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
99 lines
4.7 KiB
Swift
99 lines
4.7 KiB
Swift
import XCTest
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@testable import MarkBase
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final class AudioTowerLoadTest: XCTestCase {
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func testAudioTowerLoad() throws {
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print("\n═══════════════════════════════════════")
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print(" AudioTower Loading Test")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/MarkBaseEngine/models/E4B-MarkBase"
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print("Step 1: Load AudioConfig...")
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let acfg = loadAudioConfig(modelDir: modelDir)
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print(" hiddenSize: \(acfg.hiddenSize)")
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print(" numHiddenLayers: \(acfg.numHiddenLayers)")
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print(" subsamplingConvChannels: \(acfg.subsamplingConvChannels)")
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print("\nStep 2: Load safetensors...")
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let reader = try SafeTensorsReader(path: modelDir + "/model.safetensors")
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let descriptors = reader.allDescriptors()
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let audioKeys = descriptors.filter { $0.name.hasPrefix("audio_tower.") }
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print(" Found \(audioKeys.count) audio tensors")
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print("\nStep 3: Create engine...")
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let engine = try MarkBaseEngine(autoCompile: true)
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print("\nStep 4: Load AudioTower...")
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do {
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let tower = try loadAudioTower(reader: reader, config: acfg, engine: engine)
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print(" ✓ AudioTower loaded: \(tower.config.numHiddenLayers) layers")
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} catch {
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print(" ✗ AudioTower failed: \(error)")
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throw error
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}
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print("\n═══════════════════════════════════════")
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print("✓ AudioTower loading test passed")
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print("═══════════════════════════════════════\n")
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}
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func testAudioForward() throws {
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print("\n═══════════════════════════════════════")
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print(" AudioTower Forward Test")
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print("═══════════════════════════════════════\n")
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let modelDir = "/Users/accusys/MarkBaseEngine/models/E4B-MarkBase"
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print("Step 1: Load AudioTower...")
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let engine = try MarkBaseEngine(autoCompile: true)
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let acfg = loadAudioConfig(modelDir: modelDir)
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let reader = try SafeTensorsReader(path: modelDir + "/model.safetensors")
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let tower = try loadAudioTower(reader: reader, config: acfg, engine: engine)
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print(" ✓ Loaded: \(tower.config.numHiddenLayers) layers, hidden=\(tower.config.hiddenSize)")
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print("\nStep 2: Create fake mel spectrogram...")
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let seqLen = 98
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let nMels = 128
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var melFeatures: [Float] = Array(repeating: 0.1, count: seqLen * nMels)
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for i in 0..<melFeatures.count {
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melFeatures[i] = Float(i % 100) / 100.0
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}
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print(" Input shape: [\(seqLen), \(nMels)]")
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print("\nStep 3: Run forward pass...")
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let inputBuffer = engine.device.makeBuffer(bytes: melFeatures, length: melFeatures.count * 4)!
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let outputProjDims = tower.config.outputProjDims
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let outputBuffer = engine.device.makeBuffer(length: seqLen / 4 * outputProjDims * 4)!
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do {
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try tower.forward(inputBuffer: inputBuffer, seqLen: seqLen, outputBuffer: outputBuffer)
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print(" ✓ Forward pass completed")
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} catch {
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print(" ✗ Forward failed: \(error)")
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throw error
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}
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print("\nStep 4: Check output...")
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let ptr = outputBuffer.contents().assumingMemoryBound(to: Float.self)
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let outputLen = seqLen / 4 * outputProjDims
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var hasNaN = false
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var maxVal: Float = 0
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var minVal: Float = 0
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for i in 0..<outputLen {
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let v = ptr[i]
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if v.isNaN { hasNaN = true }
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if v > maxVal { maxVal = v }
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if v < minVal { minVal = v }
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}
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print(" Output shape: [\(seqLen/4), \(outputProjDims)]")
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print(" Range: [\(minVal), \(maxVal)]")
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print(" Has NaN: \(hasNaN)")
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XCTAssertFalse(hasNaN, "Output should not have NaN")
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print("\n═══════════════════════════════════════")
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print("✓ AudioTower forward test passed")
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print("═══════════════════════════════════════\n")
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}
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} |