public ColInfoEx(GcnColumn col, GcnArguments args)
{
SubtractMean = col.SubMean ?? args.SubMean;
NormKind = (col.UseStdDev ?? args.UseStdDev) ? NormalizerKind.StdDev : NormalizerKind.L2Norm;
Scale = col.Scale ?? args.Scale;
Contracts.CheckUserArg(0 < Scale && Scale < Float.PositiveInfinity, nameof(args.Scale), "scale must be a positive finite value");
}
/// <summary>
/// A helper method to create LpNormNormalizer transform for public facing API.
/// </summary>
/// <param name="env">Host Environment.</param>
/// <param name="input">Input <see cref="IDataView"/>. This is the output from previous transform or loader.</param>
/// <param name="name">Name of the output column.</param>
/// <param name="source">Name of the column to be transformed. If this is null '<paramref name="name"/>' will be used.</param>
/// <param name="normKind">The norm to use to normalize each sample.</param>
/// <param name="subMean">Subtract mean from each value before normalizing.</param>
public static IDataTransform CreateLpNormNormalizer(IHostEnvironment env,
IDataView input,
string name,
string source = null,
NormalizerKind normKind = Defaults.NormKind,
bool subMean = Defaults.LpSubMean)
{
var args = new Arguments()
{
Column = new[] { new Column()
{
Source = source ?? name,
Name = name
} },
SubMean = subMean,
NormKind = normKind
};
return(new LpNormNormalizerTransform(env, args, input));
}
public ColInfoEx(ModelLoadContext ctx, bool normKindSerialized)
{
Contracts.AssertValue(ctx);
// *** Binary format ***
// byte: subMean
// byte: NormKind
// Float: scale
SubtractMean = ctx.Reader.ReadBoolByte();
byte normKindVal = ctx.Reader.ReadByte();
Contracts.CheckDecode(Enum.IsDefined(typeof(NormalizerKind), normKindVal));
NormKind = (NormalizerKind)normKindVal;
// Note: In early versions, a bool option (useStd) to whether to normalize by StdDev rather than
// L2 norm was used. normKind was added in version=verVectorNormalizerSupported.
// normKind was defined in a way such that the serialized boolean (0: use StdDev, 1: use L2) is
// still valid.
Contracts.CheckDecode(normKindSerialized ||
(NormKind == NormalizerKind.L2Norm || NormKind == NormalizerKind.StdDev));
Scale = ctx.Reader.ReadFloat();
Contracts.CheckDecode(0 < Scale && Scale < Float.PositiveInfinity);
}
public ColInfoEx(Column col, Arguments args)
{
SubtractMean = col.SubMean ?? args.SubMean;
NormKind = col.NormKind ?? args.NormKind;
Scale = 1;
}
/// <include file='doc.xml' path='doc/members/member[@name="LpNormalize"]/*'/>
/// <param name="env">The environment.</param>
/// <param name="inputColumn">The column containing text to tokenize.</param>
/// <param name="outputColumn">The column containing output tokens. Null means <paramref name="inputColumn"/> is replaced.</param>
/// <param name="normKind">Type of norm to use to normalize each sample.</param>
/// <param name="subMean">Subtract mean from each value before normalizing.</param>
public LpNormalizer(IHostEnvironment env, string inputColumn, string outputColumn = null, NormalizerKind normKind = NormalizerKind.L2Norm, bool subMean = false)
: this(env, new[] { (inputColumn, outputColumn ?? inputColumn) }, normKind, subMean)
