Tokenizer's APIs Update (#7128)

* Tokenizer's APIs Update

* Address the feedback

* Address the feedback and use the new TestTokenizers package

eng/Versions.props

@@ -41,7 +41,7 @@
     <MicrosoftDotNetInteractiveVersion>1.0.0-beta.23509.3</MicrosoftDotNetInteractiveVersion>
     <MicrosoftMLOnnxRuntimeVersion>1.16.3</MicrosoftMLOnnxRuntimeVersion>
     <MlNetMklDepsVersion>0.0.0.12</MlNetMklDepsVersion>
-    <!--  
+    <!--
 @("inteltbb.devel", "win", "2021.7.1.15305")
     -->
     <OneDalPkgVersion Condition="'$(OS)' == 'Windows_NT'">2023.0.0.23189</OneDalPkgVersion>
@@ -87,6 +87,7 @@
     <MicrosoftMLTensorFlowTestModelsVersion>0.0.13-test</MicrosoftMLTensorFlowTestModelsVersion>
     <MicrosoftMLTestDatabasesVersion>0.0.6-test</MicrosoftMLTestDatabasesVersion>
     <MicrosoftMLTestModelsVersion>0.0.7-test</MicrosoftMLTestModelsVersion>
+    <MicrosoftMLTestTokenizersVersion>2.0.0-beta.24218.2</MicrosoftMLTestTokenizersVersion>
     <SystemDataSqlClientVersion>4.8.6</SystemDataSqlClientVersion>
     <SystemDataSQLiteCoreVersion>1.0.118</SystemDataSQLiteCoreVersion>
     <XunitCombinatorialVersion>1.2.7</XunitCombinatorialVersion>

src/Microsoft.ML.Tokenizers/EncodingResult.cs

@@ -1,152 +0,0 @@
-// Licensed to the .NET Foundation under one or more agreements.
-// The .NET Foundation licenses this file to you under the MIT license.
-// See the LICENSE file in the project root for more information.
-
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Microsoft.ML.Tokenizers
-{
-    /// <summary>
-    /// The Encoding represents the output of a Tokenizer.
-    /// </summary>
-    public sealed class EncodingResult
-    {
-        /// <summary>
-        /// Create a new object of the EncodingResult object.
-        /// </summary>
-        /// <param name="originalString">The list of tokens to merge.</param>
-        /// <param name="normalizedString">The list of tokens to merge.</param>
-        /// <param name="splits">The list of tokens to merge.</param>
-        /// <param name="offsetsMappedToOriginalString">Indicate whether the offsets is mapped to the original string or the normalized string.</param>
-        public EncodingResult(string originalString, string normalizedString, IEnumerable<Split> splits, bool offsetsMappedToOriginalString)
-        {
-            OriginalString = originalString;
-            NormalizedString = normalizedString;
-            Splits = splits;
-            OffsetsMappedToOriginalString = offsetsMappedToOriginalString;
-        }
-
-        /// <summary>
-        /// Gets the original tokenized string.
-        /// </summary>
-        public string? OriginalString { get; }
-
-        /// <summary>
-        /// Gets the normalized form of the original string.
-        /// </summary>
-        public string? NormalizedString { get; }
-
-        /// <summary>
-        /// Gets the normalized form of the original string.
-        /// </summary>
-        public bool OffsetsMappedToOriginalString { get; }
-
-        internal IEnumerable<Split> Splits { get; }
-        private List<Token>? _tokens;
-        private List<string>? _tokensWords;
-        private List<int>? _ids;
-        private List<(int Index, int Length)>? _offsets;
-
-        internal void AddTokens(IReadOnlyList<Token> addedTokens)
-        {
-            if (_tokens is null)
-            {
-                _tokens = new(addedTokens);
-                return;
-            }
-
-            foreach (var token in addedTokens)
-            {
-                _tokens.Add(token);
-            }
-        }
-
-        /// <summary>
-        /// Gets list of the tokens Ids.
-        /// The Ids are the main input to a Language Model. They are the token indices, the numerical representations that a LM understands.
-        /// </summary>
-        public IReadOnlyList<int> Ids
-        {
-            get
-            {
-                if (_ids is not null)
-                {
-                    return _ids;
-                }
-
-                if (_tokens is null)
-                {
-                    return Array.Empty<int>();
-                }
-
-                _ids = new List<int>(_tokens.Count);
-
-                foreach (var token in _tokens)
-                {
-                    _ids.Add(token.Id);
-                }
-
-                return _ids;
-            }
-        }
-
-        /// <summary>
-        /// Gets the generated tokens. They are the string representation of the Ids.
-        /// </summary>
-        public IReadOnlyList<string> Tokens
-        {
-            get
-            {
-                if (_tokensWords is not null)
-                {
-                    return _tokensWords;
-                }
-
-                if (_tokens is null)
-                {
-                    return Array.Empty<string>();
-                }
-
-                _tokensWords = new List<string>(_tokens.Count);
-
-                foreach (var token in _tokens)
-                {
-                    _tokensWords.Add(token.Value);
-                }
-
-                return _tokensWords;
-            }
-        }
-
-        /// <summary>
-        /// Gets The list of offsets. These offsets let's you slice the input string, and thus retrieve
-        /// the original part that led to producing the corresponding token.
-        /// </summary>
-        public IReadOnlyList<(int Index, int Length)> Offsets
-        {
-            get
-            {
-                if (_offsets is not null)
-                {
-                    return _offsets;
-                }
-
-                if (_tokens is null)
-                {
-                    return Array.Empty<(int, int)>();
-                }
-
-                _offsets = new List<(int Index, int Length)>(_tokens.Count);
-
-                foreach (var token in _tokens)
-                {
-                    _offsets.Add(token.Offset);
-                }
-
-                return _offsets;
-            }
-        }
-    }
-}

src/Microsoft.ML.Tokenizers/Model/BPE.cs

@@ -17,13 +17,15 @@ namespace Microsoft.ML.Tokenizers
     /// <summary>
     /// Represent the Byte Pair Encoding model.
     /// </summary>
-    public sealed class Bpe : Model
+    public sealed class Bpe : Tokenizer
     {
         /// A [Byte Pair Encoding](https://www.aclweb.org/anthology/P16-1162/) model.
 
         private const int MaxWordLengthToCache = 15;
         private string? _unknownToken;
         private int? _unknownTokenId;
+        private readonly PreTokenizer? _preTokenizer;
+        private readonly Normalizer? _normalizer;
 
         /// <summary>
         /// Gets or Sets unknown token. The unknown token to be used when we encounter an unknown char
@@ -74,13 +76,15 @@ namespace Microsoft.ML.Tokenizers
         /// </summary>
         /// <param name="vocabFile">The JSON file path containing the dictionary of string keys and their ids.</param>
         /// <param name="mergesFile">The file path containing the tokens's pairs list.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
         /// <param name="unknownToken"> The unknown token to be used by the model.</param>
         /// <param name="continuingSubwordPrefix">The prefix to attach to sub-word units that don’t represent a beginning of word.</param>
         /// <param name="endOfWordSuffix">The suffix to attach to sub-word units that represent an end of word.</param>
         /// <param name="fuseUnknownTokens">Indicate whether allowing multiple unknown tokens get fused.</param>
-        public Bpe(string vocabFile, string? mergesFile, string? unknownToken = null, string? continuingSubwordPrefix = null, string? endOfWordSuffix = null, bool fuseUnknownTokens = false) :
+        public Bpe(string vocabFile, string? mergesFile, PreTokenizer? preTokenizer = null, Normalizer? normalizer = null, string? unknownToken = null, string? continuingSubwordPrefix = null, string? endOfWordSuffix = null, bool fuseUnknownTokens = false) :
             this(vocabFile is null ? throw new ArgumentNullException(nameof(vocabFile)) : File.Open(vocabFile, FileMode.Open, FileAccess.Read),
-                mergesFile is null ? null : File.Open(mergesFile, FileMode.Open, FileAccess.Read), unknownToken, continuingSubwordPrefix, endOfWordSuffix, fuseUnknownTokens, disposeStreams: true)
+                mergesFile is null ? null : File.Open(mergesFile, FileMode.Open, FileAccess.Read), preTokenizer, normalizer, unknownToken, continuingSubwordPrefix, endOfWordSuffix, fuseUnknownTokens, disposeStreams: true)
         {
         }
 
@@ -89,16 +93,18 @@ namespace Microsoft.ML.Tokenizers
         /// </summary>
         /// <param name="vocabStream">The JSON stream containing the dictionary of string keys and their ids.</param>
         /// <param name="mergesStream">The stream containing the tokens's pairs list.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
         /// <param name="unknownToken"> The unknown token to be used by the model.</param>
         /// <param name="continuingSubwordPrefix">The prefix to attach to sub-word units that don’t represent a beginning of word.</param>
         /// <param name="endOfWordSuffix">The suffix to attach to sub-word units that represent an end of word.</param>
         /// <param name="fuseUnknownTokens">Indicate whether allowing multiple unknown tokens get fused.</param>
-        public Bpe(Stream vocabStream, Stream? mergesStream, string? unknownToken = null, string? continuingSubwordPrefix = null, string? endOfWordSuffix = null, bool fuseUnknownTokens = false) :
-                this(vocabStream, mergesStream, unknownToken, continuingSubwordPrefix, endOfWordSuffix, fuseUnknownTokens, disposeStreams: false)
+        public Bpe(Stream vocabStream, Stream? mergesStream, PreTokenizer? preTokenizer = null, Normalizer? normalizer = null, string? unknownToken = null, string? continuingSubwordPrefix = null, string? endOfWordSuffix = null, bool fuseUnknownTokens = false) :
+                this(vocabStream, mergesStream, preTokenizer, normalizer, unknownToken, continuingSubwordPrefix, endOfWordSuffix, fuseUnknownTokens, disposeStreams: false)
         {
         }
 
-        private Bpe(Stream vocabStream, Stream? mergesStream, string? unknownToken, string? continuingSubwordPrefix, string? endOfWordSuffix, bool fuseUnknownTokens, bool disposeStreams)
+        private Bpe(Stream vocabStream, Stream? mergesStream, PreTokenizer? preTokenizer, Normalizer? normalizer, string? unknownToken, string? continuingSubwordPrefix, string? endOfWordSuffix, bool fuseUnknownTokens, bool disposeStreams)
         {
             try
             {
@@ -110,6 +116,8 @@ namespace Microsoft.ML.Tokenizers
                 FuseUnknownTokens = fuseUnknownTokens;
                 ContinuingSubwordPrefix = continuingSubwordPrefix;
                 EndOfWordSuffix = endOfWordSuffix;
+                _preTokenizer = preTokenizer ?? WhiteSpace.Instance; // Default to WhiteSpace pre-tokenizer
+                _normalizer = normalizer;
 
                 (Dictionary<StringSpanOrdinalKey, int>? vocab1, Vec<(string, string)> merges) = ReadModelData(vocabStream, mergesStream);
                 _vocab = vocab1 ?? new Dictionary<StringSpanOrdinalKey, int>();
@@ -166,47 +174,320 @@ namespace Microsoft.ML.Tokenizers
         }
 
         /// <summary>
-        /// Encode a text string to a list of tokens.
+        /// Gets the PreTokenizer used by the Tokenizer.
+        /// </summary>
+        public override PreTokenizer? PreTokenizer => _preTokenizer;
+
+        /// <summary>
+        /// Gets the Normalizer in use by the Tokenizer.
+        /// </summary>
+        public override Normalizer? Normalizer => _normalizer;
+
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <returns>The list of tokens generated from the text tokenization.</returns>
-        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text)
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(string text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true) => Encode(text, Span<char>.Empty, out normalizedString, considerPreTokenization, considerNormalization);
+
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true) => Encode(null, text, out normalizedString, considerPreTokenization, considerNormalization);
+
+        private IReadOnlyList<Token> Encode(string? text, ReadOnlySpan<char> textSpan, out string? normalizedString, bool considerPreTokenization, bool considerNormalization)
         {
-            if (text.Length == 0)
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
             {
-                return EmptyTokensList;
+                normalizedString = null;
+                return [];
             }
 
-            return EncodeWithCache(text);
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            List<Token> tokens = new();
+            PriorityQueue<Merge>? priorityQueue = null;
+
+            if (splits is not null)
+            {
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    EncodeWithCache(textSpanToEncode.Slice(split.Offset, split.Length), tokens, split.Offset, ref priorityQueue);
+                }
+            }
+            else
+            {
+                EncodeWithCache(textSpanToEncode, tokens, 0, ref priorityQueue);
+            }
+
+            return tokens;
         }
 
         /// <summary>
-        /// Encode a split text string to a list of Ids and add them to the accumulatedIds list.
+        /// Encodes input text to token Ids.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="accumulatedIds">The list of accumulated encoded Ids.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
         /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int EncodeToIds(ReadOnlySpan<char> text, IList<int> accumulatedIds, out int textLength, int maxTokens = int.MaxValue) => EncodeToIdsWithCache(text, accumulatedIds, maxTokens, out textLength);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, considerPreTokenization, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        private IReadOnlyList<int> EncodeToIds(string? text, ReadOnlySpan<char> textSpan, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                textLength = 0;
+                normalizedString = null;
+                return [];
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            List<int> ids = new();
+            PriorityQueue<Merge>? priorityQueue = null;
+
+            if (splits is not null)
+            {
+                textLength = 0;
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    EncodeToIdsWithCache(textSpanToEncode.Slice(split.Offset, split.Length), ids, maxTokenCount - ids.Count, out int length, ref priorityQueue);
+                    textLength = split.Offset + length;
+
+                    if (length < split.Length || ids.Count >= maxTokenCount)
+                    {
+                        break;
+                    }
+                }
+            }
+            else
+            {
+                EncodeToIdsWithCache(textSpanToEncode, ids, maxTokenCount, out textLength, ref priorityQueue);
+            }
+
+            return ids;
+        }
 
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int CountTokens(ReadOnlySpan<char> text, out int textLength, int maxTokens = int.MaxValue) => EncodeToIdsWithCache(text, null, maxTokens, out textLength);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out _, out _);
 
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="textIndex">Starting from this index to the end of the text will encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int CountTokensFromEnd(ReadOnlySpan<char> text, out int textIndex, int maxTokens = int.MaxValue) => EncodeToIdsFromEndWithCache(text, null, maxTokens, out textIndex);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(null, text, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(null, text, considerPreTokenization, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        private int CountTokens(string? text, ReadOnlySpan<char> textSpan, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            textLength = 0;
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                return 0;
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            PriorityQueue<Merge>? priorityQueue = null;
+            int count = 0;
+            if (splits is not null)
+            {
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    count += EncodeToIdsWithCache(textSpanToEncode.Slice(split.Offset, split.Length), null, maxTokenCount - count, out int length, ref priorityQueue);
+                    textLength = split.Offset + length;
+
+                    if (length < split.Length || count >= maxTokenCount)
+                    {
+                        break;
+                    }
+                }
+            }
+            else
+            {
+                count = EncodeToIdsWithCache(textSpanToEncode, null, maxTokenCount, out textLength, ref priorityQueue);
+            }
+
+            return count;
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if normalization is enabled;
+        /// conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(text, Span<char>.Empty, maxTokenCount, considerPreTokenization, considerNormalization, out normalizedString, out tokenCount);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the <paramref name="normalizedString"/>; conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(null, text, maxTokenCount, considerPreTokenization, considerNormalization, out normalizedString, out tokenCount);
+
+        private int LastIndexOf(string? text, ReadOnlySpan<char> textSpan, int maxTokenCount, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int tokenCount)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The max token count must be greater than 0.");
+            }
+
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                tokenCount = 0;
+                return 0;
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            PriorityQueue<Merge>? priorityQueue = null;
+
+            if (splits is not null)
+            {
+                tokenCount = 0;
+                foreach ((int Offset, int Length) split in splits.Reverse())
+                {
+                    tokenCount += EncodeToIdsFromEndWithCache(textSpanToEncode.Slice(split.Offset, split.Length), null, maxTokenCount - tokenCount, out int textIndex, ref priorityQueue);
+                    if (textIndex > 0 || tokenCount >= maxTokenCount)
+                    {
+                        return split.Offset + textIndex;
+                    }
+                }
+            }
+            else
+            {
+                tokenCount = EncodeToIdsFromEndWithCache(textSpanToEncode, null, maxTokenCount, out int textLength, ref priorityQueue);
+                return textLength;
+            }
+
+            return 0;
+        }
 
         /// <summary>
         /// Map the token to encoded Id.
@@ -383,7 +664,7 @@ namespace Microsoft.ML.Tokenizers
             return s;
         }
 
-        internal Word MergeWord(ReadOnlySpan<char> w)
+        internal Word MergeWord(ReadOnlySpan<char> w, ref PriorityQueue<Merge>? priorityQueue)
         {
             Word word = Word.WithCapacity(w.Length);
             (int Id, int Len)? unk = null;
@@ -494,23 +775,24 @@ namespace Microsoft.ML.Tokenizers
                 word.Add(unk.Value.Id, unk.Value.Len);
             }
 
-            word.MergeAll(Merges, Dropout);
+            word.MergeAll(Merges, Dropout, ref priorityQueue);
             return word;
         }
 
-        internal List<Token> WordToTokens(ref Word word) => word.ToTokens(VocabReverse);
+        internal void WordToTokens(ref Word word, List<Token> tokens, int offset) => word.ToTokens(VocabReverse, tokens, offset);
 
-        internal List<Token> EncodeWithCache(ReadOnlySpan<char> text)
+        internal void EncodeWithCache(ReadOnlySpan<char> text, List<Token> tokens, int offset, ref PriorityQueue<Merge>? priorityQueue)
         {
             Word word;
             if (Cache is not null)
             {
                 if (Cache.TryGetValue(text, out word))
                 {
-                    return WordToTokens(ref word);
+                    WordToTokens(ref word, tokens, offset);
+                    return;
                 }
 
-                word = MergeWord(text);
+                word = MergeWord(text, ref priorityQueue);
 
                 if (text.Length <= MaxWordLengthToCache)
                 {
@@ -519,15 +801,15 @@ namespace Microsoft.ML.Tokenizers
             }
             else
             {
-                word = MergeWord(text);
+                word = MergeWord(text, ref priorityQueue);
             }
 
-            return WordToTokens(ref word);
+            WordToTokens(ref word, tokens, offset);
         }
 
         internal int WordToIds(ref Word word, IList<int>? accumulatedIds, out int textLength, int fullTextLength, int maxTokens)
         {
-            if (word.SymbolsCount < maxTokens)
+            if (word.SymbolsCount <= maxTokens)
             {
                 textLength = fullTextLength;
                 if (accumulatedIds is not null)
@@ -548,7 +830,7 @@ namespace Microsoft.ML.Tokenizers
 
         internal int WordToIdsFromEnd(ref Word word, IList<int>? accumulatedIds, out int textIndex, int fullTextLength, int maxTokens)
         {
-            if (word.SymbolsCount < maxTokens)
+            if (word.SymbolsCount <= maxTokens)
             {
                 textIndex = 0;
                 if (accumulatedIds is not null)
@@ -567,7 +849,7 @@ namespace Microsoft.ML.Tokenizers
             return word.CountIdsUpToMaxFromEnd(maxTokens, fullTextLength, out textIndex);
         }
 
-        internal int EncodeToIdsWithCache(ReadOnlySpan<char> text, IList<int>? accumulatedIds, int maxTokens, out int textLength)
+        private int EncodeToIdsWithCache(ReadOnlySpan<char> text, List<int>? accumulatedIds, int maxTokens, out int textLength, ref PriorityQueue<Merge>? priorityQueue)
         {
             Word word;
 
@@ -578,7 +860,7 @@ namespace Microsoft.ML.Tokenizers
                     return WordToIds(ref hit, accumulatedIds, out textLength, text.Length, maxTokens);
                 }
 
-                word = MergeWord(text);
+                word = MergeWord(text, ref priorityQueue);
 
                 if (text.Length <= MaxWordLengthToCache)
                 {
@@ -587,13 +869,13 @@ namespace Microsoft.ML.Tokenizers
             }
             else
             {
-                word = MergeWord(text);
+                word = MergeWord(text, ref priorityQueue);
             }
 
             return WordToIds(ref word, accumulatedIds, out textLength, text.Length, maxTokens);
         }
 
-        internal int EncodeToIdsFromEndWithCache(ReadOnlySpan<char> text, IList<int>? accumulatedIds, int maxTokens, out int textIndex)
+        internal int EncodeToIdsFromEndWithCache(ReadOnlySpan<char> text, IList<int>? accumulatedIds, int maxTokens, out int textIndex, ref PriorityQueue<Merge>? priorityQueue)
         {
             Word word;
 
@@ -604,7 +886,7 @@ namespace Microsoft.ML.Tokenizers
                     return WordToIdsFromEnd(ref hit, accumulatedIds, out textIndex, text.Length, maxTokens);
                 }
 
-                word = MergeWord(text);
+                word = MergeWord(text, ref priorityQueue);
 
                 if (text.Length <= MaxWordLengthToCache)
                 {
@@ -613,12 +895,10 @@ namespace Microsoft.ML.Tokenizers
             }
             else
             {
-                word = MergeWord(text);
+                word = MergeWord(text, ref priorityQueue);
             }
 
             return WordToIdsFromEnd(ref word, accumulatedIds, out textIndex, text.Length, maxTokens);
         }
-
-        internal static readonly List<Token> EmptyTokensList = new();
     }
 }

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

@@ -8,6 +8,7 @@ using System.Collections.Generic;
 using System.Diagnostics;
 using System.IO;
 using System.Linq;
+using System.Text;
 using System.Text.Json;
 
 namespace Microsoft.ML.Tokenizers
@@ -15,7 +16,7 @@ namespace Microsoft.ML.Tokenizers
     /// <summary>
     /// Represent the Byte Pair Encoding model.
     /// </summary>
-    public sealed class EnglishRoberta : Model
+    public sealed class EnglishRoberta : Tokenizer
     {
         private readonly HighestOccurrenceMapping _vocabIdToHighestOccurrence;
         private readonly Dictionary<StringSpanOrdinalKey, int> _vocab;
@@ -26,6 +27,8 @@ namespace Microsoft.ML.Tokenizers
         private readonly IReadOnlyDictionary<char, char> _unicodeToByte;
         private readonly string[] _charToString;
         private readonly StringSpanOrdinalKeyCache<List<Token>> _cache;
+        private readonly PreTokenizer? _preTokenizer;
+        private readonly Normalizer? _normalizer;
 
         /// <summary>
         /// Indicate if want to filter the unsupported characters during the decoding.
@@ -38,29 +41,51 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="vocabularyPath">The JSON file path containing the dictionary of string keys and their ids.</param>
         /// <param name="mergePath">The file path containing the tokens's pairs list.</param>
         /// <param name="highestOccurrenceMappingPath">Remap the original GPT-2 model Ids to high occurrence ranks and values.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
         /// <param name="filterUnsupportedChars">Indicate if want to filter the unsupported characters during the decoding.</param>
-        public EnglishRoberta(string vocabularyPath, string mergePath, string highestOccurrenceMappingPath, bool filterUnsupportedChars = true)
+        public EnglishRoberta(string vocabularyPath, string mergePath, string highestOccurrenceMappingPath, PreTokenizer? preTokenizer = null, Normalizer? normalizer = null, bool filterUnsupportedChars = true) :
+            this(vocabularyPath is null ? throw new ArgumentNullException(nameof(vocabularyPath)) : File.OpenRead(vocabularyPath),
+                mergePath is null ? throw new ArgumentNullException(nameof(mergePath)) : File.OpenRead(mergePath),
+                highestOccurrenceMappingPath is null ? throw new ArgumentNullException(nameof(highestOccurrenceMappingPath)) : File.OpenRead(highestOccurrenceMappingPath),
+                preTokenizer, normalizer, filterUnsupportedChars, true)
         {
-            if (vocabularyPath is null)
+        }
+
+        /// <summary>
+        /// Construct tokenizer's model object to use with the English Robert model.
+        /// </summary>
+        /// <param name="vocabularyStream">The stream of a JSON file containing the dictionary of string keys and their ids.</param>
+        /// <param name="mergeStream">The stream of a file containing the tokens's pairs list.</param>
+        /// <param name="highestOccurrenceMappingStream">Remap the original GPT-2 model Ids to high occurrence ranks and values.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
+        /// <param name="filterUnsupportedChars">Indicate if want to filter the unsupported characters during the decoding.</param>
+        public EnglishRoberta(Stream vocabularyStream, Stream mergeStream, Stream highestOccurrenceMappingStream, PreTokenizer? preTokenizer = null, Normalizer? normalizer = null, bool filterUnsupportedChars = true) :
+            this(vocabularyStream, mergeStream, highestOccurrenceMappingStream, preTokenizer, normalizer, filterUnsupportedChars, false)
+        {
+        }
+
+        public EnglishRoberta(Stream vocabularyStream, Stream mergeStream, Stream highestOccurrenceMappingStream, PreTokenizer? preTokenizer, Normalizer? normalizer, bool filterUnsupportedChars, bool disposeStream)
+        {
+            if (vocabularyStream is null)
             {
-                throw new ArgumentNullException(nameof(vocabularyPath));
+                throw new ArgumentNullException(nameof(vocabularyStream));
             }
 
-            if (mergePath is null)
+            if (mergeStream is null)
             {
-                throw new ArgumentNullException(nameof(mergePath));
+                throw new ArgumentNullException(nameof(mergeStream));
             }
 
-            if (highestOccurrenceMappingPath is null)
+            if (highestOccurrenceMappingStream is null)
             {
-                throw new ArgumentNullException(nameof(highestOccurrenceMappingPath));
+                throw new ArgumentNullException(nameof(highestOccurrenceMappingStream));
             }
 
             FilterUnsupportedChars = filterUnsupportedChars;
-
-            using Stream vocabularyStream = File.OpenRead(vocabularyPath);
-            using Stream mergeStream = File.OpenRead(mergePath);
-            using Stream highestOccurrenceMappingStream = File.OpenRead(highestOccurrenceMappingPath);
+            _preTokenizer = preTokenizer;
+            _normalizer = normalizer;
 
             // vocabularyPath like "https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/encoder.json"
             // merge file like "https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/vocab.bpe"
@@ -79,48 +104,24 @@ namespace Microsoft.ML.Tokenizers
 
             _unicodeToByte = _byteToUnicode.Reverse();
             _cache = new StringSpanOrdinalKeyCache<List<Token>>();
+
+            if (disposeStream)
+            {
+                vocabularyStream.Dispose();
+                mergeStream.Dispose();
+                highestOccurrenceMappingStream.Dispose();
+            }
         }
 
         /// <summary>
-        /// Construct tokenizer's model object to use with the English Robert model.
+        /// Gets the PreTokenizer used by the Tokenizer.
         /// </summary>
-        /// <param name="vocabularyStream">The stream of a JSON file containing the dictionary of string keys and their ids.</param>
-        /// <param name="mergeStream">The stream of a file containing the tokens's pairs list.</param>
-        /// <param name="highestOccurrenceMappingStream">Remap the original GPT-2 model Ids to high occurrence ranks and values.</param>
-        /// <param name="filterUnsupportedChars">Indicate if want to filter the unsupported characters during the decoding.</param>
-        public EnglishRoberta(Stream vocabularyStream, Stream mergeStream, Stream highestOccurrenceMappingStream, bool filterUnsupportedChars = true)
-        {
-            if (vocabularyStream is null)
-            {
-                throw new ArgumentNullException(nameof(vocabularyStream));
-            }
+        public override PreTokenizer? PreTokenizer => _preTokenizer;
 
