ac75faa0cc
CI / build-and-test (push) Has been cancelled
- 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
155 lines
8.2 KiB
Swift
155 lines
8.2 KiB
Swift
import XCTest
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@testable import MarkBase
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final class G12BTokenizerTests: XCTestCase {
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func testTokenizerLoading() throws {
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print("\n═══════════════════════════════════════")
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print(" Tokenizer Loading Test")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/.cache/huggingface/hub/models--mlx-community--gemma-4-12B-it-4bit/snapshots/73bcf09092aa277861d5a191b989b666f7f32e8f"
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print("Step 1: Check tokenizer files...")
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let tokenizerJsonPath = modelDir + "/tokenizer.json"
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let tokenizerModelPath = modelDir + "/tokenizer.model"
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let hasTokenizerJson = FileManager.default.fileExists(atPath: tokenizerJsonPath)
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let hasTokenizerModel = FileManager.default.fileExists(atPath: tokenizerModelPath)
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print(" tokenizer.json: \(hasTokenizerJson ? "✓ Found" : "✗ Not found")")
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print(" tokenizer.model: \(hasTokenizerModel ? "✓ Found" : "✗ Not found")")
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XCTAssert(hasTokenizerJson || hasTokenizerModel, "Should have at least one tokenizer file")
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print("\nStep 2: Load tokenizer...")
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let tokenizer = try TokenizerFactory.load(modelDir: modelDir)
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print(" ✓ Tokenizer loaded")
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print(" Type: \(type(of: tokenizer))")
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print(" Vocab size: \(tokenizer.vocabSize)")
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print(" BOS token: \(tokenizer.bosTokenId)")
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print(" EOS token: \(tokenizer.eosTokenId)")
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XCTAssertGreaterThan(tokenizer.vocabSize, 0, "Vocab size should be > 0")
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print("\n═══════════════════════════════════════")
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print("✓ Tokenizer loading test passed")
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print("═══════════════════════════════════════\n")
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}
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func testEncodingDecoding() throws {
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print("\n═══════════════════════════════════════")
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print(" Encoding/Decoding Test")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/.cache/huggingface/hub/models--mlx-community--gemma-4-12B-it-4bit/snapshots/73bcf09092aa277861d5a191b989b666f7f32e8f"
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let tokenizer = try TokenizerFactory.load(modelDir: modelDir)
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print("Step 1: Test encode...")
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let testText = "Hello world"
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let tokens = tokenizer.encode(text: testText)
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print(" Input: \(testText)")
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print(" Tokens: \(tokens)")
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print(" Token count: \(tokens.count)")
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XCTAssertGreaterThan(tokens.count, 2, "Should have at least BOS + EOS + content")
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XCTAssertEqual(tokens.first, tokenizer.bosTokenId, "First token should be BOS")
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XCTAssertEqual(tokens.last, tokenizer.eosTokenId, "Last token should be EOS")
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print("\nStep 2: Test decode...")
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let decodedText = tokenizer.decode(tokens: tokens)
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print(" Tokens: \(tokens)")
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print(" Decoded: \(decodedText)")
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// Note: May not be exact match due to simplified implementation
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XCTAssertGreaterThan(decodedText.count, 0, "Decoded text should not be empty")
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print("\nStep 3: Test roundtrip...")
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let reencodedTokens = tokenizer.encode(text: decodedText)
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let redecodedText = tokenizer.decode(tokens: reencodedTokens)
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print(" Original: \(testText)")
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print(" Roundtrip: \(redecodedText)")
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print("\n═══════════════════════════════════════")
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print("✓ Encoding/decoding test passed")
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print("═══════════════════════════════════════\n")
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}
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func testSpecialTokens() throws {
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print("\n═══════════════════════════════════════")
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print(" Special Tokens Test")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/.cache/huggingface/hub/models--mlx-community--gemma-4-12B-it-4bit/snapshots/73bcf09092aa277861d5a191b989b666f7f32e8f"
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let tokenizer = try TokenizerFactory.load(modelDir: modelDir)
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print("Step 1: Verify special token IDs...")
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print(" BOS token ID: \(tokenizer.bosTokenId)")
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print(" EOS token ID: \(tokenizer.eosTokenId)")
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print(" PAD token ID: \(tokenizer.padTokenId)")
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XCTAssertGreaterThanOrEqual(tokenizer.bosTokenId, 0, "BOS ID should be valid")
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XCTAssertGreaterThanOrEqual(tokenizer.eosTokenId, 0, "EOS ID should be valid")
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XCTAssertGreaterThanOrEqual(tokenizer.padTokenId, 0, "PAD ID should be valid")
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print("\nStep 2: Test with empty text...")
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let emptyTokens = tokenizer.encode(text: "")
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print(" Empty input tokens: \(emptyTokens)")
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XCTAssertEqual(emptyTokens, [tokenizer.bosTokenId, tokenizer.eosTokenId], "Empty text should be BOS + EOS only")
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print("\n═══════════════════════════════════════")
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print("✓ Special tokens test passed")
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print("═══════════════════════════════════════\n")
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}
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func testTokenizerWithModel() throws {
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print("\n═══════════════════════════════════════")
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print(" Tokenizer + Model Integration")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/.cache/huggingface/hub/models--mlx-community--gemma-4-12B-it-4bit/snapshots/73bcf09092aa277861d5a191b989b666f7f32e8f"
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print("Step 1: Load tokenizer and model...")
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let engine = try MarkBaseEngine(autoCompile: true)
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let model = try E4BModel(modelDir: modelDir, engine: engine, maxContextLength: 512)
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let tokenizer = try TokenizerFactory.load(modelDir: modelDir)
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print(" ✓ Model loaded")
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print(" ✓ Tokenizer loaded")
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print(" Model vocab size: \(model.vocabSize)")
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print(" Tokenizer vocab size: \(tokenizer.vocabSize)")
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// Note: vocab sizes should match (both 262144 for Gemma-4)
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XCTAssertEqual(model.vocabSize, tokenizer.vocabSize, "Model and tokenizer vocab should match")
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print("\nStep 2: Generate tokens from text...")
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let prompt = "Hello"
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let tokens = tokenizer.encode(text: prompt)
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print(" Prompt: \(prompt)")
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print(" Tokens: \(tokens)")
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// Generate from first token
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let firstToken = tokens[1] // Skip BOS
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let logits = try model.forward(tokenId: firstToken, position: 0)
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print(" Generated logits for token \(firstToken)")
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print(" Logits count: \(logits.count)")
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// Find next token (greedy)
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var maxLogit = logits[0]
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var nextTokenId = 0
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for i in 1..<logits.count {
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if logits[i] > maxLogit {
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maxLogit = logits[i]
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nextTokenId = i
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}
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}
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let nextTokenText = tokenizer.decode(tokens: [nextTokenId])
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print(" Next token: \(nextTokenId)")
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print(" Next token text: \(nextTokenText)")
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print("\n═══════════════════════════════════════")
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print("✓ Tokenizer + Model integration passed")
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print("═══════════════════════════════════════\n")
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}
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} |