Initial commit: E4B-MarkBase model integration with passing tests
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- E4B-MarkBase model (42 layers, 4.4GB) loaded successfully
- All Phase 1-6 tests passed (model loading, forward pass, vision/audio towers, token generation, performance)
- All stress tests passed (5/5 in 127.6s)
  - Concurrent inference
  - Memory stress (67.5 tok/s, 0 NaN)
  - Continuous generation
  - Batch processing
  - Long-running stability
- Swift Metal inference engine with multimodal support
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MarkBase Admin
2026-06-23 18:12:35 +08:00
commit ac75faa0cc
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import Foundation
//
// Tokenizer Protocol - Unified interface for all tokenizers
//
/// Tokenizer protocol for text-to-token and token-to-text conversion
public protocol Tokenizer: Sendable {
/// Encode text to token IDs
func encode(text: String) -> [Int]
/// Decode token IDs to text
func decode(tokens: [Int]) -> String
/// Vocabulary size
var vocabSize: Int { get }
/// Special token IDs
var bosTokenId: Int { get }
var eosTokenId: Int { get }
var eosTokenIds: Set<Int> { get }
var padTokenId: Int { get }
/// Raw token string for a given ID (used by StreamingDecoder)
func rawToken(for id: Int) -> String?
}
//
// Special Tokens Configuration
//
public struct SpecialTokens: Sendable {
public let bosToken: String
public let eosToken: String
public let padToken: String
public let unkToken: String
public init(
bosToken: String = "<bos>",
eosToken: String = "<eos>",
padToken: String = "<pad>",
unkToken: String = "<unk>"
) {
self.bosToken = bosToken
self.eosToken = eosToken
self.padToken = padToken
self.unkToken = unkToken
}
// Gemma-4 specific tokens
public static let gemma4 = SpecialTokens(
bosToken: "<bos>",
eosToken: "<eos>",
padToken: "<pad>",
unkToken: "<unk>"
)
}
//
// Tokenizer Error
//
public enum TokenizerError: Error, LocalizedError {
case modelNotFound(String)
case invalidModelFormat
case encodingFailed(String)
case decodingFailed([Int])
case vocabMissing(String)
public var errorDescription: String? {
switch self {
case .modelNotFound(let path):
return "Tokenizer model not found at: \(path)"
case .invalidModelFormat:
return "Invalid tokenizer model format"
case .encodingFailed(let text):
return "Failed to encode text: \(text)"
case .decodingFailed(let tokens):
return "Failed to decode tokens: \(tokens)"
case .vocabMissing(let token):
return "Token not in vocabulary: \(token)"
}
}
}
//
// Tokenizer Factory
//
public final class TokenizerFactory: @unchecked Sendable {
/// Load tokenizer from model directory
public static func load(modelDir: String) throws -> Tokenizer {
// Try tokenizer.json first (HuggingFace format)
let tokenizerJsonPath = modelDir + "/tokenizer.json"
if FileManager.default.fileExists(atPath: tokenizerJsonPath) {
return try BPETokenizer(jsonPath: tokenizerJsonPath)
}
// Try .model file (SentencePiece format)
let modelPath = modelDir + "/tokenizer.model"
if FileManager.default.fileExists(atPath: modelPath) {
return try SentencePieceTokenizer(modelPath: modelPath)
}
// Fallback to simple tokenizer (for testing)
print("Warning: No tokenizer found, using simple tokenizer")
return SimpleTokenizer()
}
}