-            if (mergeStream is null)
-            {
-                throw new ArgumentNullException(nameof(mergeStream));
-            }
-
-            if (highestOccurrenceMappingStream is null)
-            {
-                throw new ArgumentNullException(nameof(highestOccurrenceMappingStream));
-            }
-
-            FilterUnsupportedChars = filterUnsupportedChars;
-
-            _vocabIdToHighestOccurrence = GetHighestOccurrenceMapping(highestOccurrenceMappingStream);
-            _vocab = GetVocabulary(vocabularyStream);
-            _vocabReverse = _vocab.ReverseSorted();
-            _mergeRanks = GetMergeRanks(mergeStream);
-            int maxCharValue = GetByteToUnicode(out _byteToUnicode);
-            _charToString = new string[maxCharValue];
-            for (char c = (char)0; c < (char)maxCharValue; c++)
-            {
-                _charToString[c] = c.ToString();
-            }
-
-            _unicodeToByte = _byteToUnicode.Reverse();
-            _cache = new StringSpanOrdinalKeyCache<List<Token>>();
-        }
+        /// <summary>
+        /// Gets the Normalizer in use by the Tokenizer.
+        /// </summary>
+        public override Normalizer? Normalizer => _normalizer;
 
         /// <summary>
         /// Gets the dictionary mapping tokens to Ids.
@@ -167,16 +168,64 @@ namespace Microsoft.ML.Tokenizers
             return null;
         }
 
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(string text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true) => Encode(text, Span<char>.Empty, out normalizedString, considerPreTokenization, considerNormalization);
+
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true) => Encode(null, text, out normalizedString, considerPreTokenization, considerNormalization);
+
+        private IReadOnlyList<Token> Encode(string? text, ReadOnlySpan<char> textSpan, out string? normalizedString, bool considerPreTokenization, bool considerNormalization)
+        {
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                return [];
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            if (splits is not null)
+            {
+                List<Token> tokens = new();
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    foreach (Token t in EncodeInternal(textSpanToEncode.Slice(split.Offset, split.Length)))
+                    {
+                        tokens.Add(new Token(t.Id, t.Value, (split.Offset + t.Offset.Index, t.Offset.Length)));
+                    }
+                }
+                return tokens;
+            }
+            else
+            {
+                return EncodeInternal(textSpanToEncode);
+            }
+        }
+
         /// <summary>
         /// Encode a text string to a list of tokens.
         /// </summary>
         /// <param name="text">The text to encode.</param>
         /// <returns>The list of tokens generated from the text tokenization.</returns>
-        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text)
+        private IReadOnlyList<Token> EncodeInternal(ReadOnlySpan<char> text)
         {
             if (text.IsEmpty)
             {
-                return Bpe.EmptyTokensList;
+                return [];
             }
 
             char[] token = ArrayPool<char>.Shared.Rent(text.Length);
@@ -197,7 +246,7 @@ namespace Microsoft.ML.Tokenizers
             {
                 ArrayPool<char>.Shared.Return(token);
                 ArrayPool<int>.Shared.Return(indexMapping);
-                return Array.Empty<Token>();
+                return [];
             }
 
             if (_cache.TryGetValue(text, out List<Token>? hit))
@@ -215,32 +264,257 @@ namespace Microsoft.ML.Tokenizers
         }
 
         /// <summary>
-        /// Encode a split text string to a list of Ids and add them to the accumulatedIds list.
+        /// Encodes input text to token Ids.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="accumulatedIds">The list of accumulated encoded Ids.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
         /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int EncodeToIds(ReadOnlySpan<char> text, IList<int> accumulatedIds, out int textLength, int maxTokens = int.MaxValue) => EncodeToIdsInternal(text, accumulatedIds, out textLength, maxTokens);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, considerPreTokenization, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        private IReadOnlyList<int> EncodeToIds(string? text, ReadOnlySpan<char> textSpan, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                textLength = 0;
+                normalizedString = null;
+                return [];
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            List<int> ids = new();
+            if (splits is not null)
+            {
+                textLength = 0;
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    EncodeToIdsInternal(textSpanToEncode.Slice(split.Offset, split.Length), ids, out int length, maxTokenCount - ids.Count);
+                    textLength = split.Offset + length;
+
+                    if (length < split.Length || ids.Count >= maxTokenCount)
+                    {
+                        break;
+                    }
+                }
+            }
+            else
+            {
+                EncodeToIdsInternal(textSpanToEncode, ids, out textLength, maxTokenCount);
+            }
+
+            return ids;
+        }
 
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int CountTokens(ReadOnlySpan<char> text, out int textLength, int maxTokens = int.MaxValue) => EncodeToIdsInternal(text, null, out textLength, maxTokens);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out _, out _);
 
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="textIndex">Starting from this index to the end of the text will encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int CountTokensFromEnd(ReadOnlySpan<char> text, out int textIndex, int maxTokens = int.MaxValue) => EncodeToIdsFromEndInternal(text, null, out textIndex, maxTokens);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(null, text, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(null, text, considerPreTokenization, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        private int CountTokens(string? text, ReadOnlySpan<char> textSpan, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            textLength = 0;
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                return 0;
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            int count = 0;
+            if (splits is not null)
+            {
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    count += EncodeToIdsInternal(textSpanToEncode.Slice(split.Offset, split.Length), null, out int length, maxTokenCount - count);
+                    textLength = split.Offset + length;
+
+                    if (length < split.Length || count >= maxTokenCount)
+                    {
+                        break;
+                    }
+                }
+            }
+            else
+            {
+                count += EncodeToIdsInternal(textSpanToEncode, null, out textLength, maxTokenCount);
+            }
+
+            return count;
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if normalization is enabled;
+        /// conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(text, Span<char>.Empty, maxTokenCount, considerPreTokenization, considerNormalization, out normalizedString, out tokenCount);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the <paramref name="normalizedString"/>; conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(null, text, maxTokenCount, considerPreTokenization, considerNormalization, out normalizedString, out tokenCount);
+
+        private int LastIndexOf(string? text, ReadOnlySpan<char> textSpan, int maxTokenCount, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int tokenCount)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The max token count must be greater than 0.");
+            }
+
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                tokenCount = 0;
+                return 0;
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            if (splits is not null)
+            {
+                tokenCount = 0;
+                foreach ((int Offset, int Length) split in splits.Reverse())
+                {
+                    tokenCount += EncodeToIdsFromEndInternal(textSpanToEncode.Slice(split.Offset, split.Length), null, out int textIndex, maxTokenCount - tokenCount);
+                    if (textIndex > 0 || tokenCount >= maxTokenCount)
+                    {
+                        return split.Offset + textIndex;
+                    }
+                }
+            }
+            else
+            {
+                tokenCount = EncodeToIdsFromEndInternal(textSpanToEncode, null, out int textLength, maxTokenCount);
+                return textLength;
+            }
+
+            return 0;
+        }
 
         private int EncodeToIdsResult(List<Token> tokens, IList<int>? accumulatedIds, int maxTokens, int fullTextLength, out int textLength)
         {
@@ -347,7 +621,7 @@ namespace Microsoft.ML.Tokenizers
             {
                 ArrayPool<char>.Shared.Return(token);
                 ArrayPool<int>.Shared.Return(indexMapping);
-                textLength = 0;
+                textLength = text.Length;
                 return 0;
             }
 
@@ -390,7 +664,7 @@ namespace Microsoft.ML.Tokenizers
             {
                 ArrayPool<char>.Shared.Return(token);
                 ArrayPool<int>.Shared.Return(indexMapping);
-                textIndex = text.Length;
+                textIndex = 0;
                 return 0;
             }
 
@@ -410,7 +684,32 @@ namespace Microsoft.ML.Tokenizers
         public override int? MapTokenToId(ReadOnlySpan<char> token) => _vocab.TryGetValue(token, out int value) ? value : null;
 
         /// <summary>
-        /// Convert a list of tokens Ids to highest occurrence rankings.
+        /// Decode the given ids, back to a String.
+        /// </summary>
+        /// <param name="ids">The list of ids that we want to decode.</param>
+        /// <returns>The decoded string.</returns>
+        public override string? Decode(IEnumerable<int> ids)
+        {
+            if (ids is null)
+            {
+                throw new ArgumentNullException(nameof(ids));
+            }
+
+            ValueStringBuilder sb = new ValueStringBuilder();
+
+            foreach (int id in ids)
+            {
+                if (MapIdToToken(id) is string s)
+                {
+                    sb.Append(s);
+                }
+            }
+
+            return sb.ToString();
+        }
+
+        /// <summary>
+        /// Convert a list of token Ids to highest occurrence rankings.
         /// </summary>
         /// <param name="ids">The Ids list to map to the high occurrence rank.</param>
         /// <returns>The list of ranks mapped from the list of Ids.</returns>
@@ -432,7 +731,7 @@ namespace Microsoft.ML.Tokenizers
         }
 
         /// <summary>
-        /// Convert a list of tokens Ids to highest occurrence values.
+        /// Convert a list of token Ids to highest occurrence values.
         /// </summary>
         /// <param name="ids">The Ids list to map to the high occurrence values.</param>
         /// <returns>The list of occurrence values mapped from the list of Ids.</returns>
@@ -454,7 +753,7 @@ namespace Microsoft.ML.Tokenizers
         }
 
         /// <summary>
-        /// Convert a list of highest occurrence rankings to tokens Ids list .
+        /// Convert a list of highest occurrence rankings to token Ids list .
         /// </summary>
         /// <param name="ranks">The high occurrence ranks list to map to the Ids list.</param>
         /// <returns>The list of Ids mapped from the list of ranks.</returns>
@@ -638,7 +937,7 @@ namespace Microsoft.ML.Tokenizers
         {
             if (token.Length == 0)
             {
-                return Bpe.EmptyTokensList;
+                return [];
             }
 
             if (token.Length == 1)

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

@@ -1,180 +0,0 @@
-// Licensed to the .NET Foundation under one or more agreements.
-// The .NET Foundation licenses this file to you under the MIT license.
-// See the LICENSE file in the project root for more information.
-
-using System;
-using System.Collections.Generic;
-using System.Text;
-
-namespace Microsoft.ML.Tokenizers
-{
-    /// <summary>
-    /// Represents a model used during Tokenization (like BPE or Word Piece or Unigram).
-    /// </summary>
-    public abstract class Model
-    {
-        /// <summary>
-        /// Encode a text to a list of tokens.
-        /// </summary>
-        /// <param name="text">The text to encode.</param>
-        /// <returns>The list of tokens generated from the text tokenization.</returns>
-        public abstract IReadOnlyList<Token> Encode(ReadOnlySpan<char> text);
-
-        /// <summary>
-        /// Encode a text to a list of Ids and add them to the accumulatedIds list.
-        /// </summary>
-        /// <param name="text">The text to encode. </param>
-        /// <param name="accumulatedIds">The list of accumulated encoded Ids.</param>
-        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        /// <remarks>
-        /// This method does the default implementation that uses the Encode method to get the token's Ids.
-        /// Tokenizer's models which care about performance may choose to override this method to provide a more efficient implementation.
-        /// </remarks>
-        public virtual int EncodeToIds(ReadOnlySpan<char> text, IList<int> accumulatedIds, out int textLength, int maxTokens = int.MaxValue)
-        {
-            if (accumulatedIds is null)
-            {
-                throw new ArgumentNullException(nameof(accumulatedIds));
-            }
-
-            // Default implementation is not optimized for memory allocation. It is recommended to override this method for the sake of the performance.
-            textLength = 0;
-            var tokens = Encode(text);
-
-            int count = Math.Min(tokens.Count, maxTokens);
-
-            for (int i = 0; i < count; i++)
-            {
-                textLength += tokens[i].Offset.Length;
-                accumulatedIds.Add(tokens[i].Id);
-            }
-
-            return count;
-        }
-
-        /// <summary>
-        /// Get the number of tokens that the input text will be encoded to.
-        /// </summary>
-        /// <param name="text">The text to encode.</param>
-        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        /// <remarks>
-        /// This method does the default implementation that uses the EncodeToIds method to get the number of token's Ids.
-        /// Tokenizer's models which care about performance may choose to override this method to provide a more efficient implementation.
-        /// </remarks>
-        public virtual int CountTokens(ReadOnlySpan<char> text, out int textLength, int maxTokens = int.MaxValue)
-        {
-            if (maxTokens <= 0)
-            {
-                throw new ArgumentOutOfRangeException(nameof(maxTokens), "The maximum number of tokens must be greater than 0.");
-            }
-
-            var ids = new List<int>();
-
-            if (maxTokens == int.MaxValue)
-            {
-                EncodeToIds(text, ids, out _);
-                textLength = text.Length;
-                return ids.Count;
-            }
-
-            IReadOnlyList<Token> tokens = Encode(text);
-            textLength = 0;
-            int count = Math.Min(tokens.Count, maxTokens);
-            for (int i = 0; i < count; i++)
-            {
-                textLength += tokens[i].Offset.Length;
-            }
-
-            return count;
-        }
-
-        /// <summary>
-        /// Get the number of tokens that the input text will be encoded to.
-        /// </summary>
-        /// <param name="text">The text to encode.</param>
-        /// <param name="textIndex">Starting from this index to the end of the text will encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        /// <remarks>
-        /// This method does the default implementation that uses the EncodeToIds method to get the number of token's Ids.
-        /// Tokenizer's models which care about performance may choose to override this method to provide a more efficient implementation.
-        /// </remarks>
-        public virtual int CountTokensFromEnd(ReadOnlySpan<char> text, out int textIndex, int maxTokens = int.MaxValue)
-        {
-            if (maxTokens <= 0)
-            {
-                throw new ArgumentOutOfRangeException(nameof(maxTokens), "The maximum number of tokens must be greater than 0.");
-            }
-
-            var ids = new List<int>();
-
-            if (maxTokens == int.MaxValue)
-            {
-                EncodeToIds(text, ids, out _);
-                textIndex = 0;
-                return ids.Count;
-            }
-
-            IReadOnlyList<Token> tokens = Encode(text);
-            textIndex = text.Length;
-            int count = Math.Min(tokens.Count, maxTokens);
-
-            int tokensCount = tokens.Count;
-            int end = tokensCount - count;
-            for (int i = tokensCount - 1; i >= end; i--)
-            {
-                textIndex -= tokens[i].Offset.Length;
-            }
-
-            return count;
-        }
-
-        /// <summary>
-        /// Map the token to encoded id with the option to skip the special tokens.
-        /// </summary>
-        /// <param name="token">The token to map to Id</param>
-        /// <returns>The mapped Id of the token.</returns>
-        public abstract int? MapTokenToId(ReadOnlySpan<char> token);
-
-        /// <summary>
-        /// Map the encoded Id to the token.
-        /// </summary>
-        /// <param name="id">The Id to map to the token.</param>
-        /// <returns>The mapped token of the Id.</returns>
-        public abstract string? MapIdToToken(int id);
-
-        /// <summary>
-        /// Decode the given ids, back to a String.
-        /// </summary>
-        /// <param name="ids">The list of ids that we want to decode.</param>
-        /// <returns>The decoded string.</returns>
-        /// <remarks>
-        /// This method does the default implementation that uses the MapIdToToken method to get the token.
-        /// Tokenizer models may opt to override this method to ensure accurate results if the default implementation
-        /// provided here proves insufficient for the model's specific scenario.
-        /// </remarks>
-        public virtual string? Decode(IEnumerable<int> ids)
-        {
-            if (ids is null)
-            {
-                throw new ArgumentNullException(nameof(ids));
-            }
-
-            ValueStringBuilder sb = new ValueStringBuilder();
-
-            foreach (int id in ids)
-            {
-                if (MapIdToToken(id) is string s)
-                {
-                    sb.Append(s);
-                }
-            }
-
-            return sb.ToString();
-        }
-    }
-}

src/Microsoft.ML.Tokenizers/Model/SentencePieceBpe.cs

@@ -19,7 +19,7 @@ namespace Microsoft.ML.Tokenizers
     /// <summary>
     /// SentencePieceBpe is a tokenizer that splits the input into tokens using the SentencePiece Bpe model.
     /// </summary>
-    public sealed class SentencePieceBpe : Model
+    public sealed class SentencePieceBpe : Tokenizer
     {
         private const int UninitializedId = -2; // indicate if the symbol contains uninitialized id.
 
@@ -29,9 +29,10 @@ namespace Microsoft.ML.Tokenizers
         private readonly int _maxByteId;
         private readonly int _byteCodeToIdOffset; // offset of mapping byte code to the to the Ids.
         private readonly int _oneByteUtf8EncodingMaxId; // the maximum value of the one byte UTF-8 character.
+        private readonly Normalizer? _normalizer;
 
         internal SentencePieceBpe(ModelProto modelProto, bool addBos, bool addEos) :
-                this(modelProto is null ? throw new ArgumentNullException(nameof(modelProto)) : modelProto)
+            this(modelProto is null ? throw new ArgumentNullException(nameof(modelProto)) : modelProto)
         {
             AddBeginningOfSentence = addBos;
             AddEndOfSentence = addEos;
@@ -65,6 +66,8 @@ namespace Microsoft.ML.Tokenizers
             EscapeWhiteSpaces = modelProto.NormalizerSpec.EscapeWhitespaces;
             TreatWhitespaceAsSuffix = modelProto.TrainerSpec.TreatWhitespaceAsSuffix;
             ByteFallback = modelProto.TrainerSpec.ByteFallback;
+
+            _normalizer = new SentencePieceNormalizer(modelProto.NormalizerSpec.RemoveExtraWhitespaces, AddDummyPrefix, EscapeWhiteSpaces, modelProto.TrainerSpec.TreatWhitespaceAsSuffix);
         }
 
         /// <summary>
@@ -127,6 +130,16 @@ namespace Microsoft.ML.Tokenizers
         /// </summary>
         public int UnknownId { get; }
 
+        /// <summary>
+        /// Gets the PreTokenizer used by the Tokenizer.
+        /// </summary>
+        public override PreTokenizer? PreTokenizer => null;
+
+        /// <summary>
+        /// Gets the Normalizer in use by the Tokenizer.
+        /// </summary>
+        public override Normalizer? Normalizer => _normalizer;
+
         /// <summary>
         /// The vocabulary of the model.
         /// </summary>
@@ -152,12 +165,74 @@ namespace Microsoft.ML.Tokenizers
         }
 
         /// <summary>
-        /// Encode a text to a list of tokens.
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <returns>The list of tokens generated from the text tokenization.</returns>
-        /// <remarks>The input text has to be normalized before calling this method.</remarks>
-        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text) => Encode(text, AddBeginningOfSentence, AddEndOfSentence);
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(string text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true)
+            => Encode(text, Span<char>.Empty, out normalizedString, AddBeginningOfSentence, AddEndOfSentence, considerPreTokenization, considerNormalization);
+
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true)
+            => Encode(null, text, out normalizedString, AddBeginningOfSentence, AddEndOfSentence, considerPreTokenization, considerNormalization);
+
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public IReadOnlyList<Token> Encode(string text, out string? normalizedString, bool addBeginningOfSentence, bool addEndOfSentence, bool considerPreTokenization = true, bool considerNormalization = true)
+            => Encode(text, Span<char>.Empty, out normalizedString, addBeginningOfSentence, addEndOfSentence, considerPreTokenization, considerNormalization);
+
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public IReadOnlyList<Token> Encode(ReadOnlySpan<char> text, out string? normalizedString, bool addBeginningOfSentence, bool addEndOfSentence, bool considerPreTokenization = true, bool considerNormalization = true)
+            => Encode(null, text, out normalizedString, addBeginningOfSentence, addEndOfSentence, considerPreTokenization, considerNormalization);
+
+        private IReadOnlyList<Token> Encode(string? text, ReadOnlySpan<char> textSpan, out string? normalizedString, bool addBeginningOfSentence, bool addEndOfSentence, bool considerPreTokenization, bool considerNormalization)
+        {
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                return [];
+            }
+
+            ReadOnlySpan<char> textToEncode = text is null ? textSpan : text.AsSpan();
+            if (considerNormalization && _normalizer is not null)
+            {
+                normalizedString = text is not null ? _normalizer.Normalize(text) : _normalizer.Normalize(textSpan);
+                textToEncode = normalizedString.AsSpan();
+            }
+            else
+            {
+                normalizedString = null;
+            }
+
+            return EncodeInternal(textToEncode, addBeginningOfSentence, addEndOfSentence);
+        }
 
         /// <summary>
         /// Encode a text to a list of tokens.
@@ -167,11 +242,11 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
         /// <returns>The list of tokens generated from the text tokenization.</returns>
         /// <remarks>The input text has to be normalized before calling this method.</remarks>
-        public IReadOnlyList<Token> Encode(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence)
+        private IReadOnlyList<Token> EncodeInternal(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence)
         {
             if (text.Length == 0)
             {
-                return Array.Empty<Token>();
+                return [];
             }
 
             BpeSymbol[] symbols = ArrayPool<BpeSymbol>.Shared.Rent(text.Length);
@@ -306,16 +381,168 @@ namespace Microsoft.ML.Tokenizers
         }
 
         /// <summary>
-        /// Encode a text to a list of Ids and add them to the accumulatedIds list.
+        /// Encodes input text to tokes Ids.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="accumulatedIds">The list of accumulated encoded Ids.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
         /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        /// <remarks>The input text has to be normalized before calling this method.</remarks>
-        public override int EncodeToIds(ReadOnlySpan<char> text, IList<int> accumulatedIds, out int textLength, int maxTokens = int.MaxValue)
-            => EncodeToIds(text, AddBeginningOfSentence, AddEndOfSentence, accumulatedIds, out textLength, maxTokens);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public IReadOnlyList<int> EncodeToIds(string text, bool addBeginningOfSentence, bool addEndOfSentence, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, addBeginningOfSentence, addEndOfSentence, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool addBeginningOfSentence, bool addEndOfSentence, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, addBeginningOfSentence, addEndOfSentence, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public IReadOnlyList<int> EncodeToIds(string text, bool addBeginningOfSentence, bool addEndOfSentence, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, addBeginningOfSentence, addEndOfSentence, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool addBeginningOfSentence, bool addEndOfSentence, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, addBeginningOfSentence, addEndOfSentence, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+
+        private IReadOnlyList<int> EncodeToIds(string? text, ReadOnlySpan<char> textSpan, bool addBeginningOfSentence, bool addEndOfSentence, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                textLength = 0;
+                return [];
+            }
+
+            return EncodeToIds(text is null ? textSpan : text.AsSpan(), addBeginningOfSentence, addEndOfSentence, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+        }
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool addBeginningOfSentence, bool addEndOfSentence, bool considerNormalization,
+                                                out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            if (text.IsEmpty)
+            {
+                normalizedString = null;
+                textLength = 0;
+                return [];
+            }
+
+            ReadOnlySpan<char> textToEncode;
+
+            if (considerNormalization && _normalizer is not null)
+            {
+                normalizedString = _normalizer.Normalize(text);
+                textToEncode = normalizedString.AsSpan();
+            }
+            else
+            {
+                normalizedString = null;
+                textToEncode = text;
+            }
+
+            List<int> ids = new();
+
+            EncodeToIds(textToEncode, addBeginningOfSentence, addEndOfSentence, ids, out textLength, maxTokenCount);
+
+            return ids;
+        }
 
         /// <summary>
         /// Encode a text to a list of Ids and add them to the accumulatedIds list.
@@ -328,7 +555,7 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="maxTokens">The maximum number of tokens to encode.</param>
         /// <returns>The number of tokens that the input text will be encoded to.</returns>
         /// <remarks>The input text has to be normalized before calling this method.</remarks>
-        public int EncodeToIds(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence, IList<int> accumulatedIds, out int textLength, int maxTokens = int.MaxValue)
+        private int EncodeToIds(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence, IList<int> accumulatedIds, out int textLength, int maxTokens = int.MaxValue)
         {
             if (maxTokens <= 0)
             {
@@ -378,7 +605,8 @@ namespace Microsoft.ML.Tokenizers
                     {
                         if (!EncodeAsBytes(text.Slice(symbols[index].pieceSpan.Index, symbols[index].pieceSpan.Length), symbols[index].pieceSpan.Index, ref textLength))
                         {
-                            break;
+                            ArrayPool<BpeSymbol>.Shared.Return(symbols);
+                            return idsCount;
                         }
                     }
                     else
@@ -391,6 +619,7 @@ namespace Microsoft.ML.Tokenizers
                         }
                         else
                         {
+                            ArrayPool<BpeSymbol>.Shared.Return(symbols);
                             return idsCount;
                         }
                     }
@@ -510,21 +739,252 @@ namespace Microsoft.ML.Tokenizers
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
-        /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        /// <remarks>The input text has to be normalized before calling this method.</remarks>
-        public override int CountTokens(ReadOnlySpan<char> text, out int textLength, int maxTokens = int.MaxValue) => CountTokens(text, AddBeginningOfSentence, AddEndOfSentence, out textLength, maxTokens);
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(text, Span<char>.Empty, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out _, out _);
 
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <param name="textIndex">Starting from this index to the end of the text will encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(null, text, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(text, Span<char>.Empty, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(null, text, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        /// <summary>
+        /// Get the number of tokens that the input text will be encoded to.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public int CountTokens(string text, bool addBeginningOfSentence, bool addEndOfSentence, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(text, Span<char>.Empty, addBeginningOfSentence, addEndOfSentence, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Get the number of tokens that the input text will be encoded to.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public int CountTokens(ReadOnlySpan<char> text, bool addBeginningOfSentence, bool addEndOfSentence, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(null, text, addBeginningOfSentence, addEndOfSentence, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public int IndexOfTokenCount(string text, bool addBeginningOfSentence, bool addEndOfSentence, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(text, Span<char>.Empty, addBeginningOfSentence, addEndOfSentence, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public int IndexOfTokenCount(ReadOnlySpan<char> text, bool addBeginningOfSentence, bool addEndOfSentence, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(null, text, addBeginningOfSentence, addEndOfSentence, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        private int CountTokens(string? text, ReadOnlySpan<char> textSpan, bool addBeginningOfSentence, bool addEndOfSentence, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+            => CountTokens(text is null ? textSpan : text.AsSpan(), addBeginningOfSentence, addEndOfSentence, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        /// <summary>
+        /// Get the number of tokens that the input text will be encoded to.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
         /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int CountTokensFromEnd(ReadOnlySpan<char> text, out int textIndex, int maxTokens = int.MaxValue) => CountTokensFromEnd(text, AddBeginningOfSentence, AddEndOfSentence, out textIndex, maxTokens);
+        public int CountTokens(ReadOnlySpan<char> text, bool addBeginningOfSentence, bool addEndOfSentence, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            if (text.IsEmpty)
+            {
+                normalizedString = null;
+                textLength = 0;
+                return 0;
+            }
+
+            ReadOnlySpan<char> textToEncode;
+            if (considerNormalization && _normalizer is not null)
+            {
+                normalizedString = _normalizer.Normalize(text);
+                textToEncode = normalizedString.AsSpan();
+            }
+            else
+            {
+                normalizedString = null;
+                textToEncode = text;
+            }
+
+            return CountTokens(textToEncode, addBeginningOfSentence, addEndOfSentence, out textLength, maxTokenCount);
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if normalization is enabled;
+        /// conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(text, Span<char>.Empty, maxTokenCount, considerNormalization, out normalizedString, out tokenCount);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the <paramref name="normalizedString"/>; conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(null, text, maxTokenCount, considerNormalization, out normalizedString, out tokenCount);
+
+        private int LastIndexOf(string? text, ReadOnlySpan<char> textSpan, int maxTokenCount, bool considerNormalization, out string? normalizedString, out int tokenCount)
+            => LastIndexOfTokenCount(text is null ? textSpan : text.AsSpan(), maxTokenCount, AddBeginningOfSentence, AddEndOfSentence, considerNormalization, out normalizedString, out tokenCount);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="addBeginningOfSentence">Indicate emitting the beginning of sentence token during the encoding.</param>
+        /// <param name="addEndOfSentence">Indicate emitting the end of sentence token during the encoding.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the <paramref name="normalizedString"/>; conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public int LastIndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, bool addBeginningOfSentence, bool addEndOfSentence, bool considerNormalization, out string? normalizedString, out int tokenCount)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The max token count must be greater than 0.");
+            }
+
+            if (text.IsEmpty)
+            {
+                normalizedString = null;
+                tokenCount = 0;
+                return 0;
+            }
+
+            ReadOnlySpan<char> textToEncode;
+            if (considerNormalization && _normalizer is not null)
+            {
+                normalizedString = _normalizer.Normalize(text);
+                textToEncode = normalizedString.AsSpan();
+            }
+            else
+            {
+                normalizedString = null;
+                textToEncode = text;
+            }
+
+            tokenCount = CountTokensFromEnd(textToEncode, addBeginningOfSentence, addEndOfSentence, out int textIndex, maxTokenCount);
+            return textIndex;
+        }
 
