
var type = data.Schema[stratCol].Type;
if (!RangeFilter.IsValidRangeFilterColumnType(env, type))
{
// Hash the samplingKeyColumn.
// REVIEW: this could currently crash, since Hash only accepts a limited set
// of column types. It used to be HashJoin, but we should probably extend Hash
// instead of having two hash transformations.
var origStratCol = samplingKeyColumn;
samplingKeyColumn = data.Schema.GetTempColumnName(samplingKeyColumn);
HashingEstimator.ColumnOptionsInternal columnOptions;
if (seed.HasValue)
{
columnOptions = new HashingEstimator.ColumnOptionsInternal(samplingKeyColumn, origStratCol, 30, (uint)seed.Value);
}
else if (((ISeededEnvironment)env).Seed.HasValue)
{
columnOptions = new HashingEstimator.ColumnOptionsInternal(samplingKeyColumn, origStratCol, 30, (uint)((ISeededEnvironment)env).Seed.Value);
}
else
{
columnOptions = new HashingEstimator.ColumnOptionsInternal(samplingKeyColumn, origStratCol, 30);
}
data = new HashingEstimator(env, columnOptions).Fit(data).Transform(data);
}
else
{
if (!data.Schema[samplingKeyColumn].IsNormalized() && (type == NumberDataViewType.Single || type == NumberDataViewType.Double))
{
var origStratCol = samplingKeyColumn;
samplingKeyColumn = data.Schema.GetTempColumnName(samplingKeyColumn);
data = new NormalizingEstimator(env, new NormalizingEstimator.MinMaxColumnOptions(samplingKeyColumn, origStratCol, ensureZeroUntouched: true)).Fit(data).Transform(data);
}
}
}
}
/// <summary>
/// Ensures the provided <paramref name="samplingKeyColumn"/> is valid for <see cref="RangeFilter"/>, hashing it if necessary, or creates a new column <paramref name="samplingKeyColumn"/> is null.
/// </summary>
internal static void EnsureGroupPreservationColumn(IHostEnvironment env, ref IDataView data, ref string samplingKeyColumn, int?seed = null)
{
Contracts.CheckValue(env, nameof(env));
// We need to handle two cases: if samplingKeyColumn is provided, we use hashJoin to
// build a single hash of it. If it is not, we generate a random number.
if (samplingKeyColumn == null)
{
samplingKeyColumn = data.Schema.GetTempColumnName("SamplingKeyColumn");
data = new GenerateNumberTransform(env, data, samplingKeyColumn, (uint?)(seed ?? ((ISeededEnvironment)env).Seed));
}
else
{
if (!data.Schema.TryGetColumnIndex(samplingKeyColumn, out int stratCol))
{
throw env.ExceptSchemaMismatch(nameof(samplingKeyColumn), "SamplingKeyColumn", samplingKeyColumn);
}
var type = data.Schema[stratCol].Type;
if (!RangeFilter.IsValidRangeFilterColumnType(env, type))
{
var origStratCol = samplingKeyColumn;
samplingKeyColumn = data.Schema.GetTempColumnName(samplingKeyColumn);
// HashingEstimator currently handles all primitive types except for DateTime, DateTimeOffset and TimeSpan.
var itemType = type.GetItemType();
if (itemType is DateTimeDataViewType || itemType is DateTimeOffsetDataViewType || itemType is TimeSpanDataViewType)
{
data = new TypeConvertingTransformer(env, origStratCol, DataKind.Int64, origStratCol).Transform(data);
}
var localSeed = seed.HasValue ? seed : ((ISeededEnvironment)env).Seed.HasValue ? ((ISeededEnvironment)env).Seed : null;
var columnOptions =
localSeed.HasValue ?
new HashingEstimator.ColumnOptions(samplingKeyColumn, origStratCol, 30, (uint)localSeed.Value, combine: true) :
new HashingEstimator.ColumnOptions(samplingKeyColumn, origStratCol, 30, combine: true);
data = new HashingEstimator(env, columnOptions).Fit(data).Transform(data);
}
else
{
if (!data.Schema[samplingKeyColumn].IsNormalized() && (type == NumberDataViewType.Single || type == NumberDataViewType.Double))
{
var origStratCol = samplingKeyColumn;
samplingKeyColumn = data.Schema.GetTempColumnName(samplingKeyColumn);
data = new NormalizingEstimator(env, new NormalizingEstimator.MinMaxColumnOptions(samplingKeyColumn, origStratCol, ensureZeroUntouched: true)).Fit(data).Transform(data);
}
}
}
}
/// <summary>
/// Ensures the provided <paramref name="samplingKeyColumn"/> is valid for <see cref="RangeFilter"/>, hashing it if necessary, or creates a new column <paramref name="samplingKeyColumn"/> is null.
