[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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Merged
michaelgsharp merged 5 commits into from
Jan 9, 2024
Merged

[release/3.0] Fixes NER to correctly expand/shrink the labels #6946

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4221b0f
ner options fix
michaelgsharp Dec 12, 2023
dcadf3e
Ner fixed.
michaelgsharp Dec 24, 2023
24ecb34
Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs
michaelgsharp Jan 3, 2024
90a234f
fixes from PR comments
michaelgsharp Jan 4, 2024
134771e
fixed build
michaelgsharp Jan 5, 2024
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2 changes: 0 additions & 2 deletions src/Microsoft.ML.Tokenizers/Model/Model.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
/// <param name="ch"></param>
/// <returns></returns>
public abstract bool IsValidChar(char ch);

}

}
14 changes: 9 additions & 5 deletions src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
}

private protected override torch.Tensor PrepareRowTensor()
private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
{
ReadOnlyMemory<char> sentence1 = default;
Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
= FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
getSentence1(ref sentence1);
if (getSentence2 == default)
{
return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
// 0 Is the init token and must be at the beginning.
newList.Insert(0, 0);
return newList;
}
else
{
getSentence2(ref sentence2);
return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
.Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
.Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
}
}

Expand Down
85 changes: 77 additions & 8 deletions src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs
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Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
///
public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
{
private const char StartChar = (char)(' ' + 256);

public class NerOptions : NasBertOptions
{
public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
EncoderOutputDim = 384;
EmbeddingDim = 128;
Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
TaskType = BertTaskType.NamedEntityRecognition;
}
}
internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
BatchSize = batchSize,
MaxEpoch = maxEpochs,
ValidationSet = validationSet,
TaskType = BertTaskType.NamedEntityRecognition
})
{
}
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
}

internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

private protected class Trainer : NasBertTrainerBase
{
private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
{
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
return torch.tensor(targetArray, device: Device);
}

private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
{
ReadOnlyMemory<char> sentenceRom = default;
Sentence1Getter(ref sentenceRom);
var sentence = sentenceRom.ToString();
Tensor t;
var encoding = Tokenizer.Encode(sentence);

if (target.Length != encoding.Tokens.Count)
{
var targetIndex = 0;
var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
var newValues = targetEditor.Values;
for (var i = 0; i < encoding.Tokens.Count; i++)
{
if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
{
newValues[i] = target.GetItemOrDefault(++targetIndex);
}
else
{
newValues[i] = target.GetItemOrDefault(targetIndex);
}
}
target = targetEditor.Commit();
}
t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

if (t.NumberOfElements > 512)
t = t.slice(0, 0, 512, 1);

return t;
}

[MethodImpl(MethodImplOptions.AggressiveInlining)]
private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
{
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

}

private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
{
var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
TokenizerResult encoding = tokenizer.Encode(sentence);

var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
var prediction = argmax.ToArray<long>();

var targetIndex = 0;
// Figure out actual count of output tokens
for (var i = 0; i < encoding.Tokens.Count; i++)
{
if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
{
targetIndex++;
}
}

var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
var newValues = editor.Values;
targetIndex = 0;

newValues[targetIndex++] = (uint)prediction[0];

for (var i = 1; i < encoding.Tokens.Count; i++)
{
if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
{
newValues[targetIndex++] = (uint)prediction[i];
}
}

dst = editor.Commit();
}

private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
{
ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
var prediction = argmax.ToArray<long>();

var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
for (int i = 1; i < prediction.Length; i++)
{
editor.Values[i - 1] = (uint)prediction[i];
}

dst = editor.Commit();
CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
};

return classification;
Expand Down
6 changes: 3 additions & 3 deletions src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
cursorValid = cursor.MoveNext();
if (cursorValid)
{
inputTensors.Add(PrepareRowTensor());
TLabelCol target = default;
labelGetter(ref target);
inputTensors.Add(PrepareRowTensor(ref target));
targets.Add(AddToTargets(target));
}
else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
cursorValid = cursor.MoveNext();
if (cursorValid)
{
inputTensors.Add(PrepareRowTensor());
TLabelCol target = default;
labelGetter(ref target);
inputTensors.Add(PrepareRowTensor(ref target));
targets.Add(AddToTargets(target));
}
else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

private protected abstract torch.Tensor PrepareRowTensor();
private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

[MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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 Merged

michaelgsharp
merged 5 commits into

from

Jan 9, 2024
 Merged


[release/3.0] Fixes NER to correctly expand/shrink the labels
#6946
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4221b0f

ner options fix


michaelgsharp Dec 12, 2023
dcadf3e

Ner fixed.


michaelgsharp Dec 24, 2023
24ecb34

Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs


michaelgsharp Jan 3, 2024
90a234f

fixes from PR comments


michaelgsharp Jan 4, 2024
134771e

fixed build


michaelgsharp Jan 5, 2024

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2 changes: 0 additions & 2 deletions
src/Microsoft.ML.Tokenizers/Model/Model.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
 /// <param name="ch"></param>
 /// <returns></returns>
 public abstract bool IsValidChar(char ch);

 }

}

14 changes: 9 additions & 5 deletions
src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
 return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor()
 private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
 {
 ReadOnlyMemory<char> sentence1 = default;
 Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

 private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
 = FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

 internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
 internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

 public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
 base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
 getSentence1(ref sentence1);
 if (getSentence2 == default)
 {
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
 List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
 // 0 Is the init token and must be at the beginning.
 newList.Insert(0, 0);
 return newList;
 }
 else
 {
 getSentence2(ref sentence2);
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 }
 }

Expand Down

85 changes: 77 additions & 8 deletions
src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
 NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
 ///
 public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
 {
 private const char StartChar = (char)(' ' + 256);

 public class NerOptions : NasBertOptions
 {
 public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
 EncoderOutputDim = 384;
 EmbeddingDim = 128;
 Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
 TaskType = BertTaskType.NamedEntityRecognition;
 }
 }
 internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
 BatchSize = batchSize,
 MaxEpoch = maxEpochs,
 ValidationSet = validationSet,
 TaskType = BertTaskType.NamedEntityRecognition
 })
 {
 }
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
 return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
 }

 internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

 private protected class Trainer : NasBertTrainerBase
 {
 private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
 internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

 public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
 {
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
 return torch.tensor(targetArray, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
 {
 ReadOnlyMemory<char> sentenceRom = default;
 Sentence1Getter(ref sentenceRom);
 var sentence = sentenceRom.ToString();
 Tensor t;
 var encoding = Tokenizer.Encode(sentence);

 if (target.Length != encoding.Tokens.Count)
 {
 var targetIndex = 0;
 var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
 var newValues = targetEditor.Values;
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[i] = target.GetItemOrDefault(++targetIndex);
 }
 else
 {
 newValues[i] = target.GetItemOrDefault(targetIndex);
 }
 }
 target = targetEditor.Commit();
 }
 t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

 if (t.NumberOfElements > 512)
 t = t.slice(0, 0, 512, 1);

 return t;
 }

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
 private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
 {
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

 }

 private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
 {
 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
 TokenizerResult encoding = tokenizer.Encode(sentence);

 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var targetIndex = 0;
 // Figure out actual count of output tokens
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 targetIndex++;
 }
 }

 var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
 var newValues = editor.Values;
 targetIndex = 0;

 newValues[targetIndex++] = (uint)prediction[0];

 for (var i = 1; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[targetIndex++] = (uint)prediction[i];
 }
 }

 dst = editor.Commit();
 }

 private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
 {
 ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
 for (int i = 1; i < prediction.Length; i++)
 {
 editor.Values[i - 1] = (uint)prediction[i];
 }

 dst = editor.Commit();
 CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
 };

 return classification;
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

 private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

 private protected abstract torch.Tensor PrepareRowTensor();
 private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
 private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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 Merged

michaelgsharp
merged 5 commits into

from

Jan 9, 2024
 Merged


[release/3.0] Fixes NER to correctly expand/shrink the labels
#6946
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4221b0f

ner options fix


michaelgsharp Dec 12, 2023
dcadf3e

Ner fixed.


michaelgsharp Dec 24, 2023
24ecb34

Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs


michaelgsharp Jan 3, 2024
90a234f

fixes from PR comments


michaelgsharp Jan 4, 2024
134771e

fixed build


michaelgsharp Jan 5, 2024

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2 changes: 0 additions & 2 deletions
src/Microsoft.ML.Tokenizers/Model/Model.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
 /// <param name="ch"></param>
 /// <returns></returns>
 public abstract bool IsValidChar(char ch);