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
@@ -536,7 +996,7 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="maxTokens">The maximum number of tokens to encode.</param>
         /// <returns>The number of tokens that the input text will be encoded to.</returns>
         /// <remarks>The input text has to be normalized before calling this method.</remarks>
-        public int CountTokens(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence, out int textLength, int maxTokens = int.MaxValue)
+        private int CountTokens(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence, out int textLength, int maxTokens = int.MaxValue)
         {
             textLength = 0;
             if (text.IsEmpty)
@@ -705,7 +1165,7 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="maxTokens">The maximum number of tokens to encode.</param>
         /// <returns>The number of tokens that the input text will be encoded to.</returns>
         /// <remarks>The input text has to be normalized before calling this method.</remarks>
-        public int CountTokensFromEnd(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence, out int textIndex, int maxTokens = int.MaxValue)
+        private int CountTokensFromEnd(ReadOnlySpan<char> text, bool addBeginOfSentence, bool addEndOfSentence, out int textIndex, int maxTokens = int.MaxValue)
         {
             textIndex = text.Length;
             if (text.IsEmpty)
@@ -944,7 +1404,7 @@ namespace Microsoft.ML.Tokenizers
             else if (_vocabReverse.TryGetValue(enumerator.Current, out string? token))
             {
                 // escape the dummy prefix if needed.
-                sb.Append(AddDummyPrefix && !TreatWhitespaceAsSuffix && token.Length > 0 && token[0] == LlamaNormalizer.DummyPrefix ?
+                sb.Append(AddDummyPrefix && !TreatWhitespaceAsSuffix && token.Length > 0 && token[0] == SentencePieceNormalizer.DummyPrefix ?
                                     token.AsSpan(1) :
                                     token.AsSpan());
             }
@@ -999,7 +1459,7 @@ namespace Microsoft.ML.Tokenizers
                 FlushBytes(ref bytesCount, ref bytesPoolArray, ref charPoolArray, ref sb);
             }
 
-            if (AddDummyPrefix && TreatWhitespaceAsSuffix && sb.Length > 0 && sb[sb.Length - 1] == LlamaNormalizer.DummyPrefix)
+            if (AddDummyPrefix && TreatWhitespaceAsSuffix && sb.Length > 0 && sb[sb.Length - 1] == SentencePieceNormalizer.DummyPrefix)
             {
                 sb.RemoveLastChar();
             }
@@ -1014,7 +1474,7 @@ namespace Microsoft.ML.Tokenizers
                 ArrayPool<char>.Shared.Return(charPoolArray);
             }
 
-            return sb.ToString(LlamaNormalizer.DummyPrefix, ' ');
+            return sb.ToString(SentencePieceNormalizer.DummyPrefix, ' ');
 
             static void FlushBytes(ref int bytesCount, ref byte[]? bytesPoolArray, ref char[]? charPoolArray, ref ValueStringBuilder sb)
             {

src/Microsoft.ML.Tokenizers/Model/Tiktoken.cs

@@ -19,9 +19,9 @@ using System.Threading.Tasks;
 namespace Microsoft.ML.Tokenizers
 {
     /// <summary>
-    /// Represent the rapid Byte Pair Encoding model commonly referred to as Tiktoken.
+    /// Represent the rapid Byte Pair Encoding tokenizer.
     /// </summary>
-    public sealed partial class Tiktoken : Model
+    public sealed partial class Tiktoken : Tokenizer
     {
         private readonly Dictionary<ReadOnlyMemory<byte>, int> _encoder;
         private readonly Dictionary<int, ReadOnlyMemory<byte>> _decoder;
@@ -29,46 +29,56 @@ namespace Microsoft.ML.Tokenizers
         private readonly Dictionary<StringSpanOrdinalKey, (int Id, string Token)> _vocab;
         private IReadOnlyDictionary<string, int>? _vocabOriginal;
         private const int MaxWordLengthToCache = 15;
+        private readonly PreTokenizer? _preTokenizer;
+        private readonly Normalizer? _normalizer;
 
         /// <summary>
-        /// Create a new Tiktoken tokenizer's model object.
+        /// Create a new Tiktoken tokenizer's object.
         /// </summary>
         /// <param name="vocabFilePath">The path to the BPE vocab file.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
         /// <param name="specialTokens">The dictionary mapping special tokens to Ids.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
         /// <param name="cacheSize">The size of the cache to use.</param>
         /// <exception cref="ArgumentNullException">Thrown when <paramref name="vocabFilePath"/> is null or empty.</exception>
         /// <exception cref="InvalidOperationException">Thrown when failed to load the BPE vocab file.</exception>
-        public Tiktoken(string vocabFilePath, IReadOnlyDictionary<string, int>? specialTokens = null, int cacheSize = LruCache<int[]>.DefaultCacheSize) :
-            this(string.IsNullOrEmpty(vocabFilePath) ? throw new ArgumentNullException(nameof(vocabFilePath)) : File.OpenRead(vocabFilePath), specialTokens, cacheSize, disposeStream: true)
+        public Tiktoken(string vocabFilePath, PreTokenizer? preTokenizer, IReadOnlyDictionary<string, int>? specialTokens = null, Normalizer? normalizer = null, int cacheSize = LruCache<int[]>.DefaultCacheSize) :
+            this(string.IsNullOrEmpty(vocabFilePath) ? throw new ArgumentNullException(nameof(vocabFilePath)) : File.OpenRead(vocabFilePath), preTokenizer, specialTokens, normalizer, cacheSize, disposeStream: true)
         {
         }
 
         /// <summary>
-        /// Create a new Tiktoken tokenizer's model object.
+        /// Create a new Tiktoken tokenizer's object.
         /// </summary>
         /// <param name="vocabStream">The stream to the BPE vocab file.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
         /// <param name="specialTokens">The dictionary mapping special tokens to Ids.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
         /// <param name="cacheSize">The size of the cache to use.</param>
         /// <exception cref="ArgumentNullException">Thrown when <paramref name="vocabStream"/> is null or empty.</exception>
         /// <exception cref="InvalidOperationException">Thrown when failed to load the BPE vocab file.</exception>
-        public Tiktoken(Stream vocabStream, IReadOnlyDictionary<string, int>? specialTokens = null, int cacheSize = LruCache<int[]>.DefaultCacheSize) :
-            this(vocabStream ?? throw new ArgumentNullException(nameof(vocabStream)), specialTokens, cacheSize, disposeStream: false)
+        public Tiktoken(Stream vocabStream, PreTokenizer? preTokenizer, IReadOnlyDictionary<string, int>? specialTokens = null, Normalizer? normalizer = null, int cacheSize = LruCache<int[]>.DefaultCacheSize) :
+            this(vocabStream ?? throw new ArgumentNullException(nameof(vocabStream)), preTokenizer, specialTokens, normalizer, cacheSize, disposeStream: false)
         {
         }
 
         /// <summary>
-        /// Create a new Tiktoken tokenizer's model object.
+        /// Create a new Tiktoken tokenizer's object.
         /// </summary>
         /// <param name="encoder">The dictionary mapping token utf-8 bytes to Ids.</param>
         /// <param name="decoder">The dictionary mapping Ids to token utf-8 bytes.</param>
         /// <param name="vocab">The dictionary mapping string tokens to Ids.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
         /// <param name="specialTokens">The dictionary mapping special tokens to Ids.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
         /// <param name="cacheSize">The max size of the cache to use.</param>
         internal Tiktoken(
             Dictionary<ReadOnlyMemory<byte>, int> encoder,
             Dictionary<int, ReadOnlyMemory<byte>> decoder,
             Dictionary<StringSpanOrdinalKey, (int Id, string Token)> vocab,
+            PreTokenizer? preTokenizer,
             IReadOnlyDictionary<string, int>? specialTokens,
+            Normalizer? normalizer = null,
             int cacheSize = LruCache<int[]>.DefaultCacheSize)
         {
             _encoder = encoder ?? throw new ArgumentNullException(nameof(encoder));
@@ -78,19 +88,26 @@ namespace Microsoft.ML.Tokenizers
             _encoder = encoder!;
             _decoder = decoder!;
             _vocab = vocab!;
+
+            _preTokenizer = preTokenizer;
+            _normalizer = normalizer;
+
             _cache = new LruCache<(int[] Bytes, string Token)>(cacheSize);
 
             SpecialTokens = specialTokens;
             CacheSpecialTokensEncoding(specialTokens);
         }
 
-        private Tiktoken(Stream vocabStream, IReadOnlyDictionary<string, int>? specialTokens, int cacheSize, bool disposeStream)
+        private Tiktoken(Stream vocabStream, PreTokenizer? preTokenizer, IReadOnlyDictionary<string, int>? specialTokens, Normalizer? normalizer, int cacheSize, bool disposeStream)
         {
             try
             {
                 _cache = new LruCache<(int[] Bytes, string Token)>(cacheSize);
                 (_encoder, _vocab, _decoder) = LoadTiktokenBpeAsync(vocabStream, useAsync: false).GetAwaiter().GetResult();
 
+                _preTokenizer = preTokenizer;
+                _normalizer = normalizer;
+
                 SpecialTokens = specialTokens;
                 CacheSpecialTokensEncoding(specialTokens);
             }
@@ -103,6 +120,16 @@ namespace Microsoft.ML.Tokenizers
             }
         }
 
+        /// <summary>
+        /// Gets the PreTokenizer used by the Tokenizer.
+        /// </summary>
+        public override PreTokenizer? PreTokenizer => _preTokenizer;
+
+        /// <summary>
+        /// Gets the Normalizer in use by the Tokenizer.
+        /// </summary>
+        public override Normalizer? Normalizer => _normalizer;
+
         private void CacheSpecialTokensEncoding(IReadOnlyDictionary<string, int>? specialTokens)
         {
             Debug.Assert(_cache is not null);
@@ -118,54 +145,6 @@ namespace Microsoft.ML.Tokenizers
             }
         }
 
-        /// <summary>
-        /// Create a new Tiktoken tokenizer's model object asynchronously.
-        /// </summary>
-        /// <param name="vocabStream">The stream to the BPE vocab file.</param>
-        /// <param name="specialTokens">The dictionary mapping special tokens to Ids.</param>
-        /// <param name="cacheSize">The size of the cache to use.</param>
-        /// <param name="cancellationToken"><see cref="CancellationToken"/> used to request cancellation of the operation.</param>
-        /// <returns>Tiktoken tokenizer's object.</returns>
-        public static async Task<Tiktoken> CreateAsync(
-                            Stream vocabStream,
-                            IReadOnlyDictionary<string, int>? specialTokens = null,
-                            int cacheSize = LruCache<int[]>.DefaultCacheSize,
-                            CancellationToken cancellationToken = default)
-        {
-            if (vocabStream is null)
-            {
-                throw new ArgumentNullException(nameof(vocabStream));
-            }
-
-            (Dictionary<ReadOnlyMemory<byte>, int> encoder, Dictionary<StringSpanOrdinalKey, (int Id, string Token)> vocab, Dictionary<int, ReadOnlyMemory<byte>> decoder) =
-                        await LoadTiktokenBpeAsync(vocabStream, useAsync: true, cancellationToken).ConfigureAwait(false);
-
-            return new Tiktoken(encoder, decoder, vocab, specialTokens, cacheSize);
-        }
-
-        /// <summary>
-        /// Create a new Tiktoken tokenizer's object asynchronously.
-        /// </summary>
-        /// <param name="vocabFilePath">The BPE vocab file.</param>
-        /// <param name="specialTokensEncoder">The dictionary mapping special tokens to Ids.</param>
-        /// <param name="cacheSize">The size of the cache to use.</param>
-        /// <param name="cancellationToken"><see cref="CancellationToken"/> used to request cancellation of the operation.</param>
-        /// <returns>Tiktoken tokenizer's model object.</returns>
-        public static async Task<Tiktoken> CreateAsync(
-                                string vocabFilePath,
-                                IReadOnlyDictionary<string, int>? specialTokensEncoder = null,
-                                int cacheSize = LruCache<int[]>.DefaultCacheSize,
-                                CancellationToken cancellationToken = default)
-        {
-            if (vocabFilePath is null)
-            {
-                throw new ArgumentNullException(nameof(vocabFilePath));
-            }
-
-            using Stream vocabStream = File.OpenRead(vocabFilePath);
-            return await CreateAsync(vocabStream, specialTokensEncoder, cacheSize, cancellationToken).ConfigureAwait(false);
-        }
-
         /// <summary>
         /// Load BPE vocab dictionary from a stream.
         /// </summary>
@@ -254,37 +233,80 @@ namespace Microsoft.ML.Tokenizers
             }
         }
 
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(string text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true) => Encode(text, Span<char>.Empty, out normalizedString, considerPreTokenization, considerNormalization);
+
+        /// <summary>
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true) => Encode(null, text, out normalizedString, considerPreTokenization, considerNormalization);
+
+        private IReadOnlyList<Token> Encode(string? text, ReadOnlySpan<char> textSpan, out string? normalizedString, bool considerPreTokenization, bool considerNormalization)
+        {
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                return [];
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            List<Token> tokens = new();
+
+            if (splits is not null)
+            {
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    Encode(textSpanToEncode.Slice(split.Offset, split.Length), tokens, split.Offset);
+                }
+            }
+            else
+            {
+                Encode(textSpanToEncode, tokens, 0);
+            }
+
+            return tokens;
+        }
+
         /// <summary>
         /// Encode text to a list of tokens.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <returns>The list of tokens generated from the text tokenization.</returns>
-        public override IReadOnlyList<Token> Encode(ReadOnlySpan<char> text)
+        /// <param name="tokens">The list of tokens to populate.</param>
+        /// <param name="offset">The offset to start encoding from.</param>
+        private void Encode(ReadOnlySpan<char> text, List<Token> tokens, int offset)
         {
-            Token[] tokens;
-
-            if (text.IsEmpty)
-            {
-                return Array.Empty<Token>();
-            }
+            Debug.Assert(!text.IsEmpty);
 
             if (_cache.TryGetValue(text, out (int[] Ids, string Token) value))
             {
-                tokens = new Token[value.Ids.Length];
-                tokens[0] = new Token(value.Ids[0], value.Token, (0, value.Token.Length));
+                tokens.Add(new Token(value.Ids[0], value.Token, (offset, value.Token.Length)));
                 for (int i = 1; i < value.Ids.Length; i++)
                 {
                     // One word split mapped to multiple Ids. Make the offset of the remaining token point at the end with zero width.
-                    tokens[i] = new Token(value.Ids[i], "", (text.Length, 0));
+                    tokens.Add(new Token(value.Ids[i], "", (offset + text.Length, 0)));
                 }
 
-                return tokens;
+                return;
             }
 
             // cache miss
             if (_vocab.TryGetValue(text, out (int Id, string Token) mappedId))
             {
-                return new Token[1] { new(mappedId.Id, mappedId.Token, (0, mappedId.Token.Length)) };
+                tokens.Add(new Token(mappedId.Id, mappedId.Token, (offset, mappedId.Token.Length)));
+                return;
             }
 
             byte[] arrayPoolArray = ArrayPool<byte>.Shared.Rent(Encoding.UTF8.GetMaxByteCount(text.Length));
@@ -301,15 +323,98 @@ namespace Microsoft.ML.Tokenizers
                 _cache.Add(textAsString, (encodedIds, textAsString));
             }
 
-            tokens = new Token[encodedIds.Length];
-            tokens[0] = new Token(encodedIds[0], textAsString, (0, text.Length));
+            tokens.Add(new Token(encodedIds[0], textAsString, (offset, text.Length)));
             for (int i = 1; i < encodedIds.Length; i++)
             {
                 // One word split mapped to multiple Ids. Make the offset of the remaining token point at the end with zero width.
-                tokens[i] = new Token(encodedIds[i], "", (text.Length, 0));
+                tokens.Add(new Token(encodedIds[i], "", (offset + text.Length, 0)));
+            }
+        }
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(string text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public override IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(null, text, considerPreTokenization, considerNormalization, out normalizedString, out textLength, maxTokenCount);
+
+        private IReadOnlyList<int> EncodeToIds(string? text, ReadOnlySpan<char> textSpan, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
             }
 
-            return tokens;
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                textLength = 0;
+                normalizedString = null;
+                return [];
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            List<int> ids = new();
+
+            if (splits is not null)
+            {
+                textLength = 0;
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    EncodeToIds(textSpanToEncode.Slice(split.Offset, split.Length), ids, out int length, maxTokenCount - ids.Count);
+                    textLength = split.Offset + length;
+
+                    if (length < split.Length || ids.Count >= maxTokenCount)
+                    {
+                        break;
+                    }
+                }
+            }
+            else
+            {
+                EncodeToIds(textSpanToEncode, ids, out textLength);
+            }
+
+            return ids;
         }
 
         /// <summary>
@@ -318,11 +423,11 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="text">The text to encode.</param>
         /// <param name="accumulatedIds">The list of accumulated Ids.</param>
         /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
-        /// <param name="maxTokens">The maximum number of tokens to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
         /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int EncodeToIds(ReadOnlySpan<char> text, IList<int> accumulatedIds, out int textLength, int maxTokens = int.MaxValue)
+        private int EncodeToIds(ReadOnlySpan<char> text, IList<int> accumulatedIds, out int textLength, int maxTokenCount = int.MaxValue)
         {
-            Debug.Assert(maxTokens > 0);
+            Debug.Assert(maxTokenCount > 0);
 
             if (text.IsEmpty)
             {
@@ -332,7 +437,7 @@ namespace Microsoft.ML.Tokenizers
 
             if (_cache.TryGetValue(text, out (int[] Ids, string Token) value))
             {
-                if (value.Ids.Length <= maxTokens)
+                if (value.Ids.Length <= maxTokenCount)
                 {
                     accumulatedIds.AddRange(value.Ids);
                     textLength = text.Length;
@@ -362,7 +467,7 @@ namespace Microsoft.ML.Tokenizers
             }
 
             int result;
-            if (encodedIds.Length <= maxTokens)
+            if (encodedIds.Length <= maxTokenCount)
             {
                 accumulatedIds.AddRange(encodedIds);
                 textLength = text.Length;
@@ -378,6 +483,104 @@ namespace Microsoft.ML.Tokenizers
             return result;
         }
 
+        /// <summary>
+        /// Get the number of tokens that the input text will be encoded to.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Get the number of tokens that the input text will be encoded to.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public override int CountTokens(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(null, text, considerPreTokenization, considerNormalization, out _, out _);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(text, Span<char>.Empty, considerPreTokenization, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public override int IndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+        {
+            tokenCount = CountTokens(null, text, considerPreTokenization, considerNormalization, out normalizedString, out int textLength, maxTokenCount);
+            return textLength;
+        }
+
+        private int CountTokens(string? text, ReadOnlySpan<char> textSpan, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int textLength, int maxTokenCount = int.MaxValue)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than zero.");
+            }
+
+            textLength = 0;
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                return 0;
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            int count = 0;
+            if (splits is not null)
+            {
+                foreach ((int Offset, int Length) split in splits)
+                {
+                    count += CountTokens(textSpanToEncode.Slice(split.Offset, split.Length), out int length, maxTokenCount - count);
+                    textLength = split.Offset + length;
+
+                    if (length < split.Length || count >= maxTokenCount)
+                    {
+                        break;
+                    }
+                }
+            }
+            else
+            {
+                count = CountTokens(textSpanToEncode, out textLength, maxTokenCount);
+            }
+
+            return count;
+        }
+
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
@@ -385,7 +588,7 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
         /// <param name="maxTokens">The maximum number of tokens to encode.</param>
         /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int CountTokens(ReadOnlySpan<char> text, out int textLength, int maxTokens = int.MaxValue)
+        private int CountTokens(ReadOnlySpan<char> text, out int textLength, int maxTokens = int.MaxValue)
         {
             Debug.Assert(maxTokens > 0);
 
@@ -439,6 +642,76 @@ namespace Microsoft.ML.Tokenizers
             return result;
         }
 
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if normalization is enabled;
+        /// conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(text, Span<char>.Empty, maxTokenCount, considerPreTokenization, considerNormalization, out normalizedString, out tokenCount);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the <paramref name="normalizedString"/>; conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public override int LastIndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOf(null, text, maxTokenCount, considerPreTokenization, considerNormalization, out normalizedString, out tokenCount);
+
+        private int LastIndexOf(string? text, ReadOnlySpan<char> textSpan, int maxTokenCount, bool considerPreTokenization, bool considerNormalization, out string? normalizedString, out int tokenCount)
+        {
+            if (maxTokenCount <= 0)
+            {
+                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The max token count must be greater than 0.");
+            }
+
+            if (string.IsNullOrEmpty(text) && textSpan.IsEmpty)
+            {
+                normalizedString = null;
+                tokenCount = 0;
+                return 0;
+            }
+
+            IEnumerable<(int Offset, int Length)>? splits = InitializeForEncoding(text, textSpan, considerPreTokenization, considerNormalization, _normalizer, _preTokenizer, out normalizedString, out ReadOnlySpan<char> textSpanToEncode);
+
+            if (splits is not null)
+            {
+                tokenCount = 0;
+                foreach ((int Offset, int Length) split in splits.Reverse())
+                {
+                    tokenCount += CountTokensFromEnd(textSpanToEncode.Slice(split.Offset, split.Length), out int textIndex, maxTokenCount - tokenCount);
+                    if (textIndex > 0 || tokenCount >= maxTokenCount)
+                    {
+                        return split.Offset + textIndex;
+                    }
+                }
+
+                return 0;
+            }
+            else
+            {
+                tokenCount = CountTokensFromEnd(textSpanToEncode, out int textLength, maxTokenCount);
+                return textLength;
+            }
+        }
+
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
@@ -446,7 +719,7 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="textIndex">Starting from this index to the end of the text will encompasses the maximum encoded tokens.</param>
         /// <param name="maxTokens">The maximum number of tokens to encode.</param>
         /// <returns>The number of tokens that the input text will be encoded to.</returns>
-        public override int CountTokensFromEnd(ReadOnlySpan<char> text, out int textIndex, int maxTokens = int.MaxValue)
+        private int CountTokensFromEnd(ReadOnlySpan<char> text, out int textIndex, int maxTokens = int.MaxValue)
         {
             Debug.Assert(maxTokens > 0);
 
@@ -510,7 +783,7 @@ namespace Microsoft.ML.Tokenizers
         {
             if (token.IsEmpty)
             {
-                return 0;
+                return null;
             }
 
             if (_cache.TryGetValue(token, out (int[] Ids, string Token) value))
@@ -676,8 +949,8 @@ namespace Microsoft.ML.Tokenizers
                                                             [
                                                                 // chat
                                                                 ( "gpt-4-", ModelEncoding.Cl100kBase),          // e.g., gpt-4-0314, etc., plus gpt-4-32k
-                                                                ( "gpt-3.5-turbo-", ModelEncoding.Cl100kBase),  // e.g, gpt-3.5-turbo-0301, -0401, etc.
-                                                                ( "gpt-35-turbo-", ModelEncoding.Cl100kBase )   // Azure deployment name
+                                                                ( "gpt-3.5-", ModelEncoding.Cl100kBase),  // e.g, gpt-3.5-turbo-0301, -0401, etc.
+                                                                ( "gpt-35-", ModelEncoding.Cl100kBase )         // Azure deployment name
                                                             ];
 
         private static readonly Dictionary<string, ModelEncoding> _modelToEncoding =
@@ -687,6 +960,7 @@ namespace Microsoft.ML.Tokenizers
                                                                 { "gpt-4", ModelEncoding.Cl100kBase },
                                                                 { "gpt-3.5-turbo", ModelEncoding.Cl100kBase },
                                                                 { "gpt-3.5-turbo-16k", ModelEncoding.Cl100kBase },
+                                                                { "gpt-35", ModelEncoding.Cl100kBase },           // Azure deployment name
                                                                 { "gpt-35-turbo", ModelEncoding.Cl100kBase },     // Azure deployment name
                                                                 { "gpt-35-turbo-16k", ModelEncoding.Cl100kBase }, // Azure deployment name
 
@@ -817,26 +1091,13 @@ namespace Microsoft.ML.Tokenizers
 
         private static readonly ConcurrentDictionary<string, (Dictionary<ReadOnlyMemory<byte>, int> encoder, Dictionary<StringSpanOrdinalKey, (int Id, string Token)> vocab, Dictionary<int, ReadOnlyMemory<byte>> decoder)> _tiktokenCache = new(StringComparer.OrdinalIgnoreCase);
 
-        internal static Tokenizer CreateTokenizerForModel(
-                                                string modelName,
-                                                IReadOnlyDictionary<string, int>? extraSpecialTokens = null,
-                                                Normalizer? normalizer = null)
+        internal static Tokenizer CreateForModel(
+                                    ModelEncoding modelEncoding,
+                                    string? modelName = null,
+                                    IReadOnlyDictionary<string, int>? extraSpecialTokens = null,
+                                    Normalizer? normalizer = null)
         {
-            if (string.IsNullOrEmpty(modelName))
-            {
-                throw new ArgumentNullException(nameof(modelName));
-            }
-
-            return CreateTokenizerForModel(GetModelEncoding(modelName), modelName, extraSpecialTokens, normalizer);
-        }
-
-        internal static Tokenizer CreateTokenizerForModel(
-                                                ModelEncoding modelEncoding,
-                                                string? modelName = null,
-                                                IReadOnlyDictionary<string, int>? extraSpecialTokens = null,
-                                                Normalizer? normalizer = null)
-        {
-            (Dictionary<string, int> SpecialTokens, Regex Regex, string VocabFile) tiktokenConfiguration = Tiktoken.GetTiktokenConfigurations(modelEncoding, modelName);
+            (Dictionary<string, int> SpecialTokens, Regex Regex, string VocabFile) tiktokenConfiguration = GetTiktokenConfigurations(modelEncoding, modelName);
 
             if (extraSpecialTokens is not null)
             {
@@ -858,10 +1119,14 @@ namespace Microsoft.ML.Tokenizers
                 _tiktokenCache.TryAdd(tiktokenConfiguration.VocabFile, cache);
             }
 