/// </summary>
private void EnsureGroupPreservationColumn(ref IDataView data, ref string samplingKeyColumn, uint?seed = null)
{
// We need to handle two cases: if samplingKeyColumn is provided, we use hashJoin to
// build a single hash of it. If it is not, we generate a random number.
if (samplingKeyColumn == null)
{
samplingKeyColumn = data.Schema.GetTempColumnName("IdPreservationColumn");
data = new GenerateNumberTransform(Environment, data, samplingKeyColumn, seed);
}
else
{
if (!data.Schema.TryGetColumnIndex(samplingKeyColumn, out int stratCol))
{
throw Environment.ExceptSchemaMismatch(nameof(samplingKeyColumn), "GroupPreservationColumn", samplingKeyColumn);
}
var type = data.Schema[stratCol].Type;
if (!RangeFilter.IsValidRangeFilterColumnType(Environment, type))
{
// Hash the samplingKeyColumn.
// REVIEW: this could currently crash, since Hash only accepts a limited set
// of column types. It used to be HashJoin, but we should probably extend Hash
// instead of having two hash transformations.
var origStratCol = samplingKeyColumn;
int tmp;
int inc = 0;
// Generate a new column with the hashed samplingKeyColumn.
while (data.Schema.TryGetColumnIndex(samplingKeyColumn, out tmp))
{
samplingKeyColumn = string.Format("{0}_{1:000}", origStratCol, ++inc);
}
HashingEstimator.ColumnInfo columnInfo;
if (seed.HasValue)
{
columnInfo = new HashingEstimator.ColumnInfo(samplingKeyColumn, origStratCol, 30, seed.Value);
}
else
{
columnInfo = new HashingEstimator.ColumnInfo(samplingKeyColumn, origStratCol, 30);
}
data = new HashingEstimator(Environment, columnInfo).Fit(data).Transform(data);
}
}
}
public void TestMetadata()
{
var data = new[] {
new TestMeta()
{
A = new float[2] {
3.5f, 2.5f
}, B = 1, C = new double[2] {
5.1f, 6.1f
}, D = 7
},
new TestMeta()
{
A = new float[2] {
3.5f, 2.5f
}, B = 1, C = new double[2] {
5.1f, 6.1f
}, D = 7
},
new TestMeta()
{
A = new float[2] {
3.5f, 2.5f
}, B = 1, C = new double[2] {
5.1f, 6.1f
}, D = 7
}
};
var dataView = ComponentCreation.CreateDataView(Env, data);
var pipe = new HashingEstimator(Env, new[] {
new HashingTransformer.ColumnInfo("A", "HashA", invertHash: 1, hashBits: 10),
new HashingTransformer.ColumnInfo("A", "HashAUnlim", invertHash: -1, hashBits: 10),
new HashingTransformer.ColumnInfo("A", "HashAUnlimOrdered", invertHash: -1, hashBits: 10, ordered: true)
});
var result = pipe.Fit(dataView).Transform(dataView);
ValidateMetadata(result);
Done();
}
public void HashWorkout()
{
var data = new[] { new TestClass()
{
A = 1, B = 2, C = 3,
}, new TestClass()
{
A = 4, B = 5, C = 6
} };
var dataView = ComponentCreation.CreateDataView(Env, data);
var pipe = new HashingEstimator(Env, new[] {
new HashingTransformer.ColumnInfo("A", "HashA", hashBits: 4, invertHash: -1),
new HashingTransformer.ColumnInfo("B", "HashB", hashBits: 3, ordered: true),
new HashingTransformer.ColumnInfo("C", "HashC", seed: 42),
new HashingTransformer.ColumnInfo("A", "HashD"),
});
TestEstimatorCore(pipe, dataView);
Done();
}
public void HashWorkout()
{
var data = new[] { new TestClass()
{
A = 1, B = 2, C = 3,
}, new TestClass()
{
A = 4, B = 5, C = 6
} };
var dataView = ML.Data.ReadFromEnumerable(data);
