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Fixed the TextTransform bug where chargrams where being computed differently when using with/without word tokenizer. #548

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Merged
merged 8 commits into from
Jul 26, 2018
Merged

Fixed the TextTransform bug where chargrams where being computed differently when using with/without word tokenizer. #548

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868a72f
Fixed the TextTransform bug where chargrams where being computed diff…
zeahmed Jul 17, 2018
f482eea
Merge remote-tracking branch 'upstream/master' into texttransform_bug
zeahmed Jul 19, 2018
64390ee
Addressed reviewers' comments.
zeahmed Jul 19, 2018
2201433
Addressed reviewers' comments.
zeahmed Jul 21, 2018
d1dd161
Addressed reviewers' comments.
zeahmed Jul 25, 2018
f458cdb
Merge remote-tracking branch 'upstream/master' into texttransform_bug
zeahmed Jul 25, 2018
90cdf2a
Fixed bugs detected by code analyzer.
zeahmed Jul 25, 2018
3ed6e87
Addressed reviewers' comments.
zeahmed Jul 25, 2018
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78 changes: 74 additions & 4 deletions src/Microsoft.ML.Transforms/Text/CharTokenizeTransform.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -64,12 +64,16 @@ public sealed class Arguments : TransformInputBase
public const string LoaderSignature = "CharToken";
public const string UserName = "Character Tokenizer Transform";

// Keep track of the model that was saved with ver:0x00010001
private readonly bool _isSeparatorStartEnd;

private static VersionInfo GetVersionInfo()
{
return new VersionInfo(
modelSignature: "CHARTOKN",
verWrittenCur: 0x00010001, // Initial
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@TomFinley TomFinley Jul 21, 2018 •
edited by zeahmed
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verWrittenCur: 0x00010001, // Initial [](start = 16, length = 37)

See other examples. You will see that we keep commented out the version strings from old versions, to track them and so we know why we bumped the version each time. This is important: we have live code in our deserializers that is meant to handle those version bumps, and for that reason we like to have documentation on what exactly changed, so that when we have tests on this or that version in our deserializers, we know why they changed. #Resolved

verReadableCur: 0x00010001,
//verWrittenCur: 0x00010001, // Initial
verWrittenCur: 0x00010002, // Updated to use UnitSeparator <US> character instead of using <ETX><STX> for vector inputs.
verReadableCur: 0x00010002,
verWeCanReadBack: 0x00010001,
loaderSignature: LoaderSignature);
}
Expand All @@ -84,6 +88,7 @@ private static VersionInfo GetVersionInfo()
private volatile string _keyValuesStr;
private volatile int[] _keyValuesBoundaries;

private const ushort UnitSeparator = 0x1f;
private const ushort TextStartMarker = 0x02;
private const ushort TextEndMarker = 0x03;
private const int TextMarkersCount = 2;
Expand All @@ -102,6 +107,7 @@ public CharTokenizeTransform(IHostEnvironment env, Arguments args, IDataView inp

_type = GetOutputColumnType();
SetMetadata();
_isSeparatorStartEnd = false;
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@TomFinley TomFinley Jul 25, 2018 •
edited by zeahmed
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FYI there is no need for this. The default value of bool is false. #Resolved

}

private static ColumnType GetOutputColumnType()
Expand All @@ -120,6 +126,8 @@ private CharTokenizeTransform(IHost host, ModelLoadContext ctx, IDataView input)
// byte: _useMarkerChars value.
_useMarkerChars = ctx.Reader.ReadBoolByte();

_isSeparatorStartEnd = ctx.Header.ModelVerReadable < 0x00010002 || ctx.Reader.ReadBoolByte();

_type = GetOutputColumnType();
SetMetadata();
}
Expand All @@ -145,6 +153,7 @@ public override void Save(ModelSaveContext ctx)
// byte: _useMarkerChars value.
SaveBase(ctx);
ctx.Writer.WriteBoolByte(_useMarkerChars);
ctx.Writer.WriteBoolByte(_isSeparatorStartEnd);
}

protected override ColumnType GetColumnTypeCore(int iinfo)
Expand Down Expand Up @@ -399,8 +408,8 @@ private ValueGetter<VBuffer<ushort>> MakeGetterVec(IRow input, int iinfo)

var getSrc = GetSrcGetter<VBuffer<DvText>>(input, iinfo);
var src = default(VBuffer<DvText>);
return
(ref VBuffer<ushort> dst) =>

ValueGetter<VBuffer<ushort>> getterWithStartEndSep = (ref VBuffer<ushort> dst) =>
{
getSrc(ref src);

Expand Down Expand Up @@ -438,6 +447,67 @@ private ValueGetter<VBuffer<ushort>> MakeGetterVec(IRow input, int iinfo)

dst = new VBuffer<ushort>(len, values, dst.Indices);
};

ValueGetter < VBuffer<ushort> > getterWithUnitSep = (ref VBuffer<ushort> dst) =>
{
getSrc(ref src);

int len = 0;

for (int i = 0; i < src.Count; i++)
{
if (src.Values[i].HasChars)
{
len += src.Values[i].Length;

if (i > 0)
len += 1; // add UnitSeparator character to len that will be added
}
}

if (_useMarkerChars)
len += TextMarkersCount;

var values = dst.Values;
if (len > 0)
{
if (Utils.Size(values) < len)
values = new ushort[len];

int index = 0;

// VBuffer<DvText> can be a result of either concatenating text columns together
// or application of word tokenizer before char tokenizer in TextTransform.
//
// Considering VBuffer<DvText> as a single text stream.
// Therefore, prepend and append start and end markers only once i.e. at the start and at end of vector.
// Insert UnitSeparator after every piece of text in the vector.
if (_useMarkerChars)
values[index++] = TextStartMarker;

for (int i = 0; i < src.Count; i++)
{
if (!src.Values[i].HasChars)
continue;

if (i > 0)
values[index++] = UnitSeparator;

for (int ich = 0; ich < src.Values[i].Length; ich++)
{
values[index++] = src.Values[i][ich];
}
}

if (_useMarkerChars)
values[index++] = TextEndMarker;

