MarkBase Admin
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
79 lines
3.9 KiB
Swift
79 lines
3.9 KiB
Swift
import XCTest
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@testable import MarkBase
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final class MoEForwardTests: XCTestCase {
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func test26BA4BModelLoading() throws {
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print("\n═══════════════════════════════════════")
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print(" 26B-A4B MoE Model Loading Test")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/MarkBaseEngine/models/gemma-4-26b-a4b-it-4bit"
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print("Step 1: Initialize Metal engine...")
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let engine = try MarkBaseEngine()
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try engine.compileSource(MetalKernels.combinedSource)
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print(" ✓ Engine ready\n")
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print("Step 2: Load 26B-A4B MoE model...")
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do {
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let start = Date()
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let model = try E4BModel(modelDir: modelDir, engine: engine, maxContextLength: 512)
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let loadTime = Date().timeIntervalSince(start)
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print(" ✓ Model loaded successfully in \(String(format: "%.3f", loadTime))s\n")
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print("Model parameters:")
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print(" Layers: \(model.numHiddenLayers)")
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print(" Hidden size: \(model.hiddenSize)")
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print(" Vocab size: \(model.vocabSize)")
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// Verify 26B-A4B parameters
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XCTAssertEqual(model.numHiddenLayers, 30, "Should have 30 layers")
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XCTAssertEqual(model.hiddenSize, 2816, "Should have hidden_size=2816")
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XCTAssertEqual(model.vocabSize, 262144, "Should have vocab_size=262144")
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print("\n═══════════════════════════════════════")
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print("✓ MoE model loading test passed")
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print("═══════════════════════════════════════\n")
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} catch {
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print(" ✗ Model loading failed: \(error)\n")
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throw error
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}
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}
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func test26BA4BSimpleGeneration() throws {
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print("\n═══════════════════════════════════════")
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print(" 26B-A4B MoE Simple Generation")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/MarkBaseEngine/models/gemma-4-26b-a4b-it-4bit"
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let engine = try MarkBaseEngine()
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try engine.compileSource(MetalKernels.combinedSource)
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let model = try E4BModel(modelDir: modelDir, engine: engine, maxContextLength: 128)
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let tokenizer = try TokenizerFactory.load(modelDir: modelDir)
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let generator = StreamingGenerator(model: model, tokenizer: tokenizer, engine: engine)
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print("Testing simple generation (5 tokens)...")
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let prompt = "Hello"
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let config = GenerationConfig(maxTokens: 5, temperature: Float(0.7))
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let start = Date()
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let response = try generator.generateComplete(prompt: prompt, config: config)
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let genTime = Date().timeIntervalSince(start)
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print(" ✓ Generated in \(String(format: "%.3f", genTime))s")
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print(" Response: \"\(response)\"")
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print(" Speed: \(String(format: "%.2f", 5.0 / genTime)) tok/s")
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XCTAssertGreaterThan(response.count, 0, "Should generate some text")
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print("\n═══════════════════════════════════════")
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print("✓ Simple generation test passed")
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print("═══════════════════════════════════════\n")
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}
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}
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