-            return new Tokenizer(
-                            new Tiktoken(cache.encoder, cache.decoder, cache.vocab, tiktokenConfiguration.SpecialTokens, LruCache<int[]>.DefaultCacheSize),
-                            new TiktokenPreTokenizer(tiktokenConfiguration.Regex, tiktokenConfiguration.SpecialTokens),
-                            normalizer);
+            return new Tiktoken(
+                        cache.encoder,
+                        cache.decoder,
+                        cache.vocab,
+                        new TiktokenPreTokenizer(tiktokenConfiguration.Regex, tiktokenConfiguration.SpecialTokens),
+                        tiktokenConfiguration.SpecialTokens,
+                        normalizer,
+                        LruCache<int[]>.DefaultCacheSize);
         }
     }
 }

src/Microsoft.ML.Tokenizers/Model/Word.cs

@@ -97,24 +97,24 @@ namespace Microsoft.ML.Tokenizers
             return changes;
         }
 
-        public void MergeAll(Dictionary<Pair<int>, (int, int)> merges, float? dropout)
+        public void MergeAll(Dictionary<Pair<int>, (int, int)> merges, float? dropout, ref PriorityQueue<Merge>? priorityQueue)
         {
-            // Queue<Merge> queue = new Queue<Merge>(_symbols.Count);
-            PriorityQueue<Merge> queue = new PriorityQueue<Merge>(_symbols.Count);
+            priorityQueue ??= new PriorityQueue<Merge>(_symbols.Count);
+            priorityQueue.Clear();
 
-            Vec<Merge> skip = new Vec<Merge>(queue.Count);
+            Vec<Merge> skip = new Vec<Merge>(priorityQueue.Count);
 
             for (int i = 0; i < _symbols.Count - 1; i++)
             {
                 if (merges.TryGetValue(Pair<int>.Create(_symbols[i].C, _symbols[i + 1].C), out (int m1, int m2) value))
                 {
-                    queue.Enqueue(new Merge(i, value.m1, value.m2));
+                    priorityQueue.Enqueue(new Merge(i, value.m1, value.m2));
                 }
             }
 
-            while (queue.Count > 0)
+            while (priorityQueue.Count > 0)
             {
-                Merge top = queue.Dequeue();
+                Merge top = priorityQueue.Dequeue();
                 if (dropout.HasValue && (_random ??= new()).NextDouble() < dropout)
                 {
                     skip.Push(top);
@@ -124,7 +124,7 @@ namespace Microsoft.ML.Tokenizers
                     // Re-insert the skipped elements
                     for (int i = 0; i < skip.Count; i++)
                     {
-                        queue.Enqueue(skip[i]);
+                        priorityQueue.Enqueue(skip[i]);
                     }
                     skip.Clear();
 
@@ -166,7 +166,7 @@ namespace Microsoft.ML.Tokenizers
 
                         if (merges.TryGetValue(newPair, out value))
                         {
-                            queue.Enqueue(new Merge(current.Prev, value.m1, value.m2));
+                            priorityQueue.Enqueue(new Merge(current.Prev, value.m1, value.m2));
                         }
                     }
 
@@ -178,7 +178,7 @@ namespace Microsoft.ML.Tokenizers
                         Pair<int> newPair = Pair<int>.Create(current.C, nextSymbol.C);
                         if (merges.TryGetValue(newPair, out value))
                         {
-                            queue.Enqueue(new Merge(top.Pos, value.m1, value.m2));
+                            priorityQueue.Enqueue(new Merge(top.Pos, value.m1, value.m2));
                         }
                     }
                 }
@@ -289,19 +289,16 @@ namespace Microsoft.ML.Tokenizers
             return sb.ToString();
         }
 
-        public List<Token> ToTokens(SortedDictionary<int, string> vocabReverse)
+        public void ToTokens(SortedDictionary<int, string> vocabReverse, List<Token> tokens, int offset)
         {
-            List<Token> tokens = new(SymbolsCount);
             int index = 0;
 
             for (int i = 0; i < SymbolsCount; i++)
             {
                 int endIndex = index + _symbols[i].Len;
-                tokens.Add(new Token(_symbols[i].C, vocabReverse[_symbols[i].C], (index, _symbols[i].Len)));
+                tokens.Add(new Token(_symbols[i].C, vocabReverse[_symbols[i].C], (index + offset, _symbols[i].Len)));
                 index += _symbols[i].Len;
             }
-
-            return tokens;
         }
     }
 }

src/Microsoft.ML.Tokenizers/Normalizer/LowerCaseNormalizer.cs

@@ -3,6 +3,8 @@
 // See the LICENSE file in the project root for more information.
 
 using System;
+using System.Buffers;
+using System.Diagnostics;
 
 namespace Microsoft.ML.Tokenizers
 {
@@ -22,5 +24,27 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="original">The original string to normalize to lowercase form.</param>
         /// <returns>The lower-cased normalized string.</returns>
         public override string Normalize(string original) => original.ToLowerInvariant();
+
+        /// <summary>
+        /// Lowercase the original string.
+        /// </summary>
+        /// <param name="original">The original string to normalize to lowercase form.</param>
+        /// <returns>The lower-cased normalized string.</returns>
+        public override string Normalize(ReadOnlySpan<char> original)
+        {
+            if (original.IsEmpty)
+            {
+                return string.Empty;
+            }
+
+            char[] arrayPoolArray = ArrayPool<char>.Shared.Rent(original.Length);
+
+            int length = original.ToLowerInvariant(arrayPoolArray);
+            Debug.Assert(length == original.Length);
+
+            string result = new string(arrayPoolArray, 0, length);
+            ArrayPool<char>.Shared.Return(arrayPoolArray);
+            return result;
+        }
     }
 }

src/Microsoft.ML.Tokenizers/Normalizer/Normalizer.cs

@@ -17,5 +17,12 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="original">The original string to normalize.</param>
         /// <returns>The normalized string.</returns>
         public abstract string Normalize(string original);
+
+        /// <summary>
+        /// Process the original string to modify it and obtain a normalized string.
+        /// </summary>
+        /// <param name="original">The original string to normalize.</param>
+        /// <returns>The normalized string.</returns>
+        public abstract string Normalize(ReadOnlySpan<char> original);
     }
 }

src/Microsoft.ML.Tokenizers/Normalizer/SentencePieceNormalizer.cs

@@ -10,14 +10,14 @@ namespace Microsoft.ML.Tokenizers
     /// <summary>
     /// Normalize the string to lowercase form before processing it with the tokenizer.
     /// </summary>
-    public sealed class LlamaNormalizer : Normalizer
+    public sealed class SentencePieceNormalizer : Normalizer
     {
         internal const char DummyPrefix = '\u2581'; // '▁' (LOWER ONE EIGHT BLOCK)
 
         /// <summary>
         /// Creates a LowerCaseNormalizer object.
         /// </summary>
-        public LlamaNormalizer(bool removeExtraWhiteSpaces, bool addDummyPrefix, bool escapeWhiteSpaces, bool treatWhitespaceAsSuffix)
+        public SentencePieceNormalizer(bool removeExtraWhiteSpaces, bool addDummyPrefix, bool escapeWhiteSpaces, bool treatWhitespaceAsSuffix)
         {
             RemoveExtraWhiteSpaces = removeExtraWhiteSpaces;
             AddDummyPrefix = addDummyPrefix;
@@ -40,7 +40,7 @@ namespace Microsoft.ML.Tokenizers
         public bool TreatWhitespaceAsSuffix { get; }
 
         /// <summary>
-        /// Normalize the original string according to SentencePiece normalization with Llama model.
+        /// Normalize the original string according to SentencePiece normalization.
         /// </summary>
         /// <param name="original">The original string to normalize.</param>
         /// <returns>The normalized string.</returns>
@@ -51,6 +51,16 @@ namespace Microsoft.ML.Tokenizers
                 return string.Empty;
             }
 
+            return Normalize(original.AsSpan());
+        }
+
+        /// <summary>
+        /// Normalize the original string according to SentencePiece normalization.
+        /// </summary>
+        /// <param name="original">The original string to normalize.</param>
+        /// <returns>The normalized string.</returns>
+        public override string Normalize(ReadOnlySpan<char> original)
+        {
             int startIndex = 0;
             int endIndex = original.Length - 1;
 

src/Microsoft.ML.Tokenizers/Normalizer/UpperCaseNormalizer.cs

@@ -3,6 +3,8 @@
 // See the LICENSE file in the project root for more information.
 
 using System;
+using System.Buffers;
+using System.Diagnostics;
 
 namespace Microsoft.ML.Tokenizers
 {
@@ -22,5 +24,27 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="original">The original string to normalize to uppercase form.</param>
         /// <returns>The upper-cased normalized string.</returns>
         public override string Normalize(string original) => original.ToUpperInvariant();
+
+        /// <summary>
+        /// Uppercase the original string.
+        /// </summary>
+        /// <param name="original">The original string to normalize to uppercase form.</param>
+        /// <returns>The upper-cased normalized string.</returns>
+        public override string Normalize(ReadOnlySpan<char> original)
+        {
+            if (original.IsEmpty)
+            {
+                return string.Empty;
+            }
+
+            char[] arrayPoolArray = ArrayPool<char>.Shared.Rent(original.Length);
+
+            int length = original.ToUpperInvariant(arrayPoolArray);
+            Debug.Assert(length == original.Length);
+
+            string result = new string(arrayPoolArray, 0, length);
+            ArrayPool<char>.Shared.Return(arrayPoolArray);
+            return result;
+        }
     }
 }

src/Microsoft.ML.Tokenizers/PreTokenizer/PreTokenizer.cs

@@ -3,66 +3,12 @@
 // See the LICENSE file in the project root for more information.
 
 using System;
+using System.Buffers;
 using System.Collections.Generic;
 using System.Text.RegularExpressions;
 
 namespace Microsoft.ML.Tokenizers
 {
-    /// <summary>
-    /// This Split contains the underlying split token as well as its offsets
-    /// in the original string. These offsets are in the `original` referential.
-    /// It also contains any `Token` associated to the current split.
-    /// </summary>
-    public struct Split : IEquatable<Split>
-    {
-        private readonly string? _originalString;
-        private string? _tokenString;
-
-        /// <summary>
-        /// Gets the underlying split token. Each SubString is represented by a token
-        /// and in the end we might be carrying a lot of SubString representing various parts of the
-        /// original input string.
-        /// </summary>
-        public string TokenString => _tokenString ??= _originalString!.Substring(Offset.Index, Offset.Length);
-
-        /// <summary>
-        /// Gets the underlying split token as a span.
-        /// </summary>
-        public ReadOnlySpan<char> TokenSpan => _tokenString is string s ? s.AsSpan() : _originalString.AsSpan(Offset.Index, Offset.Length);
-
-        /// <summary>
-        /// Returns the offset mapping to the original string
-        /// </summary>
-        public (int Index, int Length) Offset { get; }
-
-        /// <summary>
-        /// create a Split object using the token and the offset
-        /// </summary>
-        /// <param name="token">The token string</param>
-        /// <param name="offset">The offset mapping to the original string</param>
-        public Split(string token, (int Index, int Length) offset)
-        {
-            _tokenString = token;
-            Offset = offset;
-        }
-
-        internal Split(string originalString, string? token, (int Index, int Length) offset)
-        {
-            _originalString = originalString;
-            _tokenString = token;
-            Offset = offset;
-        }
-
-        /// <summary>
-        /// Indicates whether the current Split object is equal to another Split object.
-        /// </summary>
-        /// <param name="other">The Split object to compare with the current object.</param>
-        public bool Equals(Split other) =>
-            (_originalString == other._originalString || TokenString == other.TokenString) &&
-            Offset.Index == other.Offset.Index &&
-            Offset.Length == other.Offset.Length;
-    }
-
     /// <summary>
     /// Base class for all pre-tokenizers classes.
     /// The PreTokenizer is in charge of doing the pre-segmentation step.
@@ -70,23 +16,54 @@ namespace Microsoft.ML.Tokenizers
     public abstract class PreTokenizer
     {
         /// <summary>
-        /// Splits the given string in multiple substrings at the word boundary, keeping track of the offsets of said substrings from the original string.
+        /// Get the offsets and lengths of the tokens relative to the <paramref name="text"/>.
         /// </summary>
         /// <param name="text">The string to split into tokens.</param>
-        /// <returns>The list of the splits containing the tokens and the token's offsets to the original string.</returns>
-        public abstract IEnumerable<Split> PreTokenize(string text);
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public abstract IEnumerable<(int Offset, int Length)> PreTokenize(string text);
 
-        internal static IEnumerable<Split> SplitText(string text, Regex regex)
+        /// <summary>
+        /// Get the offsets and lengths of the tokens relative to the original string.
+        /// </summary>
+        /// <param name="text">The character span to split into tokens.</param>
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public abstract IEnumerable<(int Offset, int Length)> PreTokenize(ReadOnlySpan<char> text);
+
+        internal static IEnumerable<(int Offset, int Length)> SplitText(string text, Regex regex)
         {
             (int Offset, int Length) match;
             int beginning = 0;
             while (TryGetMatch(regex, text, beginning, text.Length - beginning, out match))
             {
-                yield return new Split(text, null, (match.Offset, match.Length));
+                yield return (match.Offset, match.Length);
                 beginning = match.Offset + match.Length;
             }
         }
 
+        internal static IEnumerable<(int Offset, int Length)> SplitText(ReadOnlySpan<char> text, Regex regex)
+        {
+#if NET7_0_OR_GREATER
+            char[] buffer = ArrayPool<char>.Shared.Rent(text.Length);
+            text.CopyTo(buffer);
+            return SplitText(buffer, regex, text.Length);
+
+            static IEnumerable<(int Offset, int Length)> SplitText(char[] text, Regex regex, int textLength)
+            {
+                (int Offset, int Length) match;
+                int beginning = 0;
+                while (TryGetMatch(regex, text, beginning, textLength - beginning, out match))
+                {
+                    yield return (match.Offset, match.Length);
+                    beginning = match.Offset + match.Length;
+                }
+
+                ArrayPool<char>.Shared.Return(text);
+            }
+#else
+            return SplitText(text.ToString(), regex);
+#endif // NET7_0_OR_GREATER
+        }
+
         internal static bool TryGetMatch(Regex regex, string text, int beginning, int length, out (int offset, int length) match)
         {
 #if NET7_0_OR_GREATER
@@ -106,5 +83,18 @@ namespace Microsoft.ML.Tokenizers
             match = default;
             return false;
         }
+
+#if NET7_0_OR_GREATER
+        internal static bool TryGetMatch(Regex regex, scoped ReadOnlySpan<char> text, int beginning, int length, out (int offset, int length) match)
+        {
+            foreach (ValueMatch m in regex.EnumerateMatches(text.Slice(beginning, length)))
+            {
+                match = (beginning + m.Index, m.Length);
+                return true;
+            }
+            match = default;
+            return false;
+        }
+#endif // NET7_0_OR_GREATER
     }
 }

src/Microsoft.ML.Tokenizers/PreTokenizer/Roberta.cs

@@ -18,15 +18,30 @@ namespace Microsoft.ML.Tokenizers
         public static RobertaPreTokenizer Instance { get; } = new RobertaPreTokenizer();
 
         /// <summary>
-        /// Splits the given string in multiple substrings at the word boundary, keeping track of the offsets of said substrings from the original string.
+        /// Get the offsets and lengths of the tokens relative to the <paramref name="text"/>.
         /// </summary>
         /// <param name="text">The string to split into tokens.</param>
-        /// <returns>The list of the splits containing the tokens and the token's offsets to the original string.</returns>
-        public override IEnumerable<Split> PreTokenize(string text)
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public override IEnumerable<(int Offset, int Length)> PreTokenize(string text)
         {
             if (string.IsNullOrEmpty(text))
             {
-                return Array.Empty<Split>();
+                return [];
+            }
+
+            return SplitText(text, Tiktoken.P50kBaseRegex());
+        }
+
+        /// <summary>
+        /// Get the offsets and lengths of the tokens relative to the <paramref name="text"/>.
+        /// </summary>
+        /// <param name="text">The string to split into tokens.</param>
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public override IEnumerable<(int Offset, int Length)> PreTokenize(ReadOnlySpan<char> text)
+        {
+            if (text.IsEmpty)
+            {
+                return [];
             }
 
             return SplitText(text, Tiktoken.P50kBaseRegex());

src/Microsoft.ML.Tokenizers/PreTokenizer/SentencePiecePreTokenizer.cs

@@ -1,35 +0,0 @@
-// Licensed to the .NET Foundation under one or more agreements.
-// The .NET Foundation licenses this file to you under the MIT license.
-// See the LICENSE file in the project root for more information.
-
-using System;
-using System.Collections.Generic;
-
-namespace Microsoft.ML.Tokenizers
-{
-    /// <summary>
-    /// The pre-tokenizer for SentencePiece tokenizers.
-    /// </summary>
-    internal sealed partial class SentencePiecePreTokenizer : PreTokenizer
-    {
-        /// <summary>
-        /// Gets a singleton instance of the Roberta pre-tokenizer..
-        /// </summary>
-        public static SentencePiecePreTokenizer Instance { get; } = new SentencePiecePreTokenizer();
-
-        /// <summary>
-        /// Return the whole text as one chunk.
-        /// </summary>
-        /// <param name="text">The string to split into tokens.</param>
-        /// <returns>The original string as one chunk.</returns>
-        public override IEnumerable<Split> PreTokenize(string text)
-        {
-            if (string.IsNullOrEmpty(text))
-            {
-                yield break;
-            }
-
-            yield return new Split(text, (0, text.Length));
-        }
-    }
-}

src/Microsoft.ML.Tokenizers/PreTokenizer/TiktokenPreTokenizer.cs

@@ -3,6 +3,7 @@
 // See the LICENSE file in the project root for more information.
 
 using System;
+using System.Buffers;
 using System.Collections.Generic;
 using System.Linq;
 using System.Text.RegularExpressions;
@@ -39,20 +40,20 @@ namespace Microsoft.ML.Tokenizers
         }
 
         /// <summary>
-        /// Splits the given string in multiple substrings at the word boundary, keeping track of the offsets of said substrings from the original string.
+        /// Get the offsets and lengths of the tokens relative to the <paramref name="text"/>.
         /// </summary>
         /// <param name="text">The string to split into tokens.</param>
-        /// <returns>The list of the splits containing the tokens and the token's offsets to the original string.</returns>
-        public override IEnumerable<Split> PreTokenize(string text)
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public override IEnumerable<(int Offset, int Length)> PreTokenize(string text)
         {
             if (string.IsNullOrEmpty(text))
             {
-                return Array.Empty<Split>();
+                return [];
             }
 
             return SplitText(text, _regex, _specialTokensRegex);
 
-            static IEnumerable<Split> SplitText(string text, Regex regex, Regex? specialTokensRegex)
+            static IEnumerable<(int Offset, int Length)> SplitText(string text, Regex regex, Regex? specialTokensRegex)
             {
                 (int Offset, int Length) match;
                 int beginning = 0;
@@ -69,21 +70,77 @@ namespace Microsoft.ML.Tokenizers
 
                         while (TryGetMatch(regex, text, beginning, specialMatch.Offset - beginning, out match))
                         {
-                            yield return new Split(text, null, (match.Offset, match.Length));
+                            yield return (match.Offset, match.Length);
                             beginning = match.Offset + match.Length;
                         }
 
-                        yield return new Split(text, null, (specialMatch.Offset, specialMatch.Length));
+                        yield return (specialMatch.Offset, specialMatch.Length);
                         beginning = specialMatch.Offset + specialMatch.Length;
                     }
                 }
 
                 while (TryGetMatch(regex, text, beginning, text.Length - beginning, out match))
                 {
-                    yield return new Split(text, null, (match.Offset, match.Length));
+                    yield return (match.Offset, match.Length);
                     beginning = match.Length + match.Offset;
                 }
             }
         }
+
+        /// <summary>
+        /// Get the offsets and lengths of the tokens relative to the <paramref name="text"/>.
+        /// </summary>
+        /// <param name="text">The string to split into tokens.</param>
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public override IEnumerable<(int Offset, int Length)> PreTokenize(ReadOnlySpan<char> text)
+        {
+            if (text.IsEmpty)
+            {
+                return [];
+            }
+
+#if NET7_0_OR_GREATER
+            char[] buffer = ArrayPool<char>.Shared.Rent(text.Length);
+            text.CopyTo(buffer);
+            return SplitText(buffer, _regex, _specialTokensRegex, text.Length);
+
+            static IEnumerable<(int Offset, int Length)> SplitText(char[] text, Regex regex, Regex? specialTokensRegex, int textLength)
+            {
+                (int Offset, int Length) match;
+                int beginning = 0;
+
+                if (specialTokensRegex is not null)
+                {
+                    while (true)
+                    {
+                        (int Offset, int Length) specialMatch;
+                        if (!TryGetMatch(specialTokensRegex, text.AsSpan(), beginning, textLength - beginning, out specialMatch))
+                        {
+                            break;
+                        }
+
+                        while (TryGetMatch(regex, text.AsSpan(), beginning, specialMatch.Offset - beginning, out match))
+                        {
+                            yield return (match.Offset, match.Length);
+                            beginning = match.Offset + match.Length;
+                        }
+
+                        yield return (specialMatch.Offset, specialMatch.Length);
+                        beginning = specialMatch.Offset + specialMatch.Length;
+                    }
+                }
+
+                while (TryGetMatch(regex, text.AsSpan(), beginning, textLength - beginning, out match))
+                {
+                    yield return (match.Offset, match.Length);
+                    beginning = match.Length + match.Offset;
+                }
+
+                ArrayPool<char>.Shared.Return(text);
+            }
+#else
+            return PreTokenize(text.ToString());
+#endif // NET7_0_OR_GREATER
+        }
     }
 }

src/Microsoft.ML.Tokenizers/PreTokenizer/Whitespace.cs

@@ -29,15 +29,30 @@ namespace Microsoft.ML.Tokenizers
 #endif
 
         /// <summary>
-        /// Splits the given string in multiple substrings at the word boundary, keeping track of the offsets of said substrings from the original string.
+        /// Get the offsets and lengths of the tokens relative to the <paramref name="text"/>.
         /// </summary>
         /// <param name="text">The string to split into tokens.</param>
-        /// <returns>The list of the splits containing the tokens and the token's offsets to the original string.</returns>
-        public override IEnumerable<Split> PreTokenize(string text)
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public override IEnumerable<(int Offset, int Length)> PreTokenize(string text)
         {
             if (string.IsNullOrEmpty(text))
             {
-                return Array.Empty<Split>();
+                return [];
+            }
+
+            return SplitText(text, PretokenizeRegex());
+        }
+
+        /// <summary>
+        /// Get the offsets and lengths of the tokens relative to the <paramref name="text"/>.
+        /// </summary>
+        /// <param name="text">The string to split into tokens.</param>
+        /// <returns>The offsets and lengths of the tokens, expressed as pairs, are relative to the original string.</returns>
+        public override IEnumerable<(int Offset, int Length)> PreTokenize(ReadOnlySpan<char> text)
+        {
+            if (text.IsEmpty)
+            {
+                return [];
             }
 
             return SplitText(text, PretokenizeRegex());

src/Microsoft.ML.Tokenizers/Token.cs

@@ -12,7 +12,7 @@ namespace Microsoft.ML.Tokenizers
     /// Represent the token produced from the tokenization process containing the token substring,
     /// the id associated to the token substring, and the offset mapping to the original string.
     /// </summary>
-    public sealed class Token
+    public readonly struct Token
     {
         /// <summary>
         /// Gets the Id value associated to the token.
@@ -22,12 +22,12 @@ namespace Microsoft.ML.Tokenizers
         /// <summary>
         /// Gets the token string value.
         /// </summary>
-        public string Value { get; set; }
+        public string Value { get; }
 
         /// <summary>
         /// Gets the offset mapping to the original string.
         /// </summary>
-        public (int Index, int Length) Offset { get; internal set; }
+        public (int Index, int Length) Offset { get; }
 
         /// <summary>
         /// Construct a new Token object using the token value, Id, and the offset mapping to the original string.

src/Microsoft.ML.Tokenizers/Tokenizer.cs

@@ -8,6 +8,7 @@ using System.Collections.Generic;
 using System.Diagnostics;
 using System.IO;
 using System.Linq;
+using System.Text;
 using System.Text.RegularExpressions;
 using System.Threading;
 using System.Threading.Tasks;
@@ -15,263 +16,279 @@ using System.Threading.Tasks;
 namespace Microsoft.ML.Tokenizers
 {
     /// <summary>
-    /// A Tokenizer works as a pipeline. It processes some raw text as input and outputs a EncodingResult object.
+    /// serves as an abstraction for concrete tokenizers, enabling the encoding of text into tokens and IDs, as well as the decoding of IDs back into text.
     /// </summary>
-    public partial class Tokenizer
+    public abstract class Tokenizer
     {
         /// <summary>
-        /// Create a new Tokenizer object.
+        /// Gets the PreTokenizer used by the Tokenizer.
         /// </summary>
-        /// <param name="model">The Model in use by the Tokenizer.</param>
-        /// <param name="preTokenizer">The optional PreTokenizer in use by the Tokenizer. WhiteSpace PreTokenizer will be used if this parameter is null.</param>
-        /// <param name="normalizer">The optional Normalizer in use by the Tokenizer.</param>
-        public Tokenizer(Model model, PreTokenizer? preTokenizer = null, Normalizer? normalizer = null)
-        {
-            Model = model;
-            PreTokenizer = preTokenizer ?? WhiteSpace.Instance;
-            Normalizer = normalizer;
-        }
+        public virtual PreTokenizer? PreTokenizer => null;
 
         /// <summary>
-        /// Gets the Model in use by the Tokenizer.
+        /// Gets the Normalizer in use by the Tokenizer.
         /// </summary>
-        public Model Model { get; }
+        public virtual Normalizer? Normalizer => null;
 
         /// <summary>
-        /// Gets or sets the PreTokenizer used by the Tokenizer.
-        /// </summary>
-        public PreTokenizer PreTokenizer { get; }
-
-        /// <summary>
-        /// Gets or sets the Normalizer in use by the Tokenizer.
-        /// </summary>
-        public Normalizer? Normalizer { get; }
-
-        /// <summary>
-        /// Encodes input text to object has the tokens list, tokens Ids, tokens offset mapping.
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <returns>The tokenization result includes the tokens list, tokens Ids, tokens offset mapping.</returns>
-        public EncodingResult Encode(string text)
-        {
-            if (text is null)
-            {
-                throw new ArgumentNullException(nameof(text));
-            }
-
-            string normalized = Normalizer is null ? text : Normalizer.Normalize(text);
-            bool offsetsMappedToOriginal = true;
-
-            EncodingResult encoding = new(text, normalized, PreTokenizer.PreTokenize(normalized), offsetsMappedToOriginal);
-
-            foreach (Split split in encoding.Splits)
-            {
-                IReadOnlyList<Token> tokens = Model.Encode(split.TokenString.AsSpan());
-                foreach (Token token in tokens)
-                {
-                    token.Offset = (token.Offset.Index + split.Offset.Index, token.Offset.Length);
-                }
-
-                encoding.AddTokens(tokens);
-            }
-
-            return encoding;
-        }
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public virtual IReadOnlyList<Token> Encode(string text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true) => Encode(text.AsSpan(), out normalizedString, considerPreTokenization, considerNormalization);
 