 }

}

14 changes: 9 additions & 5 deletions
src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
 return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor()
 private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
 {
 ReadOnlyMemory<char> sentence1 = default;
 Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

 private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
 = FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

 internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
 internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

 public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
 base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
 getSentence1(ref sentence1);
 if (getSentence2 == default)
 {
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
 List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
 // 0 Is the init token and must be at the beginning.
 newList.Insert(0, 0);
 return newList;
 }
 else
 {
 getSentence2(ref sentence2);
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 }
 }

Expand Down

85 changes: 77 additions & 8 deletions
src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
 NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
 ///
 public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
 {
 private const char StartChar = (char)(' ' + 256);

 public class NerOptions : NasBertOptions
 {
 public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
 EncoderOutputDim = 384;
 EmbeddingDim = 128;
 Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
 TaskType = BertTaskType.NamedEntityRecognition;
 }
 }
 internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
 BatchSize = batchSize,
 MaxEpoch = maxEpochs,
 ValidationSet = validationSet,
 TaskType = BertTaskType.NamedEntityRecognition
 })
 {
 }
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
 return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
 }

 internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

 private protected class Trainer : NasBertTrainerBase
 {
 private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
 internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

 public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
 {
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
 return torch.tensor(targetArray, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
 {
 ReadOnlyMemory<char> sentenceRom = default;
 Sentence1Getter(ref sentenceRom);
 var sentence = sentenceRom.ToString();
 Tensor t;
 var encoding = Tokenizer.Encode(sentence);

 if (target.Length != encoding.Tokens.Count)
 {
 var targetIndex = 0;
 var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
 var newValues = targetEditor.Values;
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[i] = target.GetItemOrDefault(++targetIndex);
 }
 else
 {
 newValues[i] = target.GetItemOrDefault(targetIndex);
 }
 }
 target = targetEditor.Commit();
 }
 t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

 if (t.NumberOfElements > 512)
 t = t.slice(0, 0, 512, 1);

 return t;
 }

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
 private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
 {
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

 }

 private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
 {
 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
 TokenizerResult encoding = tokenizer.Encode(sentence);

 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var targetIndex = 0;
 // Figure out actual count of output tokens
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 targetIndex++;
 }
 }

 var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
 var newValues = editor.Values;
 targetIndex = 0;

 newValues[targetIndex++] = (uint)prediction[0];

 for (var i = 1; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[targetIndex++] = (uint)prediction[i];
 }
 }

 dst = editor.Commit();
 }

 private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
 {
 ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
 for (int i = 1; i < prediction.Length; i++)
 {
 editor.Values[i - 1] = (uint)prediction[i];
 }

 dst = editor.Commit();
 CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
 };

 return classification;
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

 private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

 private protected abstract torch.Tensor PrepareRowTensor();
 private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
 private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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 Merged

michaelgsharp
merged 5 commits into

from

Jan 9, 2024
 Merged


[release/3.0] Fixes NER to correctly expand/shrink the labels
#6946
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4221b0f

ner options fix


michaelgsharp Dec 12, 2023
dcadf3e

Ner fixed.


michaelgsharp Dec 24, 2023
24ecb34

Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs


michaelgsharp Jan 3, 2024
90a234f

fixes from PR comments


michaelgsharp Jan 4, 2024
134771e

fixed build


michaelgsharp Jan 5, 2024

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2 changes: 0 additions & 2 deletions
src/Microsoft.ML.Tokenizers/Model/Model.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
 /// <param name="ch"></param>
 /// <returns></returns>
 public abstract bool IsValidChar(char ch);

 }

}

14 changes: 9 additions & 5 deletions
src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
 return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor()
 private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
 {
 ReadOnlyMemory<char> sentence1 = default;
 Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

 private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
 = FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

 internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
 internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

 public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
 base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
 getSentence1(ref sentence1);
 if (getSentence2 == default)
 {
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
 List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
 // 0 Is the init token and must be at the beginning.
 newList.Insert(0, 0);
 return newList;
 }
 else
 {
 getSentence2(ref sentence2);
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 }
 }

