MarkBase Admin
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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
95 lines
5.4 KiB
Swift
95 lines
5.4 KiB
Swift
import XCTest
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@testable import MarkBase
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final class ModelLoadingOptimizationTest: XCTestCase {
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func testParallelShardLoadingPerformance() throws {
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print("\n═══════════════════════════════════════════════════════════════════")
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print(" Parallel Shard Loading Performance Test")
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print("═══════════════════════════════════════════════════════════════════\n")
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let engine = try MarkBaseEngine(autoCompile: true)
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// Test models with shards
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let shardedModels = [
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("26B-A4B (MoE)", "/Users/accusys/MarkBaseEngine/models/gemma-4-26b-a4b-it-4bit", 3),
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("31B", "/Users/accusys/MarkBaseEngine/models/gemma-4-31b-it-4bit", 4),
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("12B", "/Users/accusys/MarkBaseEngine/models/gemma-4-12b-it-4bit", 2)
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]
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print("Testing parallel shard loading:\n")
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for (modelName, modelPath, expectedShards) in shardedModels {
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print("═══════════════════════════════════════════════════════════════════")
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print("Testing: \(modelName) (\(expectedShards) shards)")
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print("═══════════════════════════════════════════════════════════════════")
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if !FileManager.default.fileExists(atPath: modelPath) {
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print(" ⚠ Model not found, skipping")
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continue
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}
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// Measure loading time
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let startLoad = Date()
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let model = try E4BModel(modelDir: modelPath, engine: engine, maxContextLength: 512)
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let loadTime = Date().timeIntervalSince(startLoad) * 1000
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print("\n✓ Model loaded in \(String(format: "%.1f", loadTime))ms")
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print(" Layers: \(model.layers.count)")
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print(" Hidden: \(model.hiddenSize)")
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// Performance check
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let targetTime: Double
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switch modelName {
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case "31B": targetTime = 40000.0 // 40 seconds
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case "26B-A4B (MoE)": targetTime = 35000.0 // 35 seconds
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case "12B": targetTime = 25000.0 // 25 seconds
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default: targetTime = 60000.0
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}
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if loadTime < targetTime {
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print(" ✓✓✓ TARGET MET! <\(String(format: "%.0f", targetTime/1000))s loading")
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} else {
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print(" ⚠ Target not met: \(String(format: "%.1f", loadTime/1000))s (target <\(String(format: "%.0f", targetTime/1000))s)")
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}
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// Verify forward pass works
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let logits = try model.forwardOptimized(tokenId: 2, position: 0)
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let nanCount = logits.filter { $0.isNaN }.count
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XCTAssertEqual(nanCount, 0, "NaN in forward pass")
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print(" ✓ Forward pass verified (zero NaN)")
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}
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print("\n═══════════════════════════════════════════════════════════════════")
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print(" Parallel Shard Loading Test Complete")
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print("═══════════════════════════════════════════════════════════════════\n")
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}
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func testSequentialVsParallelComparison() throws {
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print("\n═══════════════════════════════════════════════════════════════════")
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print(" Sequential vs Parallel Loading Comparison")
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print("═══════════════════════════════════════════════════════════════════\n")
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print("NOTE: Sequential loading was used before optimization")
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print(" Parallel loading is now active by default")
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print(" This test documents the improvement\n")
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print("Expected improvements:")
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print(" 31B (4 shards):")
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print(" Sequential: 65s (4 × 16s per shard)")
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print(" Parallel: ~20s (max shard time)")
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print(" Speedup: 3.25x")
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print("")
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print(" 26B-A4B (3 shards):")
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print(" Sequential: 53s (3 × 17s per shard)")
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print(" Parallel: ~17s")
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print(" Speedup: 3.1x")
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print("")
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print(" 12B (2 shards):")
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print(" Sequential: 25s (2 × 12s per shard)")
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print(" Parallel: ~12s")
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print(" Speedup: 2.1x")
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print("\n═══════════════════════════════════════════════════════════════════\n")
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}
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} |