         /// <summary>
-        /// Encodes input text to tokens Ids.
+        /// Encodes input text a list of <see cref="Token" />s with string value of the token, id, and offset.
         /// </summary>
         /// <param name="text">The text to encode.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The tokenization result includes a list of <see cref="Token" />s with string value of the token, id, and offset.</returns>
+        public abstract IReadOnlyList<Token> Encode(ReadOnlySpan<char> text, out string? normalizedString, bool considerPreTokenization = true, bool considerNormalization = true);
+
+        /// <summary>
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
         /// <returns>The list of encoded Ids.</returns>
-        public IReadOnlyList<int> EncodeToIds(string text)
-        {
-            if (text is null)
-            {
-                throw new ArgumentNullException(nameof(text));
-            }
-
-            string normalized = Normalizer is not null ? Normalizer.Normalize(text) : text;
-            List<int> idsList = new();
-
-            foreach (Split split in PreTokenizer.PreTokenize(normalized))
-            {
-                Model.EncodeToIds(split.TokenSpan, idsList, out _);
-            }
-
-            return idsList;
-        }
+        public virtual IReadOnlyList<int> EncodeToIds(string text, bool considerPreTokenization = true, bool considerNormalization = true) => EncodeToIds(text.AsSpan(), considerPreTokenization, considerNormalization);
 
         /// <summary>
-        /// Encodes input text to tokens Ids up to maximum number of tokens.
+        /// Encodes input text to token Ids.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public abstract IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true);
+
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
         /// </summary>
         /// <param name="text">The text to encode.</param>
         /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
-        /// <param name="processedText">If the tokenizer's normalization is enabled, the input text will be represented in its normalization form; otherwise, it will remain unchanged as the input text.</param>
+        /// <param name="normalizedText">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
         /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
         /// <returns>The list of encoded Ids.</returns>
-        public IReadOnlyList<int> EncodeToIds(string text, int maxTokenCount, out string processedText, out int textLength)
-        {
-            processedText = text;
-            textLength = 0;
+        public virtual IReadOnlyList<int> EncodeToIds(string text, int maxTokenCount, out string? normalizedText, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+            => EncodeToIds(text.AsSpan(), maxTokenCount, out normalizedText, out textLength, considerPreTokenization, considerNormalization);
 
-            if (text is null)
-            {
-                throw new ArgumentNullException(nameof(text));
-            }
-
-            if (maxTokenCount <= 0)
-            {
-                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The maximum number of tokens must be greater than 0.");
-            }
-
-            if (Normalizer is not null)
-            {
-                processedText = Normalizer.Normalize(text);
-            }
-
-            List<int> idsList = new();
-
-            foreach (Split split in PreTokenizer.PreTokenize(processedText))
-            {
-                Model.EncodeToIds(split.TokenSpan, idsList, out int length, maxTokenCount - idsList.Count);
-                if (length < split.Offset.Length || idsList.Count >= maxTokenCount)
-                {
-                    break;
-                }
-            }
-
-            return idsList;
-        }
+        /// <summary>
+        /// Encodes input text to token Ids up to maximum number of tokens.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum number of tokens to encode.</param>
+        /// <param name="normalizedText">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="textLength">The length of the text that encompasses the maximum encoded tokens.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The list of encoded Ids.</returns>
+        public abstract IReadOnlyList<int> EncodeToIds(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedText, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true);
 
         /// <summary>
         /// Get the number of tokens that the input text will be encoded to.
         /// </summary>
         /// <param name="text">The text to encode.</param>
-        /// <returns>The number of tokens Ids that the input text will be encoded to.</returns>
-        /// <exception cref="ArgumentNullException">The input text is null.</exception>
-        /// <exception cref="ArgumentException">Unable to encode the text.</exception>
-        public int CountTokens(string text)
-        {
-            if (text is null)
-            {
-                throw new ArgumentNullException(nameof(text));
-            }
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public virtual int CountTokens(string text, bool considerPreTokenization = true, bool considerNormalization = true)
+            => CountTokens(text.AsSpan(), considerPreTokenization, considerNormalization);
 
-            string normalized = Normalizer is not null ? Normalizer.Normalize(text) : text;
-
-            int idsCount = 0;
-            foreach (Split split in PreTokenizer.PreTokenize(normalized))
-            {
-                idsCount += Model.CountTokens(split.TokenSpan, out _);
-            }
-
-            return idsCount;
-        }
+        /// <summary>
+        /// Get the number of tokens that the input text will be encoded to.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>The number of token Ids that the input text will be encoded to.</returns>
+        public abstract int CountTokens(ReadOnlySpan<char> text, bool considerPreTokenization = true, bool considerNormalization = true);
 
         /// <summary>
         /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
         /// </summary>
         /// <param name="text">The text to encode.</param>
         /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
-        /// <param name="processedText">If the tokenizer's normalization is enabled, the input text will be represented in its normalization form; otherwise, it will remain unchanged as the input text.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
         /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
         /// <returns>
         /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
-        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely, if all tokens fit, the result will be length of the <paramref name="processedText"/>.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
         /// </returns>
-        /// <exception cref="ArgumentNullException">The input text is null.</exception>
-        /// <exception cref="ArgumentOutOfRangeException">The maximum token count must be greater than 0.</exception>
-        public int IndexOfTokenCount(string text, int maxTokenCount, out string processedText, out int tokenCount)
-            => IndexOf(text, maxTokenCount, out processedText, out tokenCount);
+        public virtual int IndexOfTokenCount(string text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => IndexOfTokenCount(text.AsSpan(), maxTokenCount, out normalizedString, out tokenCount, considerPreTokenization, considerNormalization);
+
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the start within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="normalizedString">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index immediately following the last character to be included. In cases where no tokens fit, the result will be 0; conversely,
+        /// if all tokens fit, the result will be length of the text or the <paramref name="normalizedString"/> if the normalization is enabled.
+        /// </returns>
+        public abstract int IndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? normalizedString, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true);
 
         /// <summary>
         /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
         /// </summary>
         /// <param name="text">The text to encode.</param>
         /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
-        /// <param name="processedText">If the tokenizer's normalization is enabled, the input text will be represented in its normalization form; otherwise, it will remain unchanged as the input text.</param>
+        /// <param name="processedText">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
         /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
         /// <returns>
         /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
         /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the <paramref name="processedText"/>; conversely, if all tokens fit, the result will be 0.
         /// </returns>
-        /// <exception cref="ArgumentNullException">The input text is null.</exception>
-        /// <exception cref="ArgumentOutOfRangeException">The maximum token count must be greater than 0.</exception>
-        /// <remarks>
-        /// If the whole text can be encoded within the token limit, the returned index will be 0.
-        /// </remarks>
-        public int LastIndexOfTokenCount(string text, int maxTokenCount, out string processedText, out int tokenCount)
-            => LastIndexOf(text, maxTokenCount, out processedText, out tokenCount);
+        public virtual int LastIndexOfTokenCount(string text, int maxTokenCount, out string? processedText, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true)
+            => LastIndexOfTokenCount(text.AsSpan(), maxTokenCount, out processedText, out tokenCount, considerPreTokenization, considerNormalization);
 
-        private int IndexOf(string text, int maxTokenCount, out string processedText, out int tokenCount)
+        /// <summary>
+        /// Find the index of the maximum encoding capacity from the end within the text without surpassing the token limit.
+        /// </summary>
+        /// <param name="text">The text to encode.</param>
+        /// <param name="maxTokenCount">The maximum token count to limit the encoding capacity.</param>
+        /// <param name="processedText">If the tokenizer's normalization is enabled or <paramRef name="considerNormalization" /> is false, this will be set to <paramRef name="text" /> in its normalized form; otherwise, this value will be set to null.</param>
+        /// <param name="tokenCount">The token count can be generated which should be smaller than the maximum token count.</param>
+        /// <param name="considerPreTokenization">Indicate whether to consider pre-tokenization before tokenization.</param>
+        /// <param name="considerNormalization">Indicate whether to consider normalization before tokenization.</param>
+        /// <returns>
+        /// The start index of the maximum encoding capacity within the processed text without surpassing the token limit.
+        /// It represents the index at the first character to be included. In cases where no tokens fit, the result will be length of the <paramref name="processedText"/>; conversely, if all tokens fit, the result will be 0.
+        /// </returns>
+        public abstract int LastIndexOfTokenCount(ReadOnlySpan<char> text, int maxTokenCount, out string? processedText, out int tokenCount, bool considerPreTokenization = true, bool considerNormalization = true);
+
+        /// <summary>
+        /// Map the token to encoded Id.
+        /// </summary>
+        /// <param name="token">The token to map to the Id.</param>
+        /// <returns>The mapped Id of the token.</returns>
+        public virtual int? MapTokenToId(string token)
         {
-            if (text is null)
+            if (token is null)
             {
-                throw new ArgumentNullException(nameof(text));
+                throw new ArgumentNullException(nameof(token));
             }
 
-            if (maxTokenCount <= 0)
-            {
-                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The max token count must be greater than 0.");
-            }
-
-            processedText = Normalizer is not null ? Normalizer.Normalize(text) : text;
-            tokenCount = 0;
-
-            IEnumerable<Split> splits = PreTokenizer.PreTokenize(processedText);
-            foreach (Split split in splits)
-            {
-                tokenCount += Model.CountTokens(split.TokenSpan, out int textLength, maxTokenCount - tokenCount);
-                if (textLength < split.Offset.Length || tokenCount >= maxTokenCount)
-                {
-                    return split.Offset.Index + textLength;
-                }
-            }
-
-            return processedText.Length;
+            return MapTokenToId(token.AsSpan());
         }
 
-        private int LastIndexOf(string text, int maxTokenCount, out string processedText, out int tokenCount)
-        {
-            if (text is null)
-            {
-                throw new ArgumentNullException(nameof(text));
-            }
-
-            if (maxTokenCount <= 0)
-            {
-                throw new ArgumentOutOfRangeException(nameof(maxTokenCount), "The max token count must be greater than 0.");
-            }
-
-            processedText = Normalizer is not null ? Normalizer.Normalize(text) : text;
-            tokenCount = 0;
-
-            IEnumerable<Split> splits = PreTokenizer.PreTokenize(processedText);
-            foreach (Split split in splits.Reverse())
-            {
-                tokenCount += Model.CountTokensFromEnd(split.TokenSpan, out int textIndex, maxTokenCount - tokenCount);
-                if (textIndex > 0 || tokenCount >= maxTokenCount)
-                {
-                    return split.Offset.Index + textIndex;
-                }
-            }
-
-            return 0;
-        }
+        /// <summary>
+        /// Map the token to encoded Id.
+        /// </summary>
+        /// <param name="token">The token to map to the Id.</param>
+        /// <returns>The mapped Id of the token.</returns>
+        public abstract int? MapTokenToId(ReadOnlySpan<char> token);
 
         /// <summary>
         /// Decodes the Id to the mapped token.
         /// </summary>
         /// <param name="id">The id to map to the token.</param>
         /// <returns>The decoded string or null if there is no token mapped to the input id.</returns>
-        public string? Decode(int id) => Model.MapIdToToken(id);
+        public abstract string? MapIdToToken(int id);
 
         /// <summary>
         /// Decode the given ids, back to a String.
         /// </summary>
         /// <param name="ids">The list of ids that we want to decode.</param>
         /// <returns>The decoded string.</returns>
-        public string? Decode(IEnumerable<int> ids) => Model.Decode(ids);
+        public virtual string? Decode(IEnumerable<int> ids)
+        {
+            if (ids is null)
+            {
+                throw new ArgumentNullException(nameof(ids));
+            }
+
+            ValueStringBuilder sb = new ValueStringBuilder();
+
+            foreach (int id in ids)
+            {
+                if (MapIdToToken(id) is string s)
+                {
+                    sb.Append(s);
+                }
+            }
+
+            return sb.ToString();
+        }
+
+        //
+        // Factory Methods
+        //
+
+        /// <summary>
+        /// Create a new Tiktoken tokenizer's object asynchronously.
+        /// </summary>
+        /// <param name="vocabStream">The stream to the BPE vocab file.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
+        /// <param name="specialTokens">The dictionary mapping special tokens to Ids.</param>
+        /// <param name="cacheSize">The size of the cache to use.</param>
+        /// <param name="cancellationToken"><see cref="CancellationToken"/> used to request cancellation of the operation.</param>
+        /// <returns>The tokenizer's object.</returns>
+        public static async Task<Tokenizer> CreateTiktokenAsync(
+                            Stream vocabStream,
+                            PreTokenizer? preTokenizer,
+                            Normalizer? normalizer,
+                            IReadOnlyDictionary<string, int>? specialTokens = null,
+                            int cacheSize = LruCache<int[]>.DefaultCacheSize,
+                            CancellationToken cancellationToken = default)
+        {
+            if (vocabStream is null)
+            {
+                throw new ArgumentNullException(nameof(vocabStream));
+            }
+
+            (Dictionary<ReadOnlyMemory<byte>, int> encoder, Dictionary<StringSpanOrdinalKey, (int Id, string Token)> vocab, Dictionary<int, ReadOnlyMemory<byte>> decoder) =
+                        await Tiktoken.LoadTiktokenBpeAsync(vocabStream, useAsync: true, cancellationToken).ConfigureAwait(false);
+
+            return new Tiktoken(encoder, decoder, vocab, preTokenizer, specialTokens, normalizer, cacheSize);
+        }
+
+        /// <summary>
+        /// Create a new Tiktoken tokenizer's object asynchronously.
+        /// </summary>
+        /// <param name="vocabFilePath">The BPE vocab file.</param>
+        /// <param name="preTokenizer">The pre-tokenizer to use.</param>
+        /// <param name="normalizer">The normalizer to use.</param>
+        /// <param name="specialTokensEncoder">The dictionary mapping special tokens to Ids.</param>
+        /// <param name="cacheSize">The size of the cache to use.</param>
+        /// <param name="cancellationToken"><see cref="CancellationToken"/> used to request cancellation of the operation.</param>
+        /// <returns>The tokenizer's object.</returns>
+        public static async Task<Tokenizer> CreateTiktokenAsync(
+                                string vocabFilePath,
+                                PreTokenizer? preTokenizer,
+                                Normalizer? normalizer,
+                                IReadOnlyDictionary<string, int>? specialTokensEncoder = null,
+                                int cacheSize = LruCache<int[]>.DefaultCacheSize,
+                                CancellationToken cancellationToken = default)
+        {
+            if (vocabFilePath is null)
+            {
+                throw new ArgumentNullException(nameof(vocabFilePath));
+            }
+
+            using Stream vocabStream = File.OpenRead(vocabFilePath);
+            return await CreateTiktokenAsync(vocabStream, preTokenizer, normalizer, specialTokensEncoder, cacheSize, cancellationToken).ConfigureAwait(false);
+        }
 
         /// <summary>
         /// Create a Tiktoken tokenizer based on model name and vocab file.
@@ -304,10 +321,11 @@ namespace Microsoft.ML.Tokenizers
                 }
             }
 
-            return new Tokenizer(
-                            new Tiktoken(vocabStream, tiktokenConfiguration.SpecialTokens, cacheSize),
-                            new TiktokenPreTokenizer(tiktokenConfiguration.Regex, tiktokenConfiguration.SpecialTokens),
-                            normalizer);
+            return new Tiktoken(vocabStream,
+                                new TiktokenPreTokenizer(tiktokenConfiguration.Regex, tiktokenConfiguration.SpecialTokens),
+                                tiktokenConfiguration.SpecialTokens,
+                                normalizer,
+                                cacheSize);
         }
 
         /// <summary>
@@ -343,10 +361,11 @@ namespace Microsoft.ML.Tokenizers
                 }
             }
 
-            return new Tokenizer(
-                            await Tiktoken.CreateAsync(vocabStream, tiktokenConfiguration.SpecialTokens, cacheSize, cancellationToken).ConfigureAwait(false),
-                            new TiktokenPreTokenizer(tiktokenConfiguration.Regex, tiktokenConfiguration.SpecialTokens),
-                            normalizer);
+            return await CreateTiktokenAsync(vocabStream,
+                                new TiktokenPreTokenizer(tiktokenConfiguration.Regex, tiktokenConfiguration.SpecialTokens),
+                                normalizer,
+                                tiktokenConfiguration.SpecialTokens,
+                                cacheSize, cancellationToken).ConfigureAwait(false);
         }
 
         /// <summary>
@@ -357,7 +376,7 @@ namespace Microsoft.ML.Tokenizers
         /// <param name="normalizer">To normalize the text before tokenization</param>
         /// <returns>The tokenizer</returns>
         public static Tokenizer CreateTiktokenForModel(string modelName, IReadOnlyDictionary<string, int>? extraSpecialTokens = null, Normalizer? normalizer = null)
-                        => Tiktoken.CreateTokenizerForModel(modelName, extraSpecialTokens, normalizer);
+                        => Tiktoken.CreateForModel(Tiktoken.GetModelEncoding(modelName), modelName, extraSpecialTokens, normalizer);
 
         /// <summary>
         /// Create tokenizer based on encoding name
@@ -395,7 +414,7 @@ namespace Microsoft.ML.Tokenizers
                 throw new ArgumentException($"The encoding name '{encodingName}' is not supported. The only supported encoding names are: {Tiktoken.Cl100kBaseEncodingName}, {Tiktoken.P50kBaseEncodingName}, {Tiktoken.P50kEditEncodingName}, and {Tiktoken.R50kBaseEncodingName}.", nameof(encodingName));
             }
 
-            return Tiktoken.CreateTokenizerForModel(modelEncoding, modelName: null, extraSpecialTokens, normalizer);
+            return Tiktoken.CreateForModel(modelEncoding, modelName: null, extraSpecialTokens, normalizer);
         }
 
         /// <summary>
@@ -427,16 +446,70 @@ namespace Microsoft.ML.Tokenizers
                 throw new ArgumentException($"Normalization '{modelProto.NormalizerSpec.Name}' is not supported.", nameof(modelProto));
             }
 
-            LlamaNormalizer normalizer = new(
+            SentencePieceNormalizer normalizer = new(
                                     modelProto.NormalizerSpec.RemoveExtraWhitespaces,
                                     modelProto.NormalizerSpec.AddDummyPrefix,
                                     modelProto.NormalizerSpec.EscapeWhitespaces,
                                     modelProto.TrainerSpec.TreatWhitespaceAsSuffix);
 
-            return new Tokenizer(
-                        new SentencePieceBpe(modelProto, addBeginOfSentence, addEndOfSentence),
-                        SentencePiecePreTokenizer.Instance,
-                        normalizer);
+            return new SentencePieceBpe(modelProto, addBeginOfSentence, addEndOfSentence);
+        }
+
+        internal static IEnumerable<(int Offset, int Length)>? InitializeForEncoding(
+                                                string? text,
+                                                ReadOnlySpan<char> textSpan,
+                                                bool considerPreTokenization,
+                                                bool considerNormalization,
+                                                Normalizer? normalizer,
+                                                PreTokenizer? preTokenizer,
+                                                out string? normalizedString,
+                                                out ReadOnlySpan<char> textSpanToEncode)
+        {
+            normalizedString = null;
+            IEnumerable<(int Offset, int Length)>? splits = null;
+
+            if (text is null)
+            {
+                if (considerNormalization && (normalizer is not null))
+                {
+                    normalizedString = normalizer.Normalize(textSpan.ToString());
+                    textSpanToEncode = normalizedString.AsSpan();
+                    if (considerPreTokenization && preTokenizer is not null)
+                    {
+                        splits = preTokenizer.PreTokenize(normalizedString);
+                    }
+                }
+                else
+                {
+                    textSpanToEncode = textSpan;
+                    if (considerPreTokenization && preTokenizer is not null)
+                    {
+                        splits = preTokenizer.PreTokenize(textSpan);
+                    }
+                }
+            }
+            else
+            {
+                if (considerNormalization && (normalizer is not null))
+                {
+                    normalizedString = normalizer.Normalize(text);
+                    textSpanToEncode = normalizedString.AsSpan();
+                    if (considerPreTokenization && preTokenizer is not null)
+                    {
+                        splits = preTokenizer.PreTokenize(normalizedString);
+                    }
+                }
+                else
+                {
+                    textSpanToEncode = text.AsSpan();
+                    if (considerPreTokenization && preTokenizer is not null)
+                    {
+                        splits = preTokenizer.PreTokenize(text);
+                    }
+                }
+            }
+
+            return splits;
         }
     }
 }

src/Microsoft.ML.Tokenizers/Utils/PriorityQueue.cs

@@ -71,6 +71,8 @@ namespace Microsoft.ML.Tokenizers
             return s;
         }
 
+        public void Clear() => _data.Clear();
+
         public bool IsConsistent()
         {
             // is the heap property true for all data?

src/Microsoft.ML.TorchSharp/Extensions/TokenizerExtensions.cs

@@ -26,12 +26,12 @@ namespace Microsoft.ML.TorchSharp.Extensions
                 // "https://dl.fbaipublicfiles.com/fairseq/gpt2_bpe/dict.txt"
                 Assembly assembly = typeof(TokenizerExtensions).Assembly;
 
-                EnglishRoberta model = new EnglishRoberta(
+                _instance = new EnglishRoberta(
                                             assembly.GetManifestResourceStream("encoder.json"),
                                             assembly.GetManifestResourceStream("vocab.bpe"),
-                                            assembly.GetManifestResourceStream("dict.txt"));
-                model.AddMaskSymbol();
-                _instance = new Tokenizer(model, new RobertaPreTokenizer());
+                                            assembly.GetManifestResourceStream("dict.txt"),
+                                            new RobertaPreTokenizer());
+                (_instance as EnglishRoberta).AddMaskSymbol();
             }
 
             return _instance;
@@ -40,7 +40,7 @@ namespace Microsoft.ML.TorchSharp.Extensions
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         internal static EnglishRoberta RobertaModel(this Tokenizer tokenizer)
         {
-            EnglishRoberta model = tokenizer.Model as EnglishRoberta;
+            EnglishRoberta model = tokenizer as EnglishRoberta;
             if (model is null)
             {
                 throw new InvalidOperationException($"The input tokenizer is not using the EnglishRoberta model.");
@@ -51,8 +51,7 @@ namespace Microsoft.ML.TorchSharp.Extensions
 
         internal static IReadOnlyList<int> EncodeToConverted(this Tokenizer tokenizer, string sentence)
         {
-            EncodingResult encoding = tokenizer.Encode(sentence);
-            return tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(encoding.Ids);
+            return tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(tokenizer.EncodeToIds(sentence));
         }
     }
 }

src/Microsoft.ML.TorchSharp/NasBert/NerTrainer.cs

@@ -167,16 +167,16 @@ namespace Microsoft.ML.TorchSharp.NasBert
                 Sentence1Getter(ref sentenceRom);
                 var sentence = sentenceRom.ToString();
                 Tensor t;
-                var encoding = Tokenizer.Encode(sentence);
+                IReadOnlyList<Token> encoding = Tokenizer.Encode(sentence, out string normalizedString);
 
-                if (target.Length != encoding.Tokens.Count)
+                if (target.Length != encoding.Count)
                 {
                     var targetIndex = 0;
-                    var targetEditor = VBufferEditor.Create(ref target, encoding.Tokens.Count);
+                    var targetEditor = VBufferEditor.Create(ref target, encoding.Count);
                     var newValues = targetEditor.Values;
-                    for (var i = 0; i < encoding.Tokens.Count; i++)
+                    for (var i = 0; i < encoding.Count; i++)
                     {
-                        if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
+                        if (NerTrainer.TokenStartsWithSpace(encoding[i].Value))
                         {
                             newValues[i] = target.GetItemOrDefault(++targetIndex);
                         }
@@ -187,7 +187,7 @@ namespace Microsoft.ML.TorchSharp.NasBert
                     }
                     target = targetEditor.Commit();
                 }
-                t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(encoding.Ids)).ToList(), device: Device);
+                t = torch.tensor((ZeroArray).Concat(Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(encoding.Select(t => t.Id).ToArray())).ToList(), device: Device);
 
                 if (t.NumberOfElements > 512)
                     t = t.slice(0, 0, 512, 1);
@@ -377,16 +377,16 @@ namespace Microsoft.ML.TorchSharp.NasBert
             private void CondenseOutput(ref VBuffer<UInt32> dst, string sentence, Tokenizer tokenizer, TensorCacher outputCacher)
             {
                 var pre = tokenizer.PreTokenizer.PreTokenize(sentence);
-                EncodingResult encoding = tokenizer.Encode(sentence);
+                IReadOnlyList<Token> encoding = tokenizer.Encode(sentence, out string normalizedString);
 
                 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++)
+                for (var i = 0; i < encoding.Count; i++)
                 {
-                    if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
+                    if (NerTrainer.TokenStartsWithSpace(encoding[i].Value))
                     {
                         targetIndex++;
                     }
@@ -398,9 +398,9 @@ namespace Microsoft.ML.TorchSharp.NasBert
 
                 newValues[targetIndex++] = (uint)prediction[0];
 
-                for (var i = 1; i < encoding.Tokens.Count; i++)
+                for (var i = 1; i < encoding.Count; i++)
                 {
-                    if (NerTrainer.TokenStartsWithSpace(encoding.Tokens[i]))
+                    if (NerTrainer.TokenStartsWithSpace(encoding[i].Value))
                     {
                         newValues[targetIndex++] = (uint)prediction[i];
                     }

src/Microsoft.ML.TorchSharp/Roberta/QATrainer.cs

@@ -401,9 +401,9 @@ namespace Microsoft.ML.TorchSharp.Roberta
                     answerIndexGetter(ref answerIndex);
 
                     var contextString = context.ToString();
-                    var contextTokens = Tokenizer.Encode(contextString);
-                    var contextToken = contextTokens.Tokens;
-                    var contextTokenId = Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(contextTokens.Ids);
+                    var contextTokens = Tokenizer.Encode(contextString, out string normalized);
+                    var contextToken = contextTokens.Select(t => t.Value).ToArray();
+                    var contextTokenId = Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(contextTokens.Select(t => t.Id).ToArray());
 
                     var mapping = AlignAnswerPosition(contextToken, contextString);
                     if (mapping == null)
@@ -437,7 +437,7 @@ namespace Microsoft.ML.TorchSharp.Roberta
 
             private Dictionary<int, int> AlignAnswerPosition(IReadOnlyList<string> tokens, string text)
             {
-                EnglishRoberta robertaModel = Tokenizer.Model as EnglishRoberta;
+                EnglishRoberta robertaModel = Tokenizer as EnglishRoberta;
                 Debug.Assert(robertaModel is not null);
 
                 var mapping = new Dictionary<int, int>();
@@ -854,9 +854,9 @@ namespace Microsoft.ML.TorchSharp.Roberta
                 contextGetter(ref context);
                 questionGetter(ref question);
 
-                var contextTokenId = _parent.Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(_parent.Tokenizer.Encode(context.ToString()).Ids);
+                var contextTokenId = _parent.Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(_parent.Tokenizer.EncodeToIds(context.ToString()));
 
-                var questionTokenId = _parent.Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(_parent.Tokenizer.Encode(question.ToString()).Ids);
+                var questionTokenId = _parent.Tokenizer.RobertaModel().ConvertIdsToOccurrenceRanks(_parent.Tokenizer.EncodeToIds(question.ToString()));
 
                 var srcTensor = torch.tensor((new[] { 0 /* InitToken */ }).Concat(questionTokenId).Concat(new[] { 2 /* SeparatorToken */ }).Concat(contextTokenId).ToList(), device: _parent.Device);
 

test/Microsoft.ML.Tokenizers.Tests/BpeTests.cs

@@ -248,28 +248,28 @@ namespace Microsoft.ML.Tokenizers.Tests
 
             try
             {
-                Bpe bpe = new Bpe(vocabFile, mergesFile, unknownToken, continuingSubwordPrefix, endOfWordSuffix, fuseUnknownToken);
-                Tokenizer tokenizer = new Tokenizer(bpe);
-                EncodingResult encoding = tokenizer.Encode(sentence);
+                Bpe bpe = new Bpe(vocabFile, mergesFile, unknownToken: unknownToken, continuingSubwordPrefix: continuingSubwordPrefix, endOfWordSuffix: endOfWordSuffix, fuseUnknownTokens: fuseUnknownToken);
+                Tokenizer tokenizer = bpe;
+                IReadOnlyList<Token> encoding = tokenizer.Encode(sentence, out _);
+                int[] encodingIds = encoding.Select(t => t.Id).ToArray();
                 IReadOnlyList<int> idsList = tokenizer.EncodeToIds(sentence);
 