Expand Down

85 changes: 77 additions & 8 deletions
src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
 NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
 ///
 public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
 {
 private const char StartChar = (char)(' ' + 256);

 public class NerOptions : NasBertOptions
 {
 public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
 EncoderOutputDim = 384;
 EmbeddingDim = 128;
 Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
 TaskType = BertTaskType.NamedEntityRecognition;
 }
 }
 internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
 BatchSize = batchSize,
 MaxEpoch = maxEpochs,
 ValidationSet = validationSet,
 TaskType = BertTaskType.NamedEntityRecognition
 })
 {
 }
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
 return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
 }

 internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

 private protected class Trainer : NasBertTrainerBase
 {
 private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
 internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

 public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
 {
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
 return torch.tensor(targetArray, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
 {
 ReadOnlyMemory<char> sentenceRom = default;
 Sentence1Getter(ref sentenceRom);
 var sentence = sentenceRom.ToString();
 Tensor t;
 var encoding = Tokenizer.Encode(sentence);

 if (target.Length != encoding.Tokens.Count)
 {
 var targetIndex = 0;
 var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
 var newValues = targetEditor.Values;
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[i] = target.GetItemOrDefault(++targetIndex);
 }
 else
 {
 newValues[i] = target.GetItemOrDefault(targetIndex);
 }
 }
 target = targetEditor.Commit();
 }
 t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

 if (t.NumberOfElements > 512)
 t = t.slice(0, 0, 512, 1);

 return t;
 }

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
 private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
 {
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

 }

 private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
 {
 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
 TokenizerResult encoding = tokenizer.Encode(sentence);

 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var targetIndex = 0;
 // Figure out actual count of output tokens
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 targetIndex++;
 }
 }

 var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
 var newValues = editor.Values;
 targetIndex = 0;

 newValues[targetIndex++] = (uint)prediction[0];

 for (var i = 1; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[targetIndex++] = (uint)prediction[i];
 }
 }

 dst = editor.Commit();
 }

 private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
 {
 ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
 for (int i = 1; i < prediction.Length; i++)
 {
 editor.Values[i - 1] = (uint)prediction[i];
 }

 dst = editor.Commit();
 CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
 };

 return classification;
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

 private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

 private protected abstract torch.Tensor PrepareRowTensor();
 private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
 private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

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Sign in
to your account

 Merged

michaelgsharp
merged 5 commits into

from

Jan 9, 2024
 Merged


[release/3.0] Fixes NER to correctly expand/shrink the labels
#6946
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4221b0f

ner options fix


michaelgsharp Dec 12, 2023
dcadf3e

Ner fixed.


michaelgsharp Dec 24, 2023
24ecb34

Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs


michaelgsharp Jan 3, 2024
90a234f

fixes from PR comments


michaelgsharp Jan 4, 2024
134771e

fixed build


michaelgsharp Jan 5, 2024

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2 changes: 0 additions & 2 deletions
src/Microsoft.ML.Tokenizers/Model/Model.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
 /// <param name="ch"></param>
 /// <returns></returns>
 public abstract bool IsValidChar(char ch);

 }

}

14 changes: 9 additions & 5 deletions
src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
 return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor()
 private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
 {
 ReadOnlyMemory<char> sentence1 = default;
 Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

 private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
 = FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

 internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
 internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

 public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
 base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
 getSentence1(ref sentence1);
 if (getSentence2 == default)
 {
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
 List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
 // 0 Is the init token and must be at the beginning.
 newList.Insert(0, 0);
 return newList;
 }
 else
 {
 getSentence2(ref sentence2);
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 }
 }

Expand Down

85 changes: 77 additions & 8 deletions
src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
 NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
 ///
 public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
 {
 private const char StartChar = (char)(' ' + 256);

 public class NerOptions : NasBertOptions
 {
 public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
 EncoderOutputDim = 384;
 EmbeddingDim = 128;
 Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
 TaskType = BertTaskType.NamedEntityRecognition;
 }
 }
 internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
 BatchSize = batchSize,
 MaxEpoch = maxEpochs,
 ValidationSet = validationSet,
 TaskType = BertTaskType.NamedEntityRecognition
 })
 {
 }
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
 return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
 }

 internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

 private protected class Trainer : NasBertTrainerBase
 {
 private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
 internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

 public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
 {
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
 return torch.tensor(targetArray, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
 {
 ReadOnlyMemory<char> sentenceRom = default;
 Sentence1Getter(ref sentenceRom);
 var sentence = sentenceRom.ToString();
 Tensor t;
 var encoding = Tokenizer.Encode(sentence);

 if (target.Length != encoding.Tokens.Count)
 {
 var targetIndex = 0;
 var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
 var newValues = targetEditor.Values;
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[i] = target.GetItemOrDefault(++targetIndex);
 }
 else
 {
 newValues[i] = target.GetItemOrDefault(targetIndex);
 }
 }
 target = targetEditor.Commit();
 }
 t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

 if (t.NumberOfElements > 512)
 t = t.slice(0, 0, 512, 1);

 return t;
 }

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
 private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
 {
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