var pipe = new HashingEstimator(Env, new[] {
new HashingTransformer.ColumnInfo("HashA", "A", hashBits: 4, invertHash: -1),
new HashingTransformer.ColumnInfo("HashB", "B", hashBits: 3, ordered: true),
new HashingTransformer.ColumnInfo("HashC", "C", seed: 42),
new HashingTransformer.ColumnInfo("HashD", "A"),
});
TestEstimatorCore(pipe, dataView);
Done();
}
public OneHotHashEncodingEstimator(IHostEnvironment env, params ColumnInfo[] columns)
{
Contracts.CheckValue(env, nameof(env));
_host = env.Register(nameof(ValueToKeyMappingEstimator));
_hash = new HashingEstimator(_host, columns.Select(x => x.HashInfo).ToArray());
using (var ch = _host.Start(nameof(OneHotHashEncodingEstimator)))
{
var binaryCols = new List <(string input, string output)>();
var cols = new List <(string input, string output, bool bag)>();
for (int i = 0; i < columns.Length; i++)
{
var column = columns[i];
CategoricalTransform.OutputKind kind = columns[i].OutputKind;
switch (kind)
{
default:
throw _host.ExceptUserArg(nameof(column.OutputKind));
case CategoricalTransform.OutputKind.Key:
continue;
case CategoricalTransform.OutputKind.Bin:
if ((column.HashInfo.InvertHash) != 0)
{
ch.Warning("Invert hashing is being used with binary encoding.");
}
binaryCols.Add((column.HashInfo.Output, column.HashInfo.Output));
break;
case CategoricalTransform.OutputKind.Ind:
cols.Add((column.HashInfo.Output, column.HashInfo.Output, false));
break;
case CategoricalTransform.OutputKind.Bag:
cols.Add((column.HashInfo.Output, column.HashInfo.Output, true));
break;
}
}
IEstimator <ITransformer> toBinVector = null;
IEstimator <ITransformer> toVector = null;
if (binaryCols.Count > 0)
{
toBinVector = new KeyToBinaryVectorMappingEstimator(_host, binaryCols.Select(x => new KeyToBinaryVectorTransform.ColumnInfo(x.input, x.output)).ToArray());
}
if (cols.Count > 0)
{
toVector = new KeyToVectorMappingEstimator(_host, cols.Select(x => new KeyToVectorTransform.ColumnInfo(x.input, x.output, x.bag)).ToArray());
}
if (toBinVector != null && toVector != null)
{
_toSomething = toVector.Append(toBinVector);
}
else
{
if (toBinVector != null)
{
_toSomething = toBinVector;
}
else
{
_toSomething = toVector;
}
}
}
}
internal CategoricalHashTransform(HashingEstimator hash, IEstimator <ITransformer> keyToVector, IDataView input)
{
var chain = hash.Append(keyToVector);
_transformer = chain.Fit(input);
}
internal OneHotHashEncoding(HashingEstimator hash, IEstimator <ITransformer> keyToVector, IDataView input)
{
var chain = hash.Append(keyToVector);
_transformer = chain.Fit(input);
}
internal static string CreateSplitColumn(IHostEnvironment env, ref IDataView data, string samplingKeyColumn, int?seed = null, bool fallbackInEnvSeed = false)
{
Contracts.CheckValue(env, nameof(env));
Contracts.CheckValueOrNull(samplingKeyColumn);
var splitColumnName = data.Schema.GetTempColumnName("SplitColumn");
int?seedToUse;
if (seed.HasValue)
{
seedToUse = seed.Value;
}
else if (fallbackInEnvSeed)
{
ISeededEnvironment seededEnv = (ISeededEnvironment)env;
seedToUse = seededEnv.Seed;
}
else
{
seedToUse = null;
}
// We need to handle two cases: if samplingKeyColumn is not provided, we generate a random number.