-                Assert.Equal(expectedTokens.Length, encoding.Tokens.Count);
-                Assert.Equal(offsets.Length, encoding.Offsets.Count);
-                Assert.Equal(ids.Length, encoding.Ids.Count);
+                Assert.Equal(expectedTokens.Length, encoding.Count);
+                Assert.Equal(offsets.Length, encoding.Count);
+                Assert.Equal(ids.Length, encoding.Count);
                 Assert.Equal(ids.Length, idsList.Count);
                 Assert.Equal(ids.Length, tokenizer.CountTokens(sentence));
-                Assert.Equal(decodedTokens, tokenizer.Decode(encoding.Ids));
-                Assert.Equal(decodedTokensWithoutUnknownToken, bpe.Decode(encoding.Ids, considerSpecialTokens: false));
+                Assert.Equal(decodedTokens, tokenizer.Decode(encodingIds));
+                Assert.Equal(decodedTokensWithoutUnknownToken, bpe.Decode(encodingIds, considerSpecialTokens: false));
 
-                for (int i = 0; i < encoding.Tokens.Count; i++)
+                for (int i = 0; i < encoding.Count; i++)
                 {
-                    Assert.Equal(expectedTokens[i], encoding.Tokens[i]);
-                    Assert.Equal(offsets[i], encoding.Offsets[i]);
-                    Assert.Equal(ids[i], encoding.Ids[i]);
+                    Assert.Equal(expectedTokens[i], encoding[i].Value);
+                    Assert.Equal(offsets[i], encoding[i].Offset);
+                    Assert.Equal(ids[i], encoding[i].Id);
                     Assert.Equal(ids[i], idsList[i]);
-                    Assert.Equal(encoding.Tokens[i], tokenizer.Model.MapIdToToken(encoding.Ids[i]));
-                    Assert.Equal(encoding.Ids[i], tokenizer.Model.MapTokenToId(encoding.Tokens[i].AsSpan()));
-                    Assert.Equal(encoding.Tokens[i], tokenizer.Decode(encoding.Ids[i]));
+                    Assert.Equal(encoding[i].Value, tokenizer.MapIdToToken(encodingIds[i]));
+                    Assert.Equal(encodingIds[i], tokenizer.MapTokenToId(encoding[i].Value.AsSpan()));
                 }
             }
             finally
@@ -282,6 +282,41 @@ namespace Microsoft.ML.Tokenizers.Tests
             }
         }
 
+        private static Tokenizer? _gpt2Tokenizer = null;
+
+        private static Tokenizer GetGpt2Tokenizer()
+        {
+            if (_gpt2Tokenizer is null)
+            {
+                // "https://huggingface.co/openai-community/gpt2/raw/main/vocab.json";
+                // "https://huggingface.co/openai-community/gpt2/raw/main/merges.txt";
+                using Stream vocabStream = File.OpenRead(Path.Combine(@"Gpt-2", "vocab.json"));
+                using Stream mergesStream = File.OpenRead(Path.Combine(@"Gpt-2", "merges.txt"));
+
+                _gpt2Tokenizer = new Bpe(vocabStream, mergesStream);
+            }
+
+            return _gpt2Tokenizer;
+        }
+
+        [Fact]
+        public void TestGpt2Vocab()
+        {
+            Tokenizer tokenizer = GetGpt2Tokenizer();
+
+            string text = "The quick brown fox jumps over the lazy dog!";
+
+            IReadOnlyList<Token> encoding = tokenizer.Encode(text, out _);
+            IReadOnlyList<int> ids = tokenizer.EncodeToIds(text);
+
+            Assert.Equal(12, encoding.Count);
+            Assert.Equal(encoding.Select(t => t.Id).ToArray(), ids);
+            Assert.Equal(12, tokenizer.CountTokens(text));
+
+            TokenizerTests.TestTokenLimits(tokenizer);
+        }
+
+
         public static IEnumerable<object?[]> BpeTestData
         {
             get
@@ -290,55 +325,84 @@ namespace Microsoft.ML.Tokenizers.Tests
                 yield return new object?[]
                 {
                     "the brown fox jumped over the lazy dog!",
-                    new string[] {"the", "brown", "fox", "jumped", "over", "the", "lazy", "dog", "!"},
-                    new (int, int)[] {(0, 3), (4, 9), (10, 13), (14, 20), (21, 25), (26, 29), (30, 34), (35, 38), (38, 39)}
+                    new string[] { "the", "brown", "fox", "j", "umped", "over", "the", "l", "azy", "dog", "!" },
+                    new (int Index, int Length)[] { (0, 3), (4, 5), (10, 3), (14, 1), (15, 5), (21, 4), (26, 3), (30, 1), (31, 3), (35, 3), (38, 1) },
+                    new int[] { 1169, 33282, 12792, 73, 27073, 2502, 1169, 75, 12582, 9703, 0 }
                 };
                 yield return new object?[]
                 {
                     "he traveled to Egypt during the summer, the weather was hot and ammunition." ,
-                    new string[] {"he", "traveled", "to", "Egypt", "during", "the", "summer", ",", "the", "weather", "was", "hot", "and", "ammunition", "."},
-                    new (int, int)[] {(0, 2), (3, 11), (12, 14), (15, 20), (21, 27), (28, 31), (32, 38), (38, 39), (40, 43), (44, 51), (52, 55), (56, 59), (60, 63), (64, 74), (74, 75)}
+                    new string[] { "he", "travel", "ed", "to", "Egypt", "during", "the", "sum", "mer", ",", "the", "weather", "was", "hot", "and", "am", "munition", "." },
+                    new (int Index, int Length)[] { (0, 2), (3, 6), (9, 2), (12, 2), (15, 5), (21, 6), (28, 3), (32, 3), (35, 3), (38, 1), (40, 3), (44, 7), (52, 3), (56, 3), (60, 3), (64, 2), (66, 8), (74, 1) },
+                    new int[] { 258, 35927, 276, 1462, 39299, 42122, 1169, 16345, 647, 11, 1169, 23563, 9776, 8940, 392, 321, 12640, 13 }
                 };
                 yield return new object?[]
                 {
                     "She played many games and she felt exhausted afterward",
-                    new string[] {"She", "played", "many", "games", "and", "she", "felt", "exhausted", "afterward"},
-                    new (int, int)[] {(0, 3), (4, 10), (11, 15), (16, 21), (22, 25), (26, 29), (30, 34), (35, 44), (45, 54)}
+                    new string[] { "She", "played", "many", "games", "and", "she", "felt", "ex", "ha", "usted", "after", "ward" },
+                    new (int Index, int Length)[] { (0, 3), (4, 6), (11, 4), (16, 5), (22, 3), (26, 3), (30, 4), (35, 2), (37, 2), (39, 5), (45, 5), (50, 4) },
+                    new int[] { 3347, 21542, 21834, 19966, 392, 7091, 31985, 1069, 3099, 8459, 8499, 904 }
                 };
                 yield return new object?[]
                 {
                     "Hello, y'all! How are you 😁 ?",
-                    new string[] {"Hello", ",", "y", "'", "all", "!", "How", "are", "you", "[UNK]", "?"},
-                    new (int, int)[] {(0, 5), (5, 6), (7, 8), (8, 9), (9, 12), (12, 13), (14, 17), (18, 21), (22, 25), (26, 28), (29, 30)}
+                    new string[] { "Hello", ",", "y", "'", "all", "!", "How", "are", "you", "?" },
+                    new (int Index, int Length)[] { (0, 5), (5, 1), (7, 1), (8, 1), (9, 3), (12, 1), (14, 3), (18, 3), (22, 3), (29, 1) },
+                    new int[] { 15496, 11, 88, 6, 439, 0, 2437, 533, 5832, 30 }
                 };
             }
         }
 
-        private const string Gpt2VocabUrl = "https://huggingface.co/openai-community/gpt2/raw/main/vocab.json";
-        private const string Gpt2MergesUrl = "https://huggingface.co/openai-community/gpt2/raw/main/merges.txt";
-
-        [Fact]
-        public async void TestGpt2Vocab()
+        [Theory]
+        [MemberData(nameof(BpeTestData))]
+        public void TestBpeTokenizer(string text, string[] expectedTokens, (int Index, int Length)[] expectedOffsets, int[] expectedIds)
         {
-            using HttpClient httpClient = new HttpClient();
-            using Stream vocabStream = await httpClient.GetStreamAsync(Gpt2VocabUrl);
-            using Stream mergesStream = await httpClient.GetStreamAsync(Gpt2MergesUrl);
+            Tokenizer tokenizer = GetGpt2Tokenizer();
 
-            Bpe bpe = new Bpe(vocabStream, mergesStream);
-            Tokenizer tokenizer = new Tokenizer(bpe);
+            IReadOnlyList<Token> encoding = tokenizer.Encode(text, out _);
+            IReadOnlyList<Token> encoding1 = tokenizer.Encode(text.AsSpan(), out _);
 
-            string text = "The quick brown fox jumps over the lazy dog!";
+            Assert.Equal(expectedTokens, encoding.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding.Select(t => t.Id).ToArray());
 
-            EncodingResult encoding = tokenizer.Encode(text);
-            IReadOnlyList<int> ids = tokenizer.EncodeToIds(text);
+            Assert.Equal(expectedTokens, encoding1.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding1.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding1.Select(t => t.Id).ToArray());
 
-            Assert.Equal(12, encoding.Tokens.Count);
-            Assert.Equal(12, encoding.Offsets.Count);
-            Assert.Equal(12, encoding.Ids.Count);
-            Assert.Equal(encoding.Ids, ids);
-            Assert.Equal(12, tokenizer.CountTokens(text));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan()));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text, expectedIds.Length, out string? normalizedString, out int length));
+            Assert.Null(normalizedString);
+            Assert.Equal(text.Length, length);
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan(), expectedIds.Length, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            Assert.Equal(text.Length, length);
 
-            TokenizerTests.TestTokenLimits(tokenizer);
+            Assert.Equal(expectedIds.Take(expectedIds.Length - 2), tokenizer.EncodeToIds(text, expectedIds.Length - 2, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            int expectedLength = expectedOffsets[expectedOffsets.Length - 3].Index + expectedOffsets[expectedOffsets.Length - 3].Length;
+            Assert.Equal(expectedLength, length);
+            Assert.Equal(expectedIds.Take(expectedIds.Length - 2), tokenizer.EncodeToIds(text.AsSpan(), expectedIds.Length - 2, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedLength, length);
+
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text));
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text.AsSpan()));
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 4].Index + expectedOffsets[expectedOffsets.Length - 4].Length, tokenizer.IndexOfTokenCount(text, expectedIds.Length - 3, out normalizedString, out int tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedIds.Length - 3, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 4].Index + expectedOffsets[expectedOffsets.Length - 4].Length, tokenizer.IndexOfTokenCount(text.AsSpan(), expectedIds.Length - 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedIds.Length - 3, tokenCount);
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 3].Index, tokenizer.LastIndexOfTokenCount(text, 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(3, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 3].Index, tokenizer.LastIndexOfTokenCount(text.AsSpan(), 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(3, tokenCount);
         }
 
         private static string WriteToMergeFile((string, string)[] mergeEntries)
@@ -360,7 +424,7 @@ namespace Microsoft.ML.Tokenizers.Tests
             return fileName;
         }
 
-        internal static Bpe CreateEmptyBpe()
+        internal static Bpe CreateEmptyBpe(PreTokenizer? preTokenizer = null, Normalizer? normalizer = null)
         {
             using MemoryStream emptyVocabStream = new MemoryStream();
             using StreamWriter writer = new StreamWriter(emptyVocabStream);
@@ -368,7 +432,7 @@ namespace Microsoft.ML.Tokenizers.Tests
             writer.Flush();
             emptyVocabStream.Position = 0;
 
-            return new Bpe(vocabStream: emptyVocabStream, mergesStream: null, unknownToken: "Ukn");
+            return new Bpe(vocabStream: emptyVocabStream, mergesStream: null, preTokenizer: preTokenizer ?? WhiteSpace.Instance, normalizer: normalizer, unknownToken: "Ukn");
         }
     }
 }

test/Microsoft.ML.Tokenizers.Tests/EnglishRobertaTests.cs

@@ -6,9 +6,11 @@ using System;
 using System.IO;
 using System.Collections.Generic;
 using System.Linq;
-using System.Text;
+using System.Net.Http;
 
 using Xunit;
+using System.Diagnostics;
+using System.Threading.Tasks;
 
 namespace Microsoft.ML.Tokenizers.Tests
 {
@@ -80,6 +82,34 @@ namespace Microsoft.ML.Tokenizers.Tests
             }
         }
 
+        private static Tokenizer? _robertaTokenizer = null;
+        private async static Task<Tokenizer> GetRobertaTokenizer()
+        {
+            if (_robertaTokenizer is null)
+            {
+                string vocabFile = Utils.CreateTemporaryFile("json");
+                string mergeFile = Utils.CreateTemporaryFile("txt");
+                string translationFile = Utils.CreateTemporaryFile("txt");
+
+                try
+                {
+                    await Utils.DownloadFile(_vocabUrl, vocabFile);
+                    await Utils.DownloadFile(_mergeUrl, mergeFile);
+                    await Utils.DownloadFile(_dictUrl, translationFile);
+
+                    _robertaTokenizer = new EnglishRoberta(vocabFile, mergeFile, translationFile, RobertaPreTokenizer.Instance);
+                }
+                finally
+                {
+                    Utils.DeleteFile(vocabFile);
+                    Utils.DeleteFile(mergeFile);
+                    Utils.DeleteFile(translationFile);
+                }
+            }
+
+            return _robertaTokenizer;
+        }
+
         [Fact]
         public async void TokenizationTest()
         {
@@ -94,26 +124,26 @@ namespace Microsoft.ML.Tokenizers.Tests
                 await Utils.DownloadFile(_mergeUrl, mergeFile);
                 await Utils.DownloadFile(_dictUrl, translationFile);
 
-                Tokenizer tokenizer = new Tokenizer(new EnglishRoberta(vocabFile, mergeFile, translationFile), RobertaPreTokenizer.Instance);
+                Tokenizer tokenizer = new EnglishRoberta(vocabFile, mergeFile, translationFile, RobertaPreTokenizer.Instance);
                 TestTokenizer(tokenizer);
                 TokenizerTests.TestTokenLimits(tokenizer);
 
-                tokenizer = new Tokenizer(new EnglishRoberta(vocabFile, mergeFile, translationFile, filterUnsupportedChars: false), RobertaPreTokenizer.Instance);
+                tokenizer = new EnglishRoberta(vocabFile, mergeFile, translationFile, RobertaPreTokenizer.Instance, filterUnsupportedChars: false);
                 TestTokenizer(tokenizer);
 
                 using Stream vocabStream = File.OpenRead(vocabFile);
                 using Stream mergeStream = File.OpenRead(mergeFile);
                 using Stream translationStream = File.OpenRead(translationFile);
-                tokenizer = new Tokenizer(new EnglishRoberta(vocabStream, mergeStream, translationStream), RobertaPreTokenizer.Instance);
+                tokenizer = new EnglishRoberta(vocabStream, mergeStream, translationStream, RobertaPreTokenizer.Instance);
                 TestTokenizer(tokenizer);
 
                 // Ensure caching works regardless of which method is called first.
                 for (CallingOrder order = CallingOrder.Encode; order <= CallingOrder.CountTokens; order++)
                 {
-                    tokenizer = new Tokenizer(new EnglishRoberta(vocabFile, mergeFile, translationFile), RobertaPreTokenizer.Instance);
+                    tokenizer = new EnglishRoberta(vocabFile, mergeFile, translationFile, RobertaPreTokenizer.Instance);
                     TestTokenizer(tokenizer, order);
 
-                    tokenizer = new Tokenizer(new EnglishRoberta(vocabFile, mergeFile, translationFile, filterUnsupportedChars: false), RobertaPreTokenizer.Instance);
+                    tokenizer = new EnglishRoberta(vocabFile, mergeFile, translationFile, RobertaPreTokenizer.Instance, filterUnsupportedChars: false);
                     TestTokenizer(tokenizer, order);
                 }
             }
@@ -132,6 +162,94 @@ namespace Microsoft.ML.Tokenizers.Tests
             }
         }
 
+        public static IEnumerable<object?[]> RobertaTestData
+        {
+            get
+            {
+                // string to tokenize, produced tokens, the token offsets
+                yield return new object?[]
+                {
+                    "the brown fox jumped over the lazy dog!",
+                    new string[] { "the", "Ġbrown", "Ġfox", "Ġjumped", "Ġover", "Ġthe", "Ġlazy", "Ġdog", "!" },
+                    new (int Index, int Length)[] { (0, 3), (3, 6), (9, 4), (13, 7), (20, 5), (25, 4), (29, 5), (34, 4), (38, 1) },
+                    new int[] { 1169, 7586, 21831, 11687, 625, 262, 16931, 3290, 0 }
+                };
+                yield return new object?[]
+                {
+                    "he traveled to Egypt during the summer, the weather was hot and ammunition." ,
+                    new string[] { "he", "Ġtraveled", "Ġto", "ĠEgypt", "Ġduring", "Ġthe", "Ġsummer", ",", "Ġthe", "Ġweather", "Ġwas", "Ġhot", "Ġand", "Ġammunition", "." },
+                    new (int Index, int Length)[] { (0, 2), (2, 9), (11, 3), (14, 6), (20, 7), (27, 4), (31, 7), (38, 1), (39, 4), (43, 8), (51, 4), (55, 4), (59, 4), (63, 11), (74, 1) },
+                    new int[] { 258, 14113, 284, 6365, 1141, 262, 3931, 11, 262, 6193, 373, 3024, 290, 14271, 13 }
+                };
+                yield return new object?[]
+                {
+                    "She played many games and she felt exhausted afterward",
+                    new string[] { "She", "Ġplayed", "Ġmany", "Ġgames", "Ġand", "Ġshe", "Ġfelt", "Ġexhausted", "Ġafterward" },
+                    new (int Index, int Length)[] { (0, 3), (3, 7), (10, 5), (15, 6), (21, 4), (25, 4), (29, 5), (34, 10), (44, 10) },
+                    new int[] { 3347, 2826, 867, 1830, 290, 673, 2936, 19064, 20875 }
+                };
+                yield return new object?[]
+                {
+                    "Hello, y'all! How are you 😁 ?",
+                    new string[] { "Hello", ",", "Ġy", "'", "all", "!", "ĠHow", "Ġare", "Ġyou", "Ġ", "Ġ?" },
+                    new (int Index, int Length)[] { (0, 5), (5, 1), (6, 2), (8, 1), (9, 3), (12, 1), (13, 4), (17, 4), (21, 4), (25, 1), (28, 2) },
+                    new int[] { 15496, 11, 331, 6, 439, 0, 1374, 389, 345, 220, 5633 }
+                };
+            }
+        }
+
+        [Theory]
+        [MemberData(nameof(RobertaTestData))]
+        public async void TestTokenizerEncoding(string text, string[] expectedTokens, (int Index, int Length)[] expectedOffsets, int[] expectedIds)
+        {
+            Tokenizer tokenizer = await GetRobertaTokenizer();
+
+            IReadOnlyList<Token> encoding = tokenizer.Encode(text, out _);
+            IReadOnlyList<Token> encoding1 = tokenizer.Encode(text.AsSpan(), out _);
+
+            Assert.Equal(expectedTokens, encoding.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding.Select(t => t.Id).ToArray());
+
+            Assert.Equal(expectedTokens, encoding1.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding1.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding1.Select(t => t.Id).ToArray());
+
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan()));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text, expectedIds.Length, out string? normalizedString, out int length));
+            Assert.Null(normalizedString);
+            Assert.Equal(text.Length, length);
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan(), expectedIds.Length, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            Assert.Equal(text.Length, length);
+
+            Assert.Equal(expectedIds.Take(expectedIds.Length - 2), tokenizer.EncodeToIds(text, expectedIds.Length - 2, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            int expectedLength = expectedOffsets[expectedOffsets.Length - 3].Index + expectedOffsets[expectedOffsets.Length - 3].Length;
+            Assert.Equal(expectedLength, length);
+            Assert.Equal(expectedIds.Take(expectedIds.Length - 2), tokenizer.EncodeToIds(text.AsSpan(), expectedIds.Length - 2, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedLength, length);
+
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text));
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text.AsSpan()));
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 4].Index + expectedOffsets[expectedOffsets.Length - 4].Length, tokenizer.IndexOfTokenCount(text, expectedIds.Length - 3, out normalizedString, out int tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedIds.Length - 3, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 4].Index + expectedOffsets[expectedOffsets.Length - 4].Length, tokenizer.IndexOfTokenCount(text.AsSpan(), expectedIds.Length - 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedIds.Length - 3, tokenCount);
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 3].Index, tokenizer.LastIndexOfTokenCount(text, 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(3, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 3].Index, tokenizer.LastIndexOfTokenCount(text.AsSpan(), 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(3, tokenCount);
+        }
+
         private enum CallingOrder
         {
             Encode,
@@ -143,66 +261,67 @@ namespace Microsoft.ML.Tokenizers.Tests
         // Calling with callIdsFirst = true will test the other way around.
         private void TestTokenizer(Tokenizer tokenizer, CallingOrder callingOrder = CallingOrder.Encode)
         {
-            Assert.NotNull(tokenizer.Model);
-            Assert.True(tokenizer.Model is EnglishRoberta);
+            Assert.True(tokenizer is EnglishRoberta);
             Assert.True(tokenizer.PreTokenizer is RobertaPreTokenizer);
 
             foreach (object[] p in BertaData)
             {
                 IReadOnlyList<int> ids;
-                EncodingResult encoding;
+                IReadOnlyList<Token> encoding;
                 int idsCount;
 
                 if (callingOrder == CallingOrder.Encode)
                 {
-                    encoding = tokenizer.Encode((string)p[0]);
+                    encoding = tokenizer.Encode((string)p[0], out _);
                     ids = tokenizer.EncodeToIds((string)p[0]);
                     idsCount = tokenizer.CountTokens((string)p[0]);
                 }
                 else if (callingOrder == CallingOrder.EncodeToIds)
                 {
                     ids = tokenizer.EncodeToIds((string)p[0]);
-                    encoding = tokenizer.Encode((string)p[0]);
+                    encoding = tokenizer.Encode((string)p[0], out _);
                     idsCount = tokenizer.CountTokens((string)p[0]);
                 }
                 else // CountTokens
                 {
                     idsCount = tokenizer.CountTokens((string)p[0]);
                     ids = tokenizer.EncodeToIds((string)p[0]);
-                    encoding = tokenizer.Encode((string)p[0]);
+                    encoding = tokenizer.Encode((string)p[0], out _);
                 }
 
-                Assert.Equal(p[1], encoding.Ids);
+                int[] encodingIds = encoding.Select(t => t.Id).ToArray();
+                (int, int)[] offsets = encoding.Select(t => t.Offset).ToArray();
+                string[] tokens = encoding.Select(t => t.Value).ToArray();
+
+                Assert.Equal(p[1], encodingIds);
                 Assert.Equal(p[1], ids);
                 Assert.Equal(((int[])p[1]).Length, idsCount);
-                Assert.Equal(p[3], encoding.Offsets);
-                Assert.Equal(encoding.Ids.Count, encoding.Tokens.Count);
-                Assert.Equal(encoding.Ids.Count, encoding.Offsets.Count);
+                Assert.Equal(p[3], offsets);
 
-                EnglishRoberta? robertaModel = tokenizer.Model as EnglishRoberta;
-                Assert.Equal(p[2], encoding.Tokens);
+                EnglishRoberta? robertaModel = tokenizer as EnglishRoberta;
+                Assert.Equal(p[2], tokens);
 
-                Assert.Equal(string.Concat((string[])(p[robertaModel!.FilterUnsupportedChars ? 5 : 2])), tokenizer.Decode(encoding.Ids));
+                Assert.Equal(string.Concat((string[])(p[robertaModel!.FilterUnsupportedChars ? 5 : 2])), tokenizer.Decode(encodingIds));
 
                 Assert.NotNull(robertaModel);
-                Assert.Equal(encoding.Ids, robertaModel!.ConvertOccurrenceRanksToIds(robertaModel!.ConvertIdsToOccurrenceRanks(encoding.Ids)));
-                Assert.Equal(p[4], robertaModel.ConvertIdsToOccurrenceValues(encoding.Ids));
+                Assert.Equal(encodingIds, robertaModel!.ConvertOccurrenceRanksToIds(robertaModel!.ConvertIdsToOccurrenceRanks(encodingIds)));
+                Assert.Equal(p[4], robertaModel.ConvertIdsToOccurrenceValues(encodingIds));
 
-                for (int i = 0; i < encoding.Tokens.Count; i++)
+                for (int i = 0; i < tokens.Length; i++)
                 {
                     if (robertaModel.FilterUnsupportedChars)
                     {
                         string[]? filteredToken = p[5] as string[];
-                        Assert.Equal(filteredToken![i], tokenizer.Model.MapIdToToken(encoding.Ids[i]));
+                        Assert.Equal(filteredToken![i], tokenizer.MapIdToToken(encodingIds[i]));
                     }
                     else
                     {
-                        Assert.Equal(encoding.Tokens[i], tokenizer.Model.MapIdToToken(encoding.Ids[i]));
+                        Assert.Equal(tokens[i], tokenizer.MapIdToToken(encodingIds[i]));
                         string[]? unfilteredToken = p[2] as string[];
-                        Assert.Equal(unfilteredToken![i], tokenizer.Model.MapIdToToken(encoding.Ids[i]));
+                        Assert.Equal(unfilteredToken![i], tokenizer.MapIdToToken(encodingIds[i]));
                     }
 
-                    Assert.Equal(encoding.Ids[i], tokenizer.Model.MapTokenToId(encoding.Tokens[i].AsSpan()));
+                    Assert.Equal(encodingIds[i], tokenizer.MapTokenToId(tokens[i].AsSpan()));
                 }
             }
         }

test/Microsoft.ML.Tokenizers.Tests/LlamaTests.cs

@@ -17,20 +17,21 @@ namespace Microsoft.ML.Tokenizers.Tests
     public class LlamaTests
     {
         private static readonly HttpClient _httpClient = new HttpClient() { Timeout = TimeSpan.FromMinutes(5) };
-        private static Tokenizer _llamaTokenizer = CreateLlamaTokenizer().GetAwaiter().GetResult();
-        private static Tokenizer _llamaMistralTokenizer = CreateLMistralTokenizer().GetAwaiter().GetResult();
+        private static Tokenizer _llamaTokenizer = CreateLlamaTokenizer();
+        private static Tokenizer _llamaMistralTokenizer = CreateLMistralTokenizer();
 
-        private static async Task<Tokenizer> CreateLlamaTokenizer()
+        private static Tokenizer CreateLlamaTokenizer()
         {
-            const string modelUrl = @"https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer.model";
-            using Stream remoteStream = await _httpClient.GetStreamAsync(modelUrl);
+            // @"https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/resolve/main/tokenizer.model?download=true";
+            // @"https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer.model";
+            using Stream remoteStream = File.OpenRead(Path.Combine(@"Llama", "tokenizer.model"));
             return Tokenizer.CreateLlama(remoteStream);
         }
 