 }

 private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
 {
 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
 TokenizerResult encoding = tokenizer.Encode(sentence);

 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var targetIndex = 0;
 // Figure out actual count of output tokens
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 targetIndex++;
 }
 }

 var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
 var newValues = editor.Values;
 targetIndex = 0;

 newValues[targetIndex++] = (uint)prediction[0];

 for (var i = 1; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[targetIndex++] = (uint)prediction[i];
 }
 }

 dst = editor.Commit();
 }

 private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
 {
 ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
 for (int i = 1; i < prediction.Length; i++)
 {
 editor.Values[i - 1] = (uint)prediction[i];
 }

 dst = editor.Commit();
 CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
 };

 return classification;
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

 private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

 private protected abstract torch.Tensor PrepareRowTensor();
 private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
 private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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 Merged

michaelgsharp
merged 5 commits into

from

Jan 9, 2024
 Merged


[release/3.0] Fixes NER to correctly expand/shrink the labels
#6946
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4221b0f

ner options fix


michaelgsharp Dec 12, 2023
dcadf3e

Ner fixed.


michaelgsharp Dec 24, 2023
24ecb34

Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs


michaelgsharp Jan 3, 2024
90a234f

fixes from PR comments


michaelgsharp Jan 4, 2024
134771e

fixed build


michaelgsharp Jan 5, 2024

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2 changes: 0 additions & 2 deletions
src/Microsoft.ML.Tokenizers/Model/Model.cs

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Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
 /// <param name="ch"></param>
 /// <returns></returns>
 public abstract bool IsValidChar(char ch);

 }

}

14 changes: 9 additions & 5 deletions
src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
 return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor()
 private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
 {
 ReadOnlyMemory<char> sentence1 = default;
 Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

 private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
 = FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

 internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
 internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

 public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
 base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
 getSentence1(ref sentence1);
 if (getSentence2 == default)
 {
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
 List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
 // 0 Is the init token and must be at the beginning.
 newList.Insert(0, 0);
 return newList;
 }
 else
 {
 getSentence2(ref sentence2);
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 }
 }

Expand Down

85 changes: 77 additions & 8 deletions
src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
 NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
 ///
 public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
 {
 private const char StartChar = (char)(' ' + 256);

 public class NerOptions : NasBertOptions
 {
 public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
 EncoderOutputDim = 384;
 EmbeddingDim = 128;
 Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
 TaskType = BertTaskType.NamedEntityRecognition;
 }
 }
 internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
 BatchSize = batchSize,
 MaxEpoch = maxEpochs,
 ValidationSet = validationSet,
 TaskType = BertTaskType.NamedEntityRecognition
 })
 {
 }
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
 return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
 }

 internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

 private protected class Trainer : NasBertTrainerBase
 {
 private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
 internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

 public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
 {
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
 return torch.tensor(targetArray, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
 {
 ReadOnlyMemory<char> sentenceRom = default;
 Sentence1Getter(ref sentenceRom);
 var sentence = sentenceRom.ToString();
 Tensor t;
 var encoding = Tokenizer.Encode(sentence);

 if (target.Length != encoding.Tokens.Count)
 {
 var targetIndex = 0;
 var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
 var newValues = targetEditor.Values;
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[i] = target.GetItemOrDefault(++targetIndex);
 }
 else
 {
 newValues[i] = target.GetItemOrDefault(targetIndex);
 }
 }
 target = targetEditor.Commit();
 }
 t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

 if (t.NumberOfElements > 512)
 t = t.slice(0, 0, 512, 1);

 return t;
 }

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
 private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
 {
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

 }

 private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
 {
 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
 TokenizerResult encoding = tokenizer.Encode(sentence);

 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var targetIndex = 0;
 // Figure out actual count of output tokens
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 targetIndex++;
 }
 }

 var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
 var newValues = editor.Values;
 targetIndex = 0;

 newValues[targetIndex++] = (uint)prediction[0];

 for (var i = 1; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[targetIndex++] = (uint)prediction[i];
 }
 }

 dst = editor.Commit();
 }

 private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
 {
 ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
 for (int i = 1; i < prediction.Length; i++)
 {
 editor.Values[i - 1] = (uint)prediction[i];
 }

 dst = editor.Commit();
 CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
 };

 return classification;
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

 private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

 private protected abstract torch.Tensor PrepareRowTensor();
 private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
 private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
Sign in
to your account

