Fix Swift 6 concurrency errors

Sources/Tokenizers/BPETokenizer.swift

@@ -10,7 +10,7 @@ import Foundation
 import Hub
 
 /// A pair of byte/token strings used in Byte-Pair Encoding (BPE) merge operations.
-struct BytePair: Hashable {
+struct BytePair: Hashable, Sendable {
     let a: String
     let b: String
     init(_ a: String, _ b: String) {
@@ -38,7 +38,7 @@ struct BytePair: Hashable {
 /// BPE tokenizers learn to merge the most frequently occurring pairs of characters
 /// or character sequences. This implementation supports various BPE-based models
 /// including GPT-2, RoBERTa, and other transformer models.
-class BPETokenizer: PreTrainedTokenizerModel {
+class BPETokenizer: PreTrainedTokenizerModel, @unchecked Sendable {
     let bpeRanks: [BytePair: Int]
     private let tokensToIds: [NSString: Int]
     private let idsToTokens: [Int: NSString]

Sources/Tokenizers/BertTokenizer.swift

@@ -14,7 +14,7 @@ import Hub
 /// This tokenizer performs basic tokenization (whitespace and punctuation splitting)
 /// followed by WordPiece subword tokenization, which is the approach used by BERT
 /// and related models.
-public class BertTokenizer {
+public final class BertTokenizer: Sendable {
     private let basicTokenizer: BasicTokenizer
     private let wordpieceTokenizer: WordpieceTokenizer
     private let maxLen = 512
@@ -27,16 +27,16 @@ public class BertTokenizer {
     private let ids_to_tokens: [Int: String]
 
     /// The beginning-of-sequence token string, if defined.
-    public var bosToken: String?
+    public let bosToken: String?
 
     /// The numeric ID of the beginning-of-sequence token, if defined.
-    public var bosTokenId: Int?
+    public let bosTokenId: Int?
 
     /// The end-of-sequence token string, if defined.
-    public var eosToken: String?
+    public let eosToken: String?
 
     /// The numeric ID of the end-of-sequence token, if defined.
-    public var eosTokenId: Int?
+    public let eosTokenId: Int?
 
     /// Whether consecutive unknown tokens should be fused together.
     public let fuseUnknownTokens: Bool
@@ -225,7 +225,7 @@ extension BertTokenizer: PreTrainedTokenizerModel {
     }
 }
 
-class BasicTokenizer {
+final class BasicTokenizer: Sendable {
     let doLowerCase: Bool
 
     init(doLowerCase: Bool = true) {
@@ -291,7 +291,7 @@ private extension Character {
     }
 }
 
-class WordpieceTokenizer {
+final class WordpieceTokenizer: Sendable {
     let unkToken = "[UNK]"
     private let maxInputCharsPerWord = 100
     private let vocab: [String: Int]

Sources/Tokenizers/Tokenizer.swift

@@ -215,7 +215,7 @@ public enum ChatTemplateArgument {
 ///
 /// This is the main protocol that defines all tokenizer operations, including text processing,
 /// chat template application, and special token handling.
-public protocol Tokenizer {
+public protocol Tokenizer: Sendable {
     /// Tokenizes the input text into a sequence of tokens.
     ///
     /// - Parameter text: The input text to tokenize
@@ -451,7 +451,7 @@ let specialTokenAttributes: [String] = [
 /// This class provides a complete tokenizer implementation that can be initialized from
 /// Hugging Face Hub configuration files and supports all standard tokenization operations
 /// including chat template application, normalization, pre-tokenization, and post-processing.
-public class PreTrainedTokenizer: Tokenizer {
+public class PreTrainedTokenizer: @unchecked Sendable, Tokenizer {
     let model: TokenizingModel
 
     public var bosToken: String? { model.bosToken }
@@ -477,6 +477,9 @@ public class PreTrainedTokenizer: Tokenizer {
     /// Cache for compiled Jinja templates keyed by their literal template string
     private var compiledChatTemplateCache: [String: Template] = [:]
 