Contracts.Assert(index == len);
}

dst = new VBuffer<ushort>(len, values, dst.Indices);
};
return _isSeparatorStartEnd ? getterWithStartEndSep : getterWithUnitSep;
}
}
}
54 changes: 25 additions & 29 deletions src/Microsoft.ML.Transforms/Text/TextTransform.cs
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Expand Up @@ -262,6 +262,30 @@ public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataV
view = new ConcatTransform(h, new ConcatTransform.Arguments() { Column = xfCols }, view);
}

if (tparams.NeedsNormalizeTransform)
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@zeahmed zeahmed Jul 19, 2018 •
edited
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@justinormont, I moved TextNormalizer above WordTokenizer. Let me know if there is any adverse effect of it? #Resolved

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@justinormont justinormont Jul 20, 2018 •
edited by zeahmed
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I don't know if there are averse effects of running TextNormalizer before WordTokenizer. I expect it is different, but assume not adversely so. For instance (depending on the specifics of the tokenizer), I don't can be split into {I, do, n't} but if removing punctuation first, it may be split to {I, dont}.

If you make me a build, I'll run a manual regression test. Unfortunately we don't currently have running nightly regression tests to tell us if the text datasets decreased in their core metrics.

#Resolved

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I don't like this change. It's far from clear to me that if someone asks to remove stopwords that they meant for the content of stopwords to be retained in the chargrams. At the very least this ought to be a configurable option.

In reply to: 204000786 [](ancestors = 204000786)

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@zeahmed zeahmed Jul 21, 2018 •
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@TomFinley, Can you elaborate more on this? Your point is not clear to me. Don't you see it good to have TextNormalizer applied before WordTokenizer?

In reply to: 204201054 [](ancestors = 204201054,204000786)

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@TomFinley TomFinley Jul 25, 2018 •
edited by zeahmed
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Sorry thought you were saying something else for some reason got confused. #Resolved

{
var xfCols = new TextNormalizerCol[textCols.Length];
string[] dstCols = new string[textCols.Length];
for (int i = 0; i < textCols.Length; i++)
{
dstCols[i] = GenerateColumnName(view.Schema, textCols[i], "TextNormalizer");
tempCols.Add(dstCols[i]);
xfCols[i] = new TextNormalizerCol() { Source = textCols[i], Name = dstCols[i] };
}

view = new TextNormalizerTransform(h,
new TextNormalizerArgs()
{
Column = xfCols,
KeepDiacritics = tparams.KeepDiacritics,
KeepNumbers = tparams.KeepNumbers,
KeepPunctuations = tparams.KeepPunctuations,
TextCase = tparams.TextCase
}, view);

textCols = dstCols;
}

if (tparams.NeedsWordTokenizationTransform)
{
var xfCols = new DelimitedTokenizeTransform.Column[textCols.Length];
Expand All @@ -281,34 +305,6 @@ public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataV
view = new DelimitedTokenizeTransform(h, new DelimitedTokenizeTransform.Arguments() { Column = xfCols }, view);
}

if (tparams.NeedsNormalizeTransform)
{
string[] srcCols = wordTokCols == null ? textCols : wordTokCols;
var xfCols = new TextNormalizerCol[srcCols.Length];
string[] dstCols = new string[srcCols.Length];
for (int i = 0; i < srcCols.Length; i++)
{
dstCols[i] = GenerateColumnName(view.Schema, srcCols[i], "TextNormalizer");
tempCols.Add(dstCols[i]);
xfCols[i] = new TextNormalizerCol() { Source = srcCols[i], Name = dstCols[i] };
}

view = new TextNormalizerTransform(h,
new TextNormalizerArgs()
{
Column = xfCols,
KeepDiacritics = tparams.KeepDiacritics,
KeepNumbers = tparams.KeepNumbers,
KeepPunctuations = tparams.KeepPunctuations,
TextCase = tparams.TextCase
}, view);

if (wordTokCols != null)
wordTokCols = dstCols;
else
textCols = dstCols;
}

if (tparams.NeedsRemoveStopwordsTransform)
{
Contracts.Assert(wordTokCols != null, "StopWords transform requires that word tokenization has been applied to the input text.");
Expand Down Expand Up @@ -360,7 +356,7 @@ public static IDataTransform Create(IHostEnvironment env, Arguments args, IDataV
if (tparams.CharExtractorFactory != null)
{
{
var srcCols = wordTokCols ?? textCols;
var srcCols = tparams.NeedsRemoveStopwordsTransform ? wordTokCols : textCols;
charTokCols = new string[srcCols.Length];
var xfCols = new CharTokenizeTransform.Column[srcCols.Length];
for (int i = 0; i < srcCols.Length; i++)
Expand Down
2 changes: 1 addition & 1 deletion test/Microsoft.ML.Predictor.Tests/TestPipelineSweeper.cs
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Expand Up @@ -308,7 +308,7 @@ public void PipelineSweeperRoles()
var trainAuc = bestPipeline.PerformanceSummary.TrainingMetricValue;
var testAuc = bestPipeline.PerformanceSummary.MetricValue;
Assert.True((0.94 < trainAuc) && (trainAuc < 0.95));
Assert.True((0.83 < testAuc) && (testAuc < 0.84));
Assert.True((0.815 < testAuc) && (testAuc < 0.825));

var results = runner.GetOutput<IDataView>("ResultsOut");
Assert.NotNull(results);
Expand Down
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