 Merged

michaelgsharp
merged 5 commits into

from

Jan 9, 2024
 Merged


[release/3.0] Fixes NER to correctly expand/shrink the labels
#6946
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4221b0f

ner options fix


michaelgsharp Dec 12, 2023
dcadf3e

Ner fixed.


michaelgsharp Dec 24, 2023
24ecb34

Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs


michaelgsharp Jan 3, 2024
90a234f

fixes from PR comments


michaelgsharp Jan 4, 2024
134771e

fixed build


michaelgsharp Jan 5, 2024

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2 changes: 0 additions & 2 deletions
src/Microsoft.ML.Tokenizers/Model/Model.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
 /// <param name="ch"></param>
 /// <returns></returns>
 public abstract bool IsValidChar(char ch);

 }

}

14 changes: 9 additions & 5 deletions
src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
 return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor()
 private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
 {
 ReadOnlyMemory<char> sentence1 = default;
 Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

 private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
 = FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

 internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
 internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

 public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
 base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
 getSentence1(ref sentence1);
 if (getSentence2 == default)
 {
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
 List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
 // 0 Is the init token and must be at the beginning.
 newList.Insert(0, 0);
 return newList;
 }
 else
 {
 getSentence2(ref sentence2);
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 }
 }

Expand Down

85 changes: 77 additions & 8 deletions
src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
 NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
 ///
 public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
 {
 private const char StartChar = (char)(' ' + 256);

 public class NerOptions : NasBertOptions
 {
 public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
 EncoderOutputDim = 384;
 EmbeddingDim = 128;
 Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
 TaskType = BertTaskType.NamedEntityRecognition;
 }
 }
 internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
 BatchSize = batchSize,
 MaxEpoch = maxEpochs,
 ValidationSet = validationSet,
 TaskType = BertTaskType.NamedEntityRecognition
 })
 {
 }
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
 return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
 }

 internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

 private protected class Trainer : NasBertTrainerBase
 {
 private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
 internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

 public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
 {
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
 return torch.tensor(targetArray, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
 {
 ReadOnlyMemory<char> sentenceRom = default;
 Sentence1Getter(ref sentenceRom);
 var sentence = sentenceRom.ToString();
 Tensor t;
 var encoding = Tokenizer.Encode(sentence);

 if (target.Length != encoding.Tokens.Count)
 {
 var targetIndex = 0;
 var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
 var newValues = targetEditor.Values;
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[i] = target.GetItemOrDefault(++targetIndex);
 }
 else
 {
 newValues[i] = target.GetItemOrDefault(targetIndex);
 }
 }
 target = targetEditor.Commit();
 }
 t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

 if (t.NumberOfElements > 512)
 t = t.slice(0, 0, 512, 1);

 return t;
 }

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
 private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
 {
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

 }

 private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
 {
 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
 TokenizerResult encoding = tokenizer.Encode(sentence);

 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var targetIndex = 0;
 // Figure out actual count of output tokens
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 targetIndex++;
 }
 }

 var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
 var newValues = editor.Values;
 targetIndex = 0;

 newValues[targetIndex++] = (uint)prediction[0];

 for (var i = 1; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[targetIndex++] = (uint)prediction[i];
 }
 }

 dst = editor.Commit();
 }

 private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
 {
 ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
 for (int i = 1; i < prediction.Length; i++)
 {
 editor.Values[i - 1] = (uint)prediction[i];
 }

 dst = editor.Commit();
 CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
 };

 return classification;
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

 private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

 private protected abstract torch.Tensor PrepareRowTensor();
 private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
 private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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[release/3.0] Fixes NER to correctly expand/shrink the labels#6946

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 Merged

michaelgsharp
merged 5 commits into

from

Jan 9, 2024
 Merged


[release/3.0] Fixes NER to correctly expand/shrink the labels
#6946
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4221b0f

ner options fix


michaelgsharp Dec 12, 2023
dcadf3e

Ner fixed.


michaelgsharp Dec 24, 2023
24ecb34

Update src/Microsoft.ML.Tokenizers/Model/EnglishRoberta.cs


michaelgsharp Jan 3, 2024
90a234f

fixes from PR comments


michaelgsharp Jan 4, 2024
134771e

fixed build


michaelgsharp Jan 5, 2024

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2 changes: 0 additions & 2 deletions
src/Microsoft.ML.Tokenizers/Model/Model.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -66,7 +66,5 @@ public abstract class Model
 /// <param name="ch"></param>
 /// <returns></returns>
 public abstract bool IsValidChar(char ch);