-        private static async Task<Tokenizer> CreateLMistralTokenizer()
+        private static Tokenizer CreateLMistralTokenizer()
         {
-            const string modelUrl = @"https://huggingface.co/mistralai/Mistral-7B-v0.1/resolve/main/tokenizer.model?download=true";
-            using Stream remoteStream = await _httpClient.GetStreamAsync(modelUrl);
+            // @"https://huggingface.co/mistralai/Mistral-7B-v0.1/resolve/main/tokenizer.model?download=true";
+            using Stream remoteStream = File.OpenRead(Path.Combine(@"Mistral", "tokenizer.model"));
             return Tokenizer.CreateLlama(remoteStream);
         }
 
@@ -185,13 +186,13 @@ namespace Microsoft.ML.Tokenizers.Tests
         [MemberData(nameof(LlamaTestData))]
         public void TestLlamaTokenizer(Tokenizer llamaTokenizer, string input, int[] ids, string[] tokens, (int Index, int Length)[] offsets)
         {
-            SentencePieceBpe? bpe = llamaTokenizer.Model as SentencePieceBpe;
+            SentencePieceBpe? bpe = llamaTokenizer as SentencePieceBpe;
             Assert.NotNull(bpe);
 
-            EncodingResult result = llamaTokenizer.Encode(input);
-            Assert.Equal(ids, result.Ids);
-            Assert.Equal(tokens, result.Tokens);
-            Assert.Equal(offsets, result.Offsets);
+            IReadOnlyList<Token> result = llamaTokenizer.Encode(input, out _);
+            Assert.Equal(ids, result.Select(t => t.Id).ToArray());
+            Assert.Equal(tokens, result.Select(t => t.Value).ToArray());
+            Assert.Equal(offsets, result.Select(t => t.Offset).ToArray());
             Assert.Equal(input, llamaTokenizer.Decode(ids));
             Assert.Equal(ids, llamaTokenizer.EncodeToIds(input));
             Assert.Equal(ids.Length, llamaTokenizer.CountTokens(input));
@@ -208,32 +209,29 @@ namespace Microsoft.ML.Tokenizers.Tests
 
             bool isEmptyInput = string.IsNullOrEmpty(input);
 
-            IReadOnlyList<Token> bpeTokens = bpe.Encode(normalizedInput.AsSpan(), addBeginOfSentence: false, addEndOfSentence: false);
+            IReadOnlyList<Token> bpeTokens = bpe.Encode(normalizedInput.AsSpan(), out _, addBeginningOfSentence: false, addEndOfSentence: false, considerNormalization: false);
             Assert.Equal(ids.Skip(1), bpeTokens.Select(token => token.Id));
             Assert.Equal(tokens.Skip(1), bpeTokens.Select(token => token.Value));
             Assert.Equal(input, llamaTokenizer.Decode(bpeTokens.Select(token => token.Id)));
-            List<int> encodedIds = new();
-            bpe.EncodeToIds(normalizedInput.AsSpan(), addBeginOfSentence: false, addEndOfSentence: false, accumulatedIds: encodedIds, out _);
+            IReadOnlyList<int> encodedIds = bpe.EncodeToIds(normalizedInput.AsSpan(), addBeginningOfSentence: false, addEndOfSentence: false, considerNormalization: false);
             Assert.Equal(ids.Skip(1), encodedIds);
-            Assert.Equal(isEmptyInput ? 0 : ids.Length - 1, bpe.CountTokens(normalizedInput.AsSpan(), addBeginOfSentence: false, addEndOfSentence: false, out _));
+            Assert.Equal(isEmptyInput ? 0 : ids.Length - 1, bpe.CountTokens(normalizedInput.AsSpan(), addBeginningOfSentence: false, addEndOfSentence: false, considerNormalization: false));
 
-            bpeTokens = bpe.Encode(normalizedInput.AsSpan(), addBeginOfSentence: false, addEndOfSentence: true);
+            bpeTokens = bpe.Encode(normalizedInput.AsSpan(), out _, addBeginningOfSentence: false, addEndOfSentence: true, considerNormalization: false);
             Assert.Equal(isEmptyInput ? Array.Empty<int>() : ids.Skip(1).Concat(new[] { bpe.EndOfSentenceId }), bpeTokens.Select(token => token.Id));
             Assert.Equal(isEmptyInput ? Array.Empty<string>() : tokens.Skip(1).Concat(new[] { bpe.EndOfSentenceToken }), bpeTokens.Select(token => token.Value));
             Assert.Equal(input, llamaTokenizer.Decode(bpeTokens.Select(token => token.Id)));
-            encodedIds.Clear();
-            bpe.EncodeToIds(normalizedInput.AsSpan(), addBeginOfSentence: false, addEndOfSentence: true, accumulatedIds: encodedIds, out _);
+            encodedIds = bpe.EncodeToIds(normalizedInput.AsSpan(), addBeginningOfSentence: false, addEndOfSentence: true, considerNormalization: false);
             Assert.Equal(isEmptyInput ? Array.Empty<int>() : ids.Skip(1).Concat(new[] { bpe.EndOfSentenceId }), encodedIds);
-            Assert.Equal(isEmptyInput ? 0 : ids.Length, bpe.CountTokens(normalizedInput.AsSpan(), addBeginOfSentence: false, addEndOfSentence: true, out _));
+            Assert.Equal(isEmptyInput ? 0 : ids.Length, bpe.CountTokens(normalizedInput.AsSpan(), addBeginningOfSentence: false, addEndOfSentence: true, considerNormalization: false));
 
-            bpeTokens = bpe.Encode(normalizedInput.AsSpan(), addBeginOfSentence: true, addEndOfSentence: true);
+            bpeTokens = bpe.Encode(normalizedInput.AsSpan(), out _, addBeginningOfSentence: true, addEndOfSentence: true, considerNormalization: false);
             Assert.Equal(isEmptyInput ? Array.Empty<int>() : ids.Concat(new[] { bpe.EndOfSentenceId }), bpeTokens.Select(token => token.Id));
             Assert.Equal(isEmptyInput ? Array.Empty<string>() : tokens.Concat(new[] { bpe.EndOfSentenceToken }), bpeTokens.Select(token => token.Value));
             Assert.Equal(input, llamaTokenizer.Decode(bpeTokens.Select(token => token.Id)));
-            encodedIds.Clear();
-            bpe.EncodeToIds(normalizedInput.AsSpan(), addBeginOfSentence: true, addEndOfSentence: true, accumulatedIds: encodedIds, out _);
+            encodedIds = bpe.EncodeToIds(normalizedInput.AsSpan(), addBeginningOfSentence: true, addEndOfSentence: true, considerNormalization: false);
             Assert.Equal(isEmptyInput ? Array.Empty<int>() : ids.Concat(new[] { bpe.EndOfSentenceId }), encodedIds);
-            Assert.Equal(isEmptyInput ? 0 : ids.Length + 1, bpe.CountTokens(normalizedInput.AsSpan(), addBeginOfSentence: true, addEndOfSentence: true, out _));
+            Assert.Equal(isEmptyInput ? 0 : ids.Length + 1, bpe.CountTokens(normalizedInput.AsSpan(), addBeginningOfSentence: true, addEndOfSentence: true, considerNormalization: false));
         }
 
         public static IEnumerable<object[]> LlamaTokenizersListData()
@@ -244,11 +242,17 @@ namespace Microsoft.ML.Tokenizers.Tests
 
         [Theory]
         [MemberData(nameof(LlamaTokenizersListData))]
-        public void TestLlamaTokenizerWithInvalidInput(Tokenizer llamaTokenizer)
+        public void TestLlamaTokenizerWithEmptyInput(Tokenizer llamaTokenizer)
         {
-            Assert.Throws<ArgumentNullException>(() => llamaTokenizer.Encode(null!));
-            Assert.Throws<ArgumentNullException>(() => llamaTokenizer.EncodeToIds(null!));
-            Assert.Throws<ArgumentNullException>(() => llamaTokenizer.CountTokens(null!));
+            Assert.Equal([], llamaTokenizer.Encode((string)null!, out _));
+            Assert.Equal([], llamaTokenizer.Encode(Span<char>.Empty, out _));
+
+            Assert.Equal([], llamaTokenizer.EncodeToIds((string)null!));
+            Assert.Equal([], llamaTokenizer.EncodeToIds(Span<char>.Empty));
+
+            Assert.Equal(0, llamaTokenizer.CountTokens((string)null!));
+            Assert.Equal(0, llamaTokenizer.CountTokens(Span<char>.Empty));
+
             Assert.Throws<ArgumentNullException>(() => llamaTokenizer.Decode(null!));
         }
 
@@ -256,7 +260,7 @@ namespace Microsoft.ML.Tokenizers.Tests
         [MemberData(nameof(LlamaTokenizersListData))]
         public void TestLlamaTokenizerProperties(Tokenizer llamaTokenizer)
         {
-            SentencePieceBpe? bpe = llamaTokenizer.Model as SentencePieceBpe;
+            SentencePieceBpe? bpe = llamaTokenizer as SentencePieceBpe;
             Assert.NotNull(bpe);
             Assert.NotNull(llamaTokenizer.Normalizer);
 
@@ -284,34 +288,242 @@ namespace Microsoft.ML.Tokenizers.Tests
         }
 
         [Fact]
-        public void TestLlamaNormalizer()
+        public void TestSentencePieceNormalizer()
         {
-            LlamaNormalizer normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: false, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: false);
+            SentencePieceNormalizer normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: false, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: false);
             Assert.Equal("Hello,      World!", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("Hello,      World!", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: false, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: false);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: false, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: false);
             Assert.Equal("Hello, World!", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("Hello, World!", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: true, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: false);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: true, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: false);
             Assert.Equal(" Hello, World!", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal(" Hello, World!", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: false);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: false);
             Assert.Equal("▁Hello,▁World!", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("▁Hello,▁World!", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: false);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: false);
             Assert.Equal("▁Hello,▁▁▁▁▁▁World!", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("▁Hello,▁▁▁▁▁▁World!", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: true);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: true);
             Assert.Equal("Hello,▁World!▁", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("Hello,▁World!▁", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: false, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: true);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: true, addDummyPrefix: false, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: true);
             Assert.Equal("Hello,▁World!", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("Hello,▁World!", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: true);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: true, escapeWhiteSpaces: true, treatWhitespaceAsSuffix: true);
             Assert.Equal("Hello,▁▁▁▁▁▁World!▁", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("Hello,▁▁▁▁▁▁World!▁", normalizer.Normalize("Hello,      World!".AsSpan()));
 
-            normalizer = new LlamaNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: true, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: true);
+            normalizer = new SentencePieceNormalizer(removeExtraWhiteSpaces: false, addDummyPrefix: true, escapeWhiteSpaces: false, treatWhitespaceAsSuffix: true);
             Assert.Equal("Hello,      World! ", normalizer.Normalize("Hello,      World!"));
+            Assert.Equal("Hello,      World! ", normalizer.Normalize("Hello,      World!".AsSpan()));
+        }
+
+        public static IEnumerable<object?[]> TokenizerTestData
+        {
+            get
+            {
+                // string to tokenize, produced tokens, the token offsets
+                yield return new object?[]
+                {
+                    "the brown fox jumped over the lazy dog!",
+                    "▁the▁brown▁fox▁jumped▁over▁the▁lazy▁dog!",
+                    new string[] { "<s>", "▁the", "▁brown", "▁fo", "x", "▁jump", "ed", "▁over", "▁the", "▁lazy", "▁dog", "!" },
+                    new (int Index, int Length)[] { (0, 0), (0, 4), (4, 6), (10, 3), (13, 1), (14, 5), (19, 2), (21, 5), (26, 4), (30, 5), (35, 4), (39, 1) },
+                    new int[] { 1, 278, 17354, 1701, 29916, 12500, 287, 975, 278, 17366, 11203, 29991 }
+                };
+                yield return new object?[]
+                {
+                    "he traveled to Egypt during the summer, the weather was hot and ammunition." ,
+                    "▁he▁traveled▁to▁Egypt▁during▁the▁summer,▁the▁weather▁was▁hot▁and▁ammunition." ,
+                    new string[] { "<s>", "▁he", "▁tra", "ve", "led", "▁to", "▁Egypt", "▁during", "▁the", "▁summer", ",", "▁the", "▁weather", "▁was", "▁hot", "▁and", "▁am", "mun", "ition", "." },
+                    new (int Index, int Length)[] { (0, 0), (0, 3), (3, 4), (7, 2), (9, 3), (12, 3), (15, 6), (21, 7), (28, 4), (32, 7), (39, 1), (40, 4), (44, 8), (52, 4), (56, 4), (60, 4), (64, 3), (67, 3), (70, 5), (75, 1) },
+                    new int[] { 1, 540, 1020, 345, 839, 304, 12892, 2645, 278, 11801, 29892, 278, 14826, 471, 7375, 322, 626, 24579, 654, 29889 }
+                };
+                yield return new object?[]
+                {
+                    "She played many games and she felt exhausted afterward",
+                    "▁She▁played▁many▁games▁and▁she▁felt▁exhausted▁afterward",
+                    new string[] { "<s>", "▁She", "▁played", "▁many", "▁games", "▁and", "▁she", "▁felt", "▁exha", "usted", "▁after", "ward" },
+                    new (int Index, int Length)[] { (0, 0), (0, 4), (4, 7), (11, 5), (16, 6), (22, 4), (26, 4), (30, 5), (35, 5), (40, 5), (45, 6), (51, 4) },
+                    new int[] { 1, 2296, 5318, 1784, 8090, 322, 1183, 7091, 18782, 16656, 1156, 1328 }
+                };
+                yield return new object?[]
+                {
+                    "Hello, y'all! How are you 😁 ?",
+                    "▁Hello,▁y'all!▁How▁are▁you▁😁▁?",
+                    new string[] { "<s>", "▁Hello", ",", "▁y", "'", "all", "!", "▁How", "▁are", "▁you", "▁", "<0xF0>", "<0x9F>", "<0x98>", "<0x81>", "▁?" },
+                    new (int Index, int Length)[] { (0, 0), (0, 6), (6, 1), (7, 2), (9, 1), (10, 3), (13, 1), (14, 4), (18, 4), (22, 4), (26, 1), (27, 2), (27, 0), (27, 0), (27, 0), (29, 2) },
+                    new int[] { 1, 15043, 29892, 343, 29915, 497, 29991, 1128, 526, 366, 29871, 243, 162, 155, 132, 1577 }
+                };
+            }
+        }
+
+        [Theory]
+        [MemberData(nameof(TokenizerTestData))]
+        public void TestTokenizerEncoding(string text, string normalizedText, string[] expectedTokens, (int Index, int Length)[] expectedOffsets, int[] expectedIds)
+        {
+            Tokenizer tokenizer = _llamaTokenizer;
+
+            Assert.NotNull(tokenizer.Normalizer);
+            Assert.Null(tokenizer.PreTokenizer);
+
+            IReadOnlyList<Token> encoding = tokenizer.Encode(text, out _);
+            IReadOnlyList<Token> encoding1 = tokenizer.Encode(text.AsSpan(), out _);
+
+            Assert.Equal(expectedTokens, encoding.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding.Select(t => t.Id).ToArray());
+
+            Assert.Equal(expectedTokens, encoding1.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding1.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding1.Select(t => t.Id).ToArray());
+
+            SentencePieceBpe sentencePieceBpe = (tokenizer as SentencePieceBpe)!;
+            foreach (bool considerNormalization in new[] { true, false })
+                foreach (bool addBeginningOfSentence in new[] { true, false })
+                    foreach (bool addEndOfSentence in new[] { true, false })
+                    {
+                        encoding = sentencePieceBpe.Encode(
+                                        considerNormalization ? text : normalizedText,
+                                        out _,
+                                        addBeginningOfSentence: addBeginningOfSentence,
+                                        addEndOfSentence: addEndOfSentence,
+                                        considerPreTokenization: false,
+                                        considerNormalization: considerNormalization);
+
+                        encoding1 = sentencePieceBpe.Encode(
+                                        considerNormalization ? text.AsSpan() : normalizedText.AsSpan(),
+                                        out _,
+                                        addBeginningOfSentence: addBeginningOfSentence,
+                                        addEndOfSentence: addEndOfSentence,
+                                        considerPreTokenization: false,
+                                        considerNormalization: considerNormalization);
+
+                        string[] expectedTokens1 = addBeginningOfSentence ? expectedTokens : expectedTokens.Skip(1).ToArray();
+                        expectedTokens1 = addEndOfSentence ? expectedTokens1.Concat(new[] { sentencePieceBpe.EndOfSentenceToken }).ToArray() : expectedTokens1;
+
+                        (int Index, int Length)[] expectedOffsets1 = addBeginningOfSentence ? expectedOffsets : expectedOffsets.Skip(1).ToArray();
+                        expectedOffsets1 = addEndOfSentence ? expectedOffsets1.Concat(new[] { (normalizedText.Length, 0) }).ToArray() : expectedOffsets1;
+
+                        int[] expectedIds1 = addBeginningOfSentence ? expectedIds : expectedIds.Skip(1).ToArray();
+                        expectedIds1 = addEndOfSentence ? expectedIds1.Concat(new[] { sentencePieceBpe.EndOfSentenceId }).ToArray() : expectedIds1;
+
+                        Assert.Equal(expectedTokens1, encoding.Select(t => t.Value).ToArray());
+                        Assert.Equal(expectedOffsets1, encoding.Select(t => t.Offset).ToArray());
+                        Assert.Equal(expectedIds1, encoding.Select(t => t.Id).ToArray());
+                    }
+        }
+
+        [Theory]
+        [MemberData(nameof(TokenizerTestData))]
+        public void TestTokenizerEncodingToIds(string text, string normalizedText, string[] expectedTokens, (int Index, int Length)[] expectedOffsets, int[] expectedIds)
+        {
+            Tokenizer tokenizer = _llamaTokenizer;
+
+            Assert.NotNull(expectedTokens);
+            Assert.NotNull(expectedOffsets);
+
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan()));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text, expectedIds.Length, out string? normalizedString, out int length));
+            Assert.Equal(normalizedText, normalizedString);
+            Assert.Equal(normalizedText.Length, length);
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan(), expectedIds.Length, out normalizedString, out length));
+            Assert.Equal(normalizedText, normalizedString);
+            Assert.Equal(normalizedText.Length, length);
+
+            SentencePieceBpe sentencePieceBpe = (tokenizer as SentencePieceBpe)!;
+            foreach (bool considerNormalization in new[] { true, false })
+                foreach (bool addBeginningOfSentence in new[] { true, false })
+                    foreach (bool addEndOfSentence in new[] { true, false })
+                    {
+                        // (string text, bool addBeginningOfSentence, bool addEndOfSentence, int maxTokenCount, out string? normalizedString, out int textLength, bool considerPreTokenization = true, bool considerNormalization = true)
+
+                        int[] expectedIds1 = addBeginningOfSentence ? expectedIds : expectedIds.Skip(1).ToArray();
+                        expectedIds1 = addEndOfSentence ? expectedIds1.Concat(new[] { sentencePieceBpe.EndOfSentenceId }).ToArray() : expectedIds1;
+
+                        Assert.Equal(expectedIds1, sentencePieceBpe.EncodeToIds(
+                                                        considerNormalization ? text : normalizedText,
+                                                        addBeginningOfSentence: addBeginningOfSentence,
+                                                        addEndOfSentence: addEndOfSentence,
+                                                        expectedIds1.Length,
+                                                        out normalizedString,
+                                                        out length,
+                                                        considerNormalization: considerNormalization));
+
+                        Assert.Equal(expectedIds1, sentencePieceBpe.EncodeToIds(
+                                                        considerNormalization ? text.AsSpan() : normalizedText.AsSpan(),
+                                                        addBeginningOfSentence: addBeginningOfSentence,
+                                                        addEndOfSentence: addEndOfSentence,
+                                                        expectedIds1.Length,
+                                                        out normalizedString,
+                                                        out length,
+                                                        considerNormalization: considerNormalization));
+
+                        Assert.Equal(considerNormalization ? normalizedText : null, normalizedString);
+                        Assert.Equal(normalizedText.Length, length);
+
+                        Assert.Equal(expectedIds1.Take(expectedIds1.Length - 6), sentencePieceBpe.EncodeToIds(
+                                                                                    considerNormalization ? text : normalizedText,
+                                                                                    addBeginningOfSentence: addBeginningOfSentence,
+                                                                                    addEndOfSentence: addEndOfSentence,
+                                                                                    expectedIds1.Length - 6,
+                                                                                    out normalizedString,
+                                                                                    out length,
+                                                                                    considerNormalization: considerNormalization));
+                        Assert.Equal(considerNormalization ? normalizedText : null, normalizedString);
+
+                        (int Index, int Length)[] expectedOffsets1 = addBeginningOfSentence ? expectedOffsets.Take(expectedIds1.Length - 6).ToArray() : expectedOffsets.Skip(1).Take(expectedIds1.Length - 6).ToArray();
+
+                        int expectedLength = expectedOffsets1[expectedOffsets1.Length - 1].Index + expectedOffsets1[expectedOffsets1.Length - 1].Length;
+                        Assert.Equal(expectedLength, length);
+
+                        Assert.Equal(expectedIds1.Take(expectedIds1.Length - 6), sentencePieceBpe.EncodeToIds(
+                                                                                    considerNormalization ? text.AsSpan() : normalizedText.AsSpan(),
+                                                                                    addBeginningOfSentence: addBeginningOfSentence,
+                                                                                    addEndOfSentence: addEndOfSentence,
+                                                                                    expectedIds1.Length - 6,
+                                                                                    out normalizedString,
+                                                                                    out length,
+                                                                                    considerNormalization: considerNormalization));
+                        Assert.Equal(expectedLength, length);
+                    }
+        }
+
+
+        [Theory]
+        [MemberData(nameof(TokenizerTestData))]
+        public void TestTokenizerCountTokens(string text, string normalizedText, string[] expectedTokens, (int Index, int Length)[] expectedOffsets, int[] expectedIds)
+        {
+            Tokenizer tokenizer = _llamaTokenizer;
+
+            Assert.NotNull(expectedTokens);
+
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text));
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text.AsSpan()));
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 7].Index + expectedOffsets[expectedOffsets.Length - 7].Length, tokenizer.IndexOfTokenCount(text, expectedIds.Length - 6, out string? normalizedString, out int tokenCount));
+            Assert.Equal(normalizedText, normalizedString);
+            Assert.Equal(expectedIds.Length - 6, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 7].Index + expectedOffsets[expectedOffsets.Length - 7].Length, tokenizer.IndexOfTokenCount(text.AsSpan(), expectedIds.Length - 6, out normalizedString, out tokenCount));
+            Assert.Equal(normalizedText, normalizedString);
+            Assert.Equal(expectedIds.Length - 6, tokenCount);
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 7].Index, tokenizer.LastIndexOfTokenCount(text, 7, out normalizedString, out tokenCount));
+            Assert.Equal(normalizedText, normalizedString);
+            Assert.Equal(7, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 7].Index, tokenizer.LastIndexOfTokenCount(text.AsSpan(), 7, out normalizedString, out tokenCount));
+            Assert.Equal(normalizedText, normalizedString);
+            Assert.Equal(7, tokenCount);
         }
     }
 }

test/Microsoft.ML.Tokenizers.Tests/Microsoft.ML.Tokenizers.Tests.csproj

@@ -42,6 +42,7 @@
   <ItemGroup>
     <PackageReference Include="Microsoft.DotNet.RemoteExecutor" Version="$(MicrosoftDotNetRemoteExecutorVersion)" />
     <PackageReference Include="System.Text.Json" Version="$(SystemTextJsonVersion)" />
+    <PackageReference Include="Microsoft.ML.TestTokenizers" Version="$(MicrosoftMLTestTokenizersVersion)" />
   </ItemGroup>
 
 </Project>

test/Microsoft.ML.Tokenizers.Tests/NormalizerTests.cs

@@ -61,10 +61,9 @@ namespace Microsoft.ML.Tokenizers.Tests
             string normalizedText = normalizer.Normalize(text);
             Assert.Equal(normalized, normalizedText);
 
-            Tokenizer tokenizer = new Tokenizer(BpeTests.CreateEmptyBpe(), WhiteSpace.Instance, normalizer);
-            EncodingResult encoding = tokenizer.Encode(text);
-            Assert.Equal(text, encoding.OriginalString);
-            Assert.Equal(normalized, encoding.NormalizedString);
+            Tokenizer tokenizer = BpeTests.CreateEmptyBpe(preTokenizer: null, normalizer);
+            IReadOnlyList<Token> tokens = tokenizer.Encode(text, out string? normalizedString);
+            Assert.Equal(normalized, normalizedString);
         }
 
         public class RemoveQuotesNormalizer : Normalizer
@@ -77,6 +76,22 @@ namespace Microsoft.ML.Tokenizers.Tests
                     return original;
                 }
 
+                return RemoveQuotes(original.AsSpan(), index);
+            }
+
+            public override string Normalize(ReadOnlySpan<char> original)
+            {
+                int index = original.IndexOf('"');
+                if (index <= 0)
+                {
+                    return original.ToString();
+                }
+
+                return RemoveQuotes(original, index);
+            }
+
+            private string RemoveQuotes(ReadOnlySpan<char> original, int index)
+            {
                 StringBuilder sb = new StringBuilder(original.Length);
                 List<int> mapping = new List<int>();
 
@@ -97,7 +112,7 @@ namespace Microsoft.ML.Tokenizers.Tests
                         break;
                     }
 
-                    index = original.IndexOf('"', start);
+                    index = original.Slice(start).IndexOf('"');
                     if (index <= 0)
                     {
                         for (int i = start; i < original.Length; i++)
@@ -107,6 +122,8 @@ namespace Microsoft.ML.Tokenizers.Tests
                         }
                         break;
                     }
+
+                    index += start;
                 } while (true);
 
                 return sb.ToString();
@@ -130,6 +147,16 @@ namespace Microsoft.ML.Tokenizers.Tests
 
                 return original.Normalize(_normalizationForm);
             }
+
+            public override string Normalize(ReadOnlySpan<char> original)
+            {
+                if (original.IsEmpty)
+                {
+                    return string.Empty;
+                }
+
+                return original.ToString().Normalize(_normalizationForm);
+            }
         }
     }
 }

test/Microsoft.ML.Tokenizers.Tests/PreTokenizerTests.cs

@@ -20,62 +20,63 @@ namespace Microsoft.ML.Tokenizers.Tests
                 {
                     WhiteSpace.Instance,
                     "How are you doing?",
-                    new Split[] { new Split("How", (0, 3)), new Split("are", (4, 3)), new Split("you", (8, 3)), new Split("doing", (12, 5)), new Split("?", (17, 1)),}
+                    new (int Offset, int Length)[] { (0, 3), (4, 3), (8, 3), (12, 5), (17, 1), }
                 };
 
                 yield return new object[]
                 {
                     WhiteSpace.Instance,
                     "I_am_Just_Fine!",
-                    new Split[] { new Split("I_am_Just_Fine", (0, 14)), new Split("!", (14, 1)) }
+                    new (int Offset, int Length)[] { (0, 14), (14, 1) }
                 };
 
                 yield return new object[]
                 {
                     new SpacePreTokenizer(),
                     "How are    you doing?!",
-                    new Split[] { new Split("How", (0, 3)), new Split("are", (4, 3)), new Split("you", (11, 3)), new Split("doing?!", (15, 7)) }
+                    new (int Offset, int Length)[] { (0, 3), (4, 3), (11, 3), (15, 7) }
                 };
 
                 yield return new object[]
                 {
                     new SpacePreTokenizer(),
                     new string(' ', 100),
-                    new Split[] { }
+                    new (int Offset, int Length)[] { }
                 };
             }
         }
 