if (samplingKeyColumn == null)
{
data = new GenerateNumberTransform(env, data, splitColumnName, (uint?)seedToUse);
}
else
{
// If samplingKeyColumn was provided we will make a new column based on it, but using a temporary
// name, as it might be dropped elsewhere in the code
if (!data.Schema.TryGetColumnIndex(samplingKeyColumn, out int samplingColIndex))
{
throw env.ExceptSchemaMismatch(nameof(samplingKeyColumn), "SamplingKeyColumn", samplingKeyColumn);
}
var type = data.Schema[samplingColIndex].Type;
if (!RangeFilter.IsValidRangeFilterColumnType(env, type))
{
var hashInputColumnName = samplingKeyColumn;
// HashingEstimator currently handles all primitive types except for DateTime, DateTimeOffset and TimeSpan.
var itemType = type.GetItemType();
if (itemType is DateTimeDataViewType || itemType is DateTimeOffsetDataViewType || itemType is TimeSpanDataViewType)
{
data = new TypeConvertingTransformer(env, splitColumnName, DataKind.Int64, samplingKeyColumn).Transform(data);
hashInputColumnName = splitColumnName;
}
var columnOptions =
seedToUse.HasValue ?
new HashingEstimator.ColumnOptions(splitColumnName, hashInputColumnName, 30, (uint)seedToUse.Value, combine: true) :
new HashingEstimator.ColumnOptions(splitColumnName, hashInputColumnName, 30, combine: true);
data = new HashingEstimator(env, columnOptions).Fit(data).Transform(data);
}
else
{
if (type != NumberDataViewType.Single && type != NumberDataViewType.Double)
{
data = new ColumnCopyingEstimator(env, (splitColumnName, samplingKeyColumn)).Fit(data).Transform(data);
}
else
{
data = new NormalizingEstimator(env, new NormalizingEstimator.MinMaxColumnOptions(splitColumnName, samplingKeyColumn, ensureZeroUntouched: false)).Fit(data).Transform(data);
}
}
}
return(splitColumnName);
}
private string GetSplitColumn(IChannel ch, IDataView input, ref IDataView output)
{
// The stratification column and/or group column, if they exist at all, must be present at this point.
var schema = input.Schema;
output = input;
// If no stratification column was specified, but we have a group column of type Single, Double or
// Key (contiguous) use it.
string stratificationColumn = null;
if (!string.IsNullOrWhiteSpace(Args.StratificationColumn))
{
stratificationColumn = Args.StratificationColumn;
}
else
{
string group = TrainUtils.MatchNameOrDefaultOrNull(ch, schema, nameof(Args.GroupColumn), Args.GroupColumn, DefaultColumnNames.GroupId);
int index;
if (group != null && schema.TryGetColumnIndex(group, out index))
{
// Check if group column key type with known cardinality.
var type = schema[index].Type;
if (type.GetKeyCount() > 0)
{
stratificationColumn = group;
}
}
}
if (string.IsNullOrEmpty(stratificationColumn))
{
stratificationColumn = "StratificationColumn";
int tmp;
int inc = 0;
while (input.Schema.TryGetColumnIndex(stratificationColumn, out tmp))
{
stratificationColumn = string.Format("StratificationColumn_{0:000}", ++inc);
}
var keyGenArgs = new GenerateNumberTransform.Options();
var col = new GenerateNumberTransform.Column();
col.Name = stratificationColumn;
keyGenArgs.Columns = new[] { col };
output = new GenerateNumberTransform(Host, keyGenArgs, input);
}
else
{
int col;
if (!input.Schema.TryGetColumnIndex(stratificationColumn, out col))
{
throw ch.ExceptUserArg(nameof(Arguments.StratificationColumn), "Column '{0}' does not exist", stratificationColumn);
}
var type = input.Schema[col].Type;
if (!RangeFilter.IsValidRangeFilterColumnType(ch, type))
{
ch.Info("Hashing the stratification column");
var origStratCol = stratificationColumn;
int tmp;
int inc = 0;
while (input.Schema.TryGetColumnIndex(stratificationColumn, out tmp))
{
stratificationColumn = string.Format("{0}_{1:000}", origStratCol, ++inc);
}
output = new HashingEstimator(Host, origStratCol, stratificationColumn, 30).Fit(input).Transform(input);
}
}
return(stratificationColumn);
}