 }

}

14 changes: 9 additions & 5 deletions
src/Microsoft.ML.TorchSharp/NasBert/NasBertTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -240,7 +240,7 @@ private protected override torch.Tensor PrepareBatchTensor(ref List<Tensor> inpu
 return DataUtils.CollateTokens(inputTensors, Tokenizer.RobertaModel().PadIndex, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor()
 private protected override torch.Tensor PrepareRowTensor(ref TLabelCol target)
 {
 ReadOnlyMemory<char> sentence1 = default;
 Sentence1Getter(ref sentence1);
Expand DownExpand Up@@ -494,7 +494,8 @@ private protected abstract class NasBertMapper : TorchSharpBaseMapper

 private static readonly FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate> _makeLabelAnnotationGetter
 = FuncInstanceMethodInfo1<NasBertMapper, DataViewSchema.DetachedColumn, Delegate>.Create(target => target.GetLabelAnnotations<int>);

 internal static readonly int[] InitTokenArray = new[] { 0 /* InitToken */ };
 internal static readonly int[] SeperatorTokenArray = new[] { 2 /* SeperatorToken */ };

 public NasBertMapper(TorchSharpBaseTransformer<TLabelCol, TTargetsCol> parent, DataViewSchema inputSchema) :
 base(parent, inputSchema)
Expand DownExpand Up@@ -583,13 +584,16 @@ private IList<int> PrepInputTokens(ref ReadOnlyMemory<char> sentence1, ref ReadO
 getSentence1(ref sentence1);
 if (getSentence2 == default)
 {
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString())).ToList();
 List<int> newList = new List<int>(tokenizer.EncodeToConverted(sentence1.ToString()));
 // 0 Is the init token and must be at the beginning.
 newList.Insert(0, 0);
 return newList;
 }
 else
 {
 getSentence2(ref sentence2);
 return new[] { 0 /* InitToken */ }.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(new[] { 2 /* SeperatorToken */ }).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 return InitTokenArray.Concat(tokenizer.EncodeToConverted(sentence1.ToString()))
 .Concat(SeperatorTokenArray).Concat(tokenizer.EncodeToConverted(sentence2.ToString())).ToList();
 }
 }

Expand Down

85 changes: 77 additions & 8 deletions
src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -19,6 +19,7 @@
using Microsoft.ML.TorchSharp.NasBert.Models;
using TorchSharp;
using static Microsoft.ML.TorchSharp.NasBert.NasBertTrainer;
using static TorchSharp.torch;

[assembly: LoadableClass(typeof(NerTransformer), null, typeof(SignatureLoadModel),
 NerTransformer.UserName, NerTransformer.LoaderSignature)]
Expand DownExpand Up@@ -61,6 +62,8 @@ namespace Microsoft.ML.TorchSharp.NasBert
 ///
 public class NerTrainer : NasBertTrainer<VBuffer<uint>, TargetType>
 {
 private const char StartChar = (char)(' ' + 256);

 public class NerOptions : NasBertOptions
 {
 public NerOptions()
Expand All@@ -69,6 +72,7 @@ public NerOptions()
 EncoderOutputDim = 384;
 EmbeddingDim = 128;
 Arches = new int[] { 15, 16, 14, 0, 0, 0, 15, 16, 14, 0, 0, 0, 17, 14, 15, 0, 0, 0, 17, 14, 15, 0, 0, 0 };
 TaskType = BertTaskType.NamedEntityRecognition;
 }
 }
 internal NerTrainer(IHostEnvironment env, NerOptions options) : base(env, options)
Expand All@@ -93,7 +97,6 @@ internal NerTrainer(IHostEnvironment env,
 BatchSize = batchSize,
 MaxEpoch = maxEpochs,
 ValidationSet = validationSet,
 TaskType = BertTaskType.NamedEntityRecognition
 })
 {
 }
Expand All@@ -108,9 +111,12 @@ private protected override TorchSharpBaseTransformer<VBuffer<uint>, TargetType>
 return new NerTransformer(host, options as NasBertOptions, model as NasBertModel, labelColumn);
 }