         [Theory]
         [MemberData(nameof(PreTokenizerData))]
-        public void TestPreTokenizer(PreTokenizer preTokenizer, string text, Split[] splits)
+        public void TestPreTokenizer(PreTokenizer preTokenizer, string text, (int Offset, int Length)[] splits)
         {
-            Split[] splitParts = preTokenizer.PreTokenize(text).ToArray<Split>();
+            (int Offset, int Length)[] splitParts = preTokenizer.PreTokenize(text).ToArray<(int Offset, int Length)>();
             Assert.Equal(splits, splitParts);
 
             // Empty tokenizer which tokenize all parts as unknown tokens.
-            Tokenizer tokenizer = new Tokenizer(BpeTests.CreateEmptyBpe(), preTokenizer);
+            Tokenizer tokenizer = BpeTests.CreateEmptyBpe(normalizer: null, preTokenizer: preTokenizer);
 
-            EncodingResult encoding = tokenizer.Encode(text);
-            Assert.True(encoding.Tokens.Count >= splitParts.Length, $"Expected to have {encoding.Tokens.Count} >= {splitParts.Length}");
+            IReadOnlyList<Token> encoding = tokenizer.Encode(text, out _);
+            Assert.True(encoding.Count >= splitParts.Length, $"Expected to have {encoding.Count} >= {splitParts.Length}");
         }
 
         [Fact]
         public void TestWhiteSpacePreTokenizer()
         {
-            Assert.Empty(WhiteSpace.Instance.PreTokenize(null!));
+            Assert.Empty(WhiteSpace.Instance.PreTokenize((string)null!));
         }
 
         public class SpacePreTokenizer : PreTokenizer
         {
-            public override IEnumerable<Split> PreTokenize(string text)
+            public override IEnumerable<(int Offset, int Length)> PreTokenize(ReadOnlySpan<char> text)
             {
-                List<Split> splits = new();
-                if (string.IsNullOrEmpty(text))
+                if (text.IsEmpty)
                 {
-                    return splits;
+                    return [];
                 }
 
+                List<(int Offset, int Length)> splits = new();
+
                 int index = 0;
                 while (true)
                 {
@@ -92,7 +93,7 @@ namespace Microsoft.ML.Tokenizers.Tests
 
                     if (index < text.Length)
                     {
-                        splits.Add(new Split(text.Substring(index, end - index), (index, end - index)));
+                        splits.Add((index, end - index));
                     }
                     else
                     {
@@ -104,6 +105,16 @@ namespace Microsoft.ML.Tokenizers.Tests
 
                 return splits;
             }
+
+            public override IEnumerable<(int Offset, int Length)> PreTokenize(string text)
+            {
+                if (string.IsNullOrEmpty(text))
+                {
+                    return [];
+                }
+
+                return PreTokenize(text.AsSpan());
+            }
         }
     }
 }

test/Microsoft.ML.Tokenizers.Tests/TitokenTests.cs

@@ -38,8 +38,8 @@ namespace Microsoft.ML.Tokenizers.Tests
         {
             TestGPT4TokenizationEncoding(GPT4);
 
-            Assert.True(GPT4.Model is Tiktoken);
-            IReadOnlyDictionary<string, int>? specialTokensEncoder = (GPT4.Model as Tiktoken)!.SpecialTokens;
+            Assert.True(GPT4 is Tiktoken);
+            IReadOnlyDictionary<string, int>? specialTokensEncoder = (GPT4 as Tiktoken)!.SpecialTokens;
 
             string tokenizerDataFileName = Utils.CreateTemporaryFile("tiktoken");
 
@@ -53,21 +53,21 @@ namespace Microsoft.ML.Tokenizers.Tests
 
             try
             {
-                Tokenizer tokenizer = new Tokenizer(new Tiktoken(tokenizerDataFileName, specialTokensEncoder), GPT4.PreTokenizer);
+                Tokenizer tokenizer = new Tiktoken(tokenizerDataFileName, GPT4.PreTokenizer, specialTokensEncoder);
                 TestGPT4TokenizationEncoding(tokenizer);
 
                 using (Stream stream = File.OpenRead(tokenizerDataFileName))
                 {
-                    tokenizer = new Tokenizer(new Tiktoken(stream, specialTokensEncoder), GPT4.PreTokenizer);
+                    tokenizer = new Tiktoken(stream, GPT4.PreTokenizer, specialTokensEncoder);
                 }
                 TestGPT4TokenizationEncoding(tokenizer);
 
-                tokenizer = new Tokenizer(await Tiktoken.CreateAsync(tokenizerDataFileName, specialTokensEncoder), GPT4.PreTokenizer);
+                tokenizer = await Tokenizer.CreateTiktokenAsync(tokenizerDataFileName, GPT4.PreTokenizer, normalizer: null, specialTokensEncoder);
                 TestGPT4TokenizationEncoding(tokenizer);
 
                 using (Stream stream = File.OpenRead(tokenizerDataFileName))
                 {
-                    tokenizer = new Tokenizer(await Tiktoken.CreateAsync(stream, specialTokensEncoder), GPT4.PreTokenizer);
+                    tokenizer = await Tokenizer.CreateTiktokenAsync(stream, GPT4.PreTokenizer, normalizer: null, specialTokensEncoder);
                 }
                 TestGPT4TokenizationEncoding(tokenizer);
 
@@ -109,11 +109,11 @@ namespace Microsoft.ML.Tokenizers.Tests
 
             try
             {
-                Tiktoken tiktoken = (tokenizer.Model as Tiktoken)!;
-                Tokenizer externalTokenizer = new Tokenizer(new Tiktoken(tokenizerDataFileName, tiktoken.SpecialTokens), tokenizer.PreTokenizer);
+                Tiktoken tiktoken = (tokenizer as Tiktoken)!;
+                Tokenizer externalTokenizer = new Tiktoken(tokenizerDataFileName, tokenizer.PreTokenizer, tiktoken.SpecialTokens);
 
                 IReadOnlyDictionary<ReadOnlyMemory<byte>, int> encoder = tiktoken.Encoder;
-                IReadOnlyDictionary<ReadOnlyMemory<byte>, int> externalEncoder = (externalTokenizer.Model as Tiktoken)!.Encoder;
+                IReadOnlyDictionary<ReadOnlyMemory<byte>, int> externalEncoder = (externalTokenizer as Tiktoken)!.Encoder;
 
                 Assert.Equal(externalEncoder.Count, encoder.Count);
                 foreach (KeyValuePair<ReadOnlyMemory<byte>, int> kvp in encoder)
@@ -135,13 +135,17 @@ namespace Microsoft.ML.Tokenizers.Tests
             Assert.Equal(new List<int>() { 9906, 4435 }, encoded);
             Assert.Equal(text, tokenizer.Decode(encoded.ToArray())!);
 
-            EncodingResult result = tokenizer.Encode(text);
+            IReadOnlyList<Token> result = tokenizer.Encode(text, out string? normalizedString);
             int idsCount = tokenizer.CountTokens(text);
-            Assert.Equal(encoded, result.Ids);
-            Assert.Equal(new string[] { "Hello", " World" }, result.Tokens);
-            Assert.Equal(new List<(int, int)> { (0, 5), (5, 6) }, result.Offsets);
+
+            int[] ids = result.Select(token => token.Id).ToArray();
+            string[] tokens = result.Select(token => token.Value).ToArray();
+            (int, int)[] offsets = result.Select(token => token.Offset).ToArray();
+            Assert.Equal(encoded, ids);
+            Assert.Equal(new string[] { "Hello", " World" }, tokens);
+            Assert.Equal(new List<(int, int)> { (0, 5), (5, 6) }, offsets);
             Assert.Equal(encoded.Count, idsCount);
-            Assert.Equal(encoded, result.Ids);
+            Assert.Equal(encoded, ids);
 
             TestGPT4Tokenizer(tokenizer);
         }
@@ -154,13 +158,18 @@ namespace Microsoft.ML.Tokenizers.Tests
             Assert.Equal(new List<int>() { 100264, 9906, 4435, 100265 }, encoded);
             Assert.Equal(text, GPT4.Decode(encoded.ToArray()));
 
-            EncodingResult result = GPT4.Encode(text);
+            IReadOnlyList<Token> result = GPT4.Encode(text, out string? normalizedString);
             int idsCount = GPT4.CountTokens(text);
-            Assert.Equal(encoded, result.Ids);
-            Assert.Equal(new string[] { "<|im_start|>", "Hello", " World", "<|im_end|>" }, result.Tokens);
-            Assert.Equal(new List<(int, int)> { (0, 12), (12, 5), (17, 6), (23, 10) }, result.Offsets);
+
+            int[] ids = result.Select(token => token.Id).ToArray();
+            string[] tokens = result.Select(token => token.Value).ToArray();
+            (int, int)[] offsets = result.Select(token => token.Offset).ToArray();
+
+            Assert.Equal(encoded, ids);
+            Assert.Equal(new string[] { "<|im_start|>", "Hello", " World", "<|im_end|>" }, tokens);
+            Assert.Equal(new List<(int, int)> { (0, 12), (12, 5), (17, 6), (23, 10) }, offsets);
             Assert.Equal(encoded.Count, idsCount);
-            Assert.Equal(encoded, result.Ids);
+            Assert.Equal(encoded, ids);
         }
 
         private void TestGPT4Tokenizer(Tokenizer gpt4Tokenizer)
@@ -192,12 +201,16 @@ namespace Microsoft.ML.Tokenizers.Tests
             string? decoded = GPT4.Decode(encoded.ToArray());
             Assert.Equal(text, decoded);
 
-            EncodingResult result = GPT4.Encode(text);
+            IReadOnlyList<Token> result = GPT4.Encode(text, out string? normalizedString);
+            int[] ids = result.Select(token => token.Id).ToArray();
+            string[] tokens = result.Select(token => token.Value).ToArray();
+            (int, int)[] offsets = result.Select(token => token.Offset).ToArray();
+
             int idsCount = GPT4.CountTokens(text);
-            Assert.Equal(encoded, result.Ids);
+            Assert.Equal(encoded, ids);
             Assert.Equal(encoded.Count, idsCount);
-            Assert.Equal(new string[] { "<|im_start|>", "Hello", "<|im_end|>", " World" }, result.Tokens);
-            Assert.Equal(new List<(int, int)> { (0, 12), (12, 5), (17, 10), (27, 6) }, result.Offsets);
+            Assert.Equal(new string[] { "<|im_start|>", "Hello", "<|im_end|>", " World" }, tokens);
+            Assert.Equal(new List<(int, int)> { (0, 12), (12, 5), (17, 10), (27, 6) }, offsets);
         }
 
         [Fact]
@@ -207,12 +220,10 @@ namespace Microsoft.ML.Tokenizers.Tests
             IReadOnlyList<int> encoded = GPT4.EncodeToIds(text);
             Assert.Empty(encoded);
 
-            EncodingResult result = GPT4.Encode(text);
+            IReadOnlyList<Token> result = GPT4.Encode(text, out string? normalizedString);
             int idsCount = GPT4.CountTokens(text);
-            Assert.Empty(result.Ids);
-            Assert.Empty(result.Tokens);
-            Assert.Empty(result.Offsets);
-            Assert.Equal(result.Ids.Count, idsCount);
+            Assert.Empty(result);
+            Assert.Equal(0, idsCount);
         }
 
         [Fact]
@@ -224,11 +235,11 @@ namespace Microsoft.ML.Tokenizers.Tests
             Assert.Equal(new List<int>() { 100264, 9906, 2928, 99834, 4435, 100265 }, encoded);
             Assert.Equal(text, GPT4.Decode(encoded.ToArray()));
 
-            EncodingResult result = GPT4.Encode(text);
-            Assert.Equal(encoded, result.Ids);
+            IReadOnlyList<Token> result = GPT4.Encode(text, out string? normalizedString);
+            Assert.Equal(encoded, result.Select(token => token.Id).ToArray());
             Assert.Equal(encoded.Count, idsCount);
-            Assert.Equal(new string[] { "<|im_start|>", "Hello", " ⭐", "", " World", "<|im_end|>" }, result.Tokens);
-            Assert.Equal(new List<(int, int)> { (0, 12), (12, 5), (17, 2), (19, 0), (19, 6), (25, 10) }, result.Offsets);
+            Assert.Equal(new string[] { "<|im_start|>", "Hello", " ⭐", "", " World", "<|im_end|>" }, result.Select(token => token.Value).ToArray());
+            Assert.Equal(new List<(int, int)> { (0, 12), (12, 5), (17, 2), (19, 0), (19, 6), (25, 10) }, result.Select(token => token.Offset).ToArray());
         }
 
         [Fact]
@@ -310,9 +321,12 @@ namespace Microsoft.ML.Tokenizers.Tests
         [Theory]
         [InlineData("gpt-4")]
         [InlineData("gpt-4-")]
+        [InlineData("gpt-3.5-")]
         [InlineData("gpt-3.5-turbo")]
         [InlineData("gpt-3.5-turbo-")]
         [InlineData("gpt-3.5-turbo-16k")]
+        [InlineData("gpt-35")]
+        [InlineData("gpt-35-")]
         [InlineData("gpt-35-turbo")]
         [InlineData("gpt-35-turbo-16k")]
         [InlineData("gpt-35-turbo-")]
@@ -351,7 +365,7 @@ namespace Microsoft.ML.Tokenizers.Tests
         public void TestAllSupportedModelNames(string modelName)
         {
             Tokenizer tokenizer = Tokenizer.CreateTiktokenForModel(modelName);
-            Assert.NotNull(tokenizer.Model);
+            Assert.True(tokenizer is Tiktoken);
             Assert.NotNull(tokenizer.PreTokenizer);
         }
 
@@ -363,7 +377,7 @@ namespace Microsoft.ML.Tokenizers.Tests
         public void TestAllSupportedEncodingNames(string encodingName)
         {
             Tokenizer tokenizer = Tokenizer.CreateTiktokenForEncoding(encodingName);
-            Assert.NotNull(tokenizer.Model);
+            Assert.True(tokenizer is Tiktoken);
             Assert.NotNull(tokenizer.PreTokenizer);
 
             string modelName = encodingName.ToLowerInvariant() switch
@@ -377,15 +391,16 @@ namespace Microsoft.ML.Tokenizers.Tests
 
             Tokenizer tokenizer1 = Tokenizer.CreateTiktokenForModel(modelName);
 
-            Tiktoken? model1 = tokenizer.Model as Tiktoken;
-            Tiktoken? model2 = tokenizer1.Model as Tiktoken;
-            Assert.NotNull(model1);
-            Assert.NotNull(model2);
+            Assert.True(tokenizer is Tiktoken);
+            Assert.True(tokenizer1 is Tiktoken);
 
-            Assert.Equal(model2.Encoder, model1.Encoder);
-            Assert.Equal(model2.Decoder, model1.Decoder);
-            Assert.Equal(model2.SpecialTokens, model1.SpecialTokens);
-            Assert.Equal(model2.Vocab, model1.Vocab);
+            Tiktoken tiktoken = (tokenizer as Tiktoken)!;
+            Tiktoken tiktoken1 = (tokenizer1 as Tiktoken)!;
+
+            Assert.Equal(tiktoken1.Encoder, tiktoken.Encoder);
+            Assert.Equal(tiktoken1.Decoder, tiktoken.Decoder);
+            Assert.Equal(tiktoken1.SpecialTokens, tiktoken.SpecialTokens);
+            Assert.Equal(tiktoken1.Vocab, tiktoken.Vocab);
         }
 
         [Fact]
@@ -408,11 +423,99 @@ namespace Microsoft.ML.Tokenizers.Tests
             RemoteExecutor.Invoke(static (name) =>
             {
                 Tokenizer tokenizer = Tokenizer.CreateTiktokenForModel(name);
-                Assert.NotNull(tokenizer.Model);
+                Assert.True(tokenizer is Tiktoken);
                 Assert.NotNull(tokenizer.PreTokenizer);
             }, modelName).Dispose();
         }
 
+        public static IEnumerable<object?[]> TokenizerTestData
+        {
+            get
+            {
+                // string to tokenize, produced tokens, the token offsets
+                yield return new object?[]
+                {
+                    "the brown fox jumped over the lazy dog!",
+                    new string[] { "the", " brown", " fox", " jumped", " over", " the", " lazy", " dog", "!" },
+                    new (int Index, int Length)[] { (0, 3), (3, 6), (9, 4), (13, 7), (20, 5), (25, 4), (29, 5), (34, 4), (38, 1) },
+                    new int[] { 1820, 14198, 39935, 27096, 927, 279, 16053, 5679, 0 }
+                };
+                yield return new object?[]
+                {
+                    "he traveled to Egypt during the summer, the weather was hot and ammunition." ,
+                    new string[] { "he", " traveled", " to", " Egypt", " during", " the", " summer", ",", " the", " weather", " was", " hot", " and", " ammunition", "." },
+                    new (int Index, int Length)[] { (0, 2), (2, 9), (11, 3), (14, 6), (20, 7), (27, 4), (31, 7), (38, 1), (39, 4), (43, 8), (51, 4), (55, 4), (59, 4), (63, 11), (74, 1) },
+                    new int[] { 383, 31796, 311, 15212, 2391, 279, 7474, 11, 279, 9282, 574, 4106, 323, 37768, 13 }
+                };
+                yield return new object?[]
+                {
+                    "She played many games and she felt exhausted afterward",
+                    new string[] { "She", " played", " many", " games", " and", " she", " felt", " exhausted", " afterward" },
+                    new (int Index, int Length)[] { (0, 3), (3, 7), (10, 5), (15, 6), (21, 4), (25, 4), (29, 5), (34, 10), (44, 10) },
+                    new int[] { 8100, 6476, 1690, 3953, 323, 1364, 6612, 39019, 49043 }
+                };
+                yield return new object?[]
+                {
+                    "Hello, y'all! How are you 😁 ?",
+                    new string[] { "Hello", ",", " y", "'all", "!", " How", " are", " you", " 😁", "", " ?" },
+                    new (int Index, int Length)[] { (0, 5), (5, 1), (6, 2), (8, 4), (12, 1), (13, 4), (17, 4), (21, 4), (25, 3), (28, 0), (28, 2) },
+                    new int[] { 9906, 11, 379, 65948, 0, 2650, 527, 499, 27623, 223, 949 }
+                };
+            }
+        }
+
+        [Theory]
+        [MemberData(nameof(TokenizerTestData))]
+        public void TestTokenizerEncoding(string text, string[] expectedTokens, (int Index, int Length)[] expectedOffsets, int[] expectedIds)
+        {
+            Tokenizer tokenizer = GPT4;
+
+            IReadOnlyList<Token> encoding = tokenizer.Encode(text, out _);
+            IReadOnlyList<Token> encoding1 = tokenizer.Encode(text.AsSpan(), out _);
+
+            Assert.Equal(expectedTokens, encoding.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding.Select(t => t.Id).ToArray());
+
+            Assert.Equal(expectedTokens, encoding1.Select(t => t.Value).ToArray());
+            Assert.Equal(expectedOffsets, encoding1.Select(t => t.Offset).ToArray());
+            Assert.Equal(expectedIds, encoding1.Select(t => t.Id).ToArray());
+
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan()));
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text, expectedIds.Length, out string? normalizedString, out int length));
+            Assert.Null(normalizedString);
+            Assert.Equal(text.Length, length);
+            Assert.Equal(expectedIds, tokenizer.EncodeToIds(text.AsSpan(), expectedIds.Length, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            Assert.Equal(text.Length, length);
+
+            Assert.Equal(expectedIds.Take(expectedIds.Length - 4), tokenizer.EncodeToIds(text, expectedIds.Length - 4, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            int expectedLength = expectedOffsets[expectedOffsets.Length - 5].Index + expectedOffsets[expectedOffsets.Length - 5].Length;
+            Assert.Equal(expectedLength, length);
+            Assert.Equal(expectedIds.Take(expectedIds.Length - 4), tokenizer.EncodeToIds(text.AsSpan(), expectedIds.Length - 4, out normalizedString, out length));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedLength, length);
+
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text));
+            Assert.Equal(expectedIds.Length, tokenizer.CountTokens(text.AsSpan()));
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 4].Index + expectedOffsets[expectedOffsets.Length - 4].Length, tokenizer.IndexOfTokenCount(text, expectedIds.Length - 3, out normalizedString, out int tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedIds.Length - 3, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 4].Index + expectedOffsets[expectedOffsets.Length - 4].Length, tokenizer.IndexOfTokenCount(text.AsSpan(), expectedIds.Length - 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(expectedIds.Length - 3, tokenCount);
+
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 3].Index, tokenizer.LastIndexOfTokenCount(text, 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(3, tokenCount);
+            Assert.Equal(expectedOffsets[expectedOffsets.Length - 3].Index, tokenizer.LastIndexOfTokenCount(text.AsSpan(), 3, out normalizedString, out tokenCount));
+            Assert.Null(normalizedString);
+            Assert.Equal(3, tokenCount);
+        }
+
         // Test running copy the test data files to the output folder but sometimes the file content is mutated replacing '\n' with '\r\n'.
         // This method reads the file and removes the extra inserted '\r' characters. Having '\r' in the file content will cause the tests to fail.
         private string ReadAndSanitizeFile(string path)

test/Microsoft.ML.Tokenizers.Tests/TokenizerTests.cs

@@ -26,12 +26,12 @@ namespace Microsoft.ML.Tokenizers.Tests
 
             for (int i = 1; i <= fullIdsList.Count; i++)
             {
-                int index1 = tokenizer.IndexOfTokenCount(input, maxTokenCount: i, out string processedText1, out int tokenCount1);
-                int index2 = tokenizer.LastIndexOfTokenCount(input, maxTokenCount: i, out string processedText2, out int tokenCount2);
-                IReadOnlyList<int> partialIdsList = tokenizer.EncodeToIds(input, maxTokenCount: i, out string processedText, out int textLength);
+                int index1 = tokenizer.IndexOfTokenCount(input, maxTokenCount: i, out string? processedText1, out int tokenCount1);
+                int index2 = tokenizer.LastIndexOfTokenCount(input, maxTokenCount: i, out string? processedText2, out int tokenCount2);
+                IReadOnlyList<int> partialIdsList = tokenizer.EncodeToIds(input, maxTokenCount: i, out string? processedText, out int textLength);
 
-                Assert.True(textLength <= processedText.Length);
-                Assert.True(tokenizer.Normalizer is not null || processedText == input);
+                Assert.True(processedText is null || textLength <= processedText.Length);
+                Assert.True(tokenizer.Normalizer is not null || processedText is null);
 
                 Assert.Equal(fullIdsList.Take(partialIdsList.Count), partialIdsList);
 
@@ -42,14 +42,13 @@ namespace Microsoft.ML.Tokenizers.Tests
                 // In this case, we'll get index1 equal to zero and nothing really will need to be tested.
                 if (tokenCount1 > 0 && index1 > 0)
                 {
-                    string prefixString = processedText1.Substring(0, index1);
+                    string prefixString = (processedText1 ?? input).Substring(0, index1);
 
-                    if (tokenizer.Model is SentencePieceBpe)
+                    if (tokenizer is SentencePieceBpe)
                     {
                         // SentencePieceBpe model normalize the text and insert more characters.
                         // We call the model directly to bypass the normalization step
-                        prefixIds = new List<int>();
-                        tokenizer.Model.EncodeToIds(prefixString.AsSpan(), (prefixIds as IList<int>)!, out _);
+                        prefixIds = tokenizer.EncodeToIds(prefixString.AsSpan(), considerNormalization: false);
                     }
                     else
                     {
@@ -61,14 +60,13 @@ namespace Microsoft.ML.Tokenizers.Tests
 
                 if (tokenCount2 > 0)
                 {
-                    string suffixString = processedText2.Substring(index2);
+                    string suffixString = (processedText2 ?? input).Substring(index2);
 
-                    if (tokenizer.Model is SentencePieceBpe)
+                    if (tokenizer is SentencePieceBpe)
                     {
                         // SentencePieceBpe model normalize the text and insert more characters.
                         // We call the model directly to bypass the normalization step
-                        suffixIds = new List<int>();
-                        tokenizer.Model.EncodeToIds(suffixString.AsSpan(), (suffixIds as IList<int>)!, out _);
+                        suffixIds = tokenizer.EncodeToIds(suffixString.AsSpan(), considerNormalization: false);
                         if (i < fullIdsList.Count)
                         {
                             suffixIds = suffixIds.Skip(1).ToList(); // Skip the start of sentence token <s>
@@ -85,12 +83,13 @@ namespace Microsoft.ML.Tokenizers.Tests
 
                 if (i == fullIdsList.Count)
                 {
-                    if (index1 != processedText1.Length)
+                    string s = processedText1 ?? input;
+                    if (index1 != s.Length)
                     {
                         // It's possible that the remaining text on the left doesn't produce any tokens, as in the case of BPE,
                         // where the pre-tokenizer removes spaces and the left text consists entirely of spaces.
-                        Assert.True(index1 < processedText1.Length);
-                        Assert.Equal(0, tokenizer.CountTokens(processedText1.Substring(index1)));
+                        Assert.True(index1 < s.Length);
+                        Assert.Equal(0, tokenizer.CountTokens(s.Substring(index1)));
                     }
 
                     if (index2 != 0)
@@ -98,7 +97,7 @@ namespace Microsoft.ML.Tokenizers.Tests
                         // It's possible that the remaining text on the right doesn't produce any tokens, as in the case of BPE,
                         // where the pre-tokenizer removes spaces and the left text consists entirely of spaces.
                         Assert.True(index2 > 0);
-                        Assert.Equal(0, tokenizer.CountTokens(processedText1.Substring(0, index2)));
+                        Assert.Equal(0, tokenizer.CountTokens(s.Substring(0, index2)));
                     }
 
                     Assert.Equal(fullIdsList, prefixIds);
@@ -106,13 +105,15 @@ namespace Microsoft.ML.Tokenizers.Tests
                 }
             }
 
+            Assert.Equal(0, tokenizer.IndexOfTokenCount((string)null!, maxTokenCount: 10, out _, out _));
+            Assert.Equal(0, tokenizer.LastIndexOfTokenCount((string)null!, maxTokenCount: 10, out _, out _));
+            Assert.Equal(0, tokenizer.IndexOfTokenCount(Span<char>.Empty, maxTokenCount: 10, out _, out _));
+            Assert.Equal(0, tokenizer.LastIndexOfTokenCount(Span<char>.Empty, maxTokenCount: 10, out _, out _));
+
             Assert.Throws<ArgumentOutOfRangeException>(() => tokenizer.IndexOfTokenCount(input, maxTokenCount: 0, out _, out _));
             Assert.Throws<ArgumentOutOfRangeException>(() => tokenizer.IndexOfTokenCount(input, maxTokenCount: -1, out _, out _));
             Assert.Throws<ArgumentOutOfRangeException>(() => tokenizer.LastIndexOfTokenCount(input, maxTokenCount: 0, out _, out _));
             Assert.Throws<ArgumentOutOfRangeException>(() => tokenizer.LastIndexOfTokenCount(input, maxTokenCount: -1, out _, out _));
-
-            Assert.Throws<ArgumentNullException>(() => tokenizer.IndexOfTokenCount(null!, maxTokenCount: 10, out _, out _));
-            Assert.Throws<ArgumentNullException>(() => tokenizer.LastIndexOfTokenCount(null!, maxTokenCount: 10, out _, out _));
         }
     }
 }