+    /// Lock to protect the compiled chat template cache from concurrent access
+    private let cacheLock = NSLock()
+
     /// Initializes a tokenizer from Hugging Face configuration files.
     ///
     /// - Parameters:
@@ -531,10 +534,26 @@ public class PreTrainedTokenizer: Tokenizer {
     }
 
     private func compiledTemplate(for templateString: String) throws -> Template {
+        // Fast path: check cache under lock
+        cacheLock.lock()
         if let cached = compiledChatTemplateCache[templateString] {
+            cacheLock.unlock()
             return cached
         }
+        cacheLock.unlock()
+
+        // Compile template outside of lock to avoid holding lock during expensive operation
         let compiled = try Template(templateString)
+
+        // Insert into cache under lock (using double-checked locking pattern)
+        cacheLock.lock()
+        defer { cacheLock.unlock() }
+
+        // Check again in case another thread compiled the same template
+        if let cached = compiledChatTemplateCache[templateString] {
+            return cached
+        }
+
         compiledChatTemplateCache[templateString] = compiled
         return compiled
     }
@@ -905,7 +924,7 @@ public extension AutoTokenizer {
 
 // MARK: - Tokenizer model classes
 
-class T5Tokenizer: UnigramTokenizer {}
+class T5Tokenizer: UnigramTokenizer, @unchecked Sendable {}
 
 // MARK: - PreTrainedTokenizer classes
 
@@ -954,7 +973,7 @@ func maybeUpdatePostProcessor(tokenizerConfig: Config, processorConfig: Config?)
 }
 
 /// See https://github.com/xenova/transformers.js/blob/1a9964fb09b8f54fcbeac46dc6aae8d76795809d/src/tokenizers.js#L3203 for these exceptions
-class LlamaPreTrainedTokenizer: PreTrainedTokenizer {
+class LlamaPreTrainedTokenizer: PreTrainedTokenizer, @unchecked Sendable {
     let isLegacy: Bool
 
     required init(tokenizerConfig: Config, tokenizerData: Config, strict: Bool = true) throws {

Sources/Tokenizers/UnigramTokenizer.swift

@@ -14,7 +14,7 @@ import Hub
 /// Unigram tokenizers use a probabilistic approach where each token has a score,
 /// and the tokenization process finds the most probable segmentation of the input text.
 /// This is commonly used in models like T5 and XLM-RoBERTa.
-class UnigramTokenizer: PreTrainedTokenizerModel {
+class UnigramTokenizer: PreTrainedTokenizerModel, @unchecked Sendable {
     /// A token with its associated score in the Unigram model.
     struct SentencePieceToken {
         var token: String

Tests/TokenizersTests/BertTokenizerTests.swift

@@ -83,6 +83,7 @@ private enum Squad {
 
 // MARK: -
 
+@MainActor
 private let bertTokenizer: BertTokenizer = {
     let vocab = {
         let url = Bundle.module.url(forResource: "bert-vocab", withExtension: "txt")!
@@ -101,6 +102,7 @@ private let bertTokenizer: BertTokenizer = {
 // MARK: -
 
 @Suite("BERT Tokenizer Tests")
+@MainActor
 struct BertTokenizerTests {
     @Test("Basic tokenizer correctly tokenizes text")
     func testBasicTokenizer() {

Tests/TokenizersTests/ChatTemplateTests.swift

@@ -19,6 +19,7 @@ struct ChatTemplateTests {
         ]
     ]
 
+    @MainActor
     static let phiTokenizerTask = Task {
         try await AutoTokenizer.from(pretrained: "microsoft/Phi-3-mini-128k-instruct")
     }
@@ -27,6 +28,7 @@ struct ChatTemplateTests {
         try await phiTokenizerTask.value
     }
 
+    @MainActor
     static let tokenizerWithTemplateArrayTask = Task {
         try await AutoTokenizer.from(pretrained: "mlx-community/Mistral-7B-Instruct-v0.3-4bit")
     }