 internal static bool TokenStartsWithSpace(string token) => token is null || (token.Length != 0 && token[0] == StartChar);

 private protected class Trainer : NasBertTrainerBase
 {
 private const string ModelUrlString = "models/pretrained_NasBert_14M_encoder.tsm";
 internal static readonly int[] ZeroArray = new int[] { 0 /* InitToken */};

 public Trainer(TorchSharpBaseTrainer<VBuffer<uint>, TargetType> parent, IChannel ch, IDataView input) : base(parent, ch, input, ModelUrlString)
 {
Expand DownExpand Up@@ -155,6 +161,40 @@ private protected override torch.Tensor CreateTargetsTensor(ref List<TargetType>
 return torch.tensor(targetArray, device: Device);
 }

 private protected override torch.Tensor PrepareRowTensor(ref VBuffer<uint> target)
 {
 ReadOnlyMemory<char> sentenceRom = default;
 Sentence1Getter(ref sentenceRom);
 var sentence = sentenceRom.ToString();
 Tensor t;
 var encoding = Tokenizer.Encode(sentence);

 if (target.Length != encoding.Tokens.Count)
 {
 var targetIndex = 0;
 var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
 var newValues = targetEditor.Values;
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[i] = target.GetItemOrDefault(++targetIndex);
 }
 else
 {
 newValues[i] = target.GetItemOrDefault(targetIndex);
 }
 }
 target = targetEditor.Commit();
 }
 t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().IdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);

 if (t.NumberOfElements > 512)
 t = t.slice(0, 0, 512, 1);

 return t;
 }

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
 private protected override int GetNumCorrect(torch.Tensor predictions, torch.Tensor targets)
 {
Expand DownExpand Up@@ -334,6 +374,41 @@ private protected override Delegate CreateGetter(DataViewRow input, int iinfo, T

 }

 private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
 {
 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
 TokenizerResult encoding = tokenizer.Encode(sentence);

 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var targetIndex = 0;
 // Figure out actual count of output tokens
 for (var i = 0; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 targetIndex++;
 }
 }

 var editor = VBufferEditor.Create(ref dst, targetIndex + 1);
 var newValues = editor.Values;
 targetIndex = 0;

 newValues[targetIndex++] = (uint)prediction[0];

 for (var i = 1; i < encoding.Tokens.Count; i++)
 {
 if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
 {
 newValues[targetIndex++] = (uint)prediction[i];
 }
 }

 dst = editor.Commit();
 }

 private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, TensorCacher outputCacher)
 {
 ValueGetter<ReadOnlyMemory<char>> getSentence1 = default;
Expand All@@ -353,13 +428,7 @@ private Delegate MakePredictedLabelGetter(DataViewRow input, IChannel ch, Tensor
 var argmax = (outputCacher as BertTensorCacher).Result.argmax(-1);
 var prediction = argmax.ToArray<long>();

 var editor = VBufferEditor.Create(ref dst, prediction.Length - 1);
 for (int i = 1; i < prediction.Length; i++)
 {
 editor.Values[i - 1] = (uint)prediction[i];
 }

 dst = editor.Commit();
 CondenseOutput(ref dst, sentence1.ToString(), tokenizer, outputCacher);
 };

 return classification;
Expand Down

6 changes: 3 additions & 3 deletions
src/Microsoft.ML.TorchSharp/TorchSharpBaseTrainer.cs

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -238,9 +238,9 @@ private bool ValidateStep(DataViewRowCursor cursor,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -312,9 +312,9 @@ private bool TrainStep(IHost host,
 cursorValid = cursor.MoveNext();
 if (cursorValid)
 {
 inputTensors.Add(PrepareRowTensor());
 TLabelCol target = default;
 labelGetter(ref target);
 inputTensors.Add(PrepareRowTensor(ref target));
 targets.Add(AddToTargets(target));
 }
 else
Expand DownExpand Up@@ -343,7 +343,7 @@ private bool TrainStep(IHost host,

 private protected abstract void RunModelAndBackPropagate(ref List<Tensor> inputTensorm, ref Tensor targetsTensor);

 private protected abstract torch.Tensor PrepareRowTensor();
 private protected abstract torch.Tensor PrepareRowTensor(ref TLabelCol target);
 private protected abstract torch.Tensor PrepareBatchTensor(ref List<Tensor> inputTensors, Device device);

 [MethodImpl(MethodImplOptions.AggressiveInlining)]
Expand Down
Loading