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llm-in-text/backend/tests/simulate_macos.py

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
macOS环境模拟测试工具
在非macOS环境下模拟Apple Silicon环境进行测试
运行方式:
python backend/tests/simulate_macos.py --help
python backend/tests/simulate_macos.py --device mps
python backend/tests/simulate_macos.py --apple-silicon
python backend/tests/simulate_macos.py --full-simulation
"""
import argparse
import importlib
import os
import platform
import sys
from unittest.mock import patch
import numpy as np
class MacOSSimulator:
"""macOS环境模拟器"""
def __init__(self):
self.original_platform_system = platform.system
self.original_platform_machine = platform.machine
self.patches = []
def simulate_apple_silicon(self):
"""模拟Apple Silicon环境"""
print("\n" + "="*70)
print("模拟 Apple Silicon 环境")
print("="*70)
# 模拟Darwin系统和arm64架构
self.patches.append(patch('platform.system', return_value='Darwin'))
self.patches.append(patch('platform.machine', return_value='arm64'))
for p in self.patches:
p.start()
print("✓ 平台: Darwin (macOS)")
print("✓ 架构: arm64 (Apple Silicon)")
def simulate_mps_device(self):
"""模拟MPS设备可用"""
print("\n" + "="*70)
print("模拟 MPS 设备")
print("="*70)
# 创建模拟的torch.backends.mps
mock_mps = type('MockMPS', (), {
'is_available': lambda: True,
'is_built': lambda: True,
'empty_cache': lambda: None
})()
mock_backends = type('MockBackends', (), {
'mps': mock_mps
})()
# 模拟torch模块
mock_torch = type('MockTorch', (), {
'backends': mock_backends,
'mps': mock_mps,
'randn': lambda *args, **kwargs: np.random.randn(*args),
'mm': lambda a, b: np.dot(a, b),
'empty_cache': lambda: None
})()
self.patches.append(patch('torch', mock_torch))
self.patches.append(patch('torch.backends.mps.is_available', return_value=True))
self.patches.append(patch('torch.backends.mps.is_built', return_value=True))
for p in self.patches[-3:]:
p.start()
print("✓ MPS 可用: True")
print("✓ MPS 已编译: True")
def simulate_cuda_device(self):
"""模拟CUDA设备可用"""
print("\n" + "="*70)
print("模拟 CUDA 设备")
print("="*70)
mock_cuda = type('MockCUDA', (), {
'is_available': lambda: True,
'device_count': lambda: 1,
'get_device_properties': lambda n: type('Props', (), {'total_memory': 8*1024*1024*1024})(),
'empty_cache': lambda: None
})()
self.patches.append(patch('torch.cuda', mock_cuda))
self.patches.append(patch('torch.cuda.is_available', return_value=True))
for p in self.patches[-2:]:
p.start()
print("✓ CUDA 可用: True")
print("✓ GPU 数量: 1")
print("✓ 显存: 8 GB")
def cleanup(self):
"""清理所有补丁"""
for p in self.patches:
p.stop()
self.patches.clear()
print("\n✓ 已清理模拟环境")
def test_device_detection_on_apple_silicon():
"""测试Apple Silicon设备检测"""
print("\n测试1: Apple Silicon 设备检测")
print("-"*70)
simulator = MacOSSimulator()
try:
simulator.simulate_apple_silicon()
simulator.simulate_mps_device()
# 设置环境变量
os.environ['TTS_ASR_DEVICE'] = 'auto'
os.environ['TTS_ASR_MODEL_SIZE'] = 'auto'
# 重新导入模块以应用模拟
if 'backend.tts_asr' in sys.modules:
del sys.modules['backend.tts_asr']
from backend.tts_asr import (
_is_apple_silicon,
_detect_device_capabilities,
_get_recommended_model_size
)
# 测试Apple Silicon检测
assert _is_apple_silicon(), "应该检测到Apple Silicon"
print("✓ Apple Silicon 检测: 通过")
# 测试设备能力检测
caps = _detect_device_capabilities()
print(f"✓ 设备: {caps.device}")
print(f"✓ MPS 可用: {caps.mps_available}")
print(f"✓ 推荐模型大小: {caps.recommended_model_size}")
# 测试模型大小推荐
recommended_size = _get_recommended_model_size()
assert recommended_size in ['small', 'tiny', 'base'], \
f"Apple Silicon应推荐小模型但推荐了 {recommended_size}"
print(f"✓ 推荐模型大小: {recommended_size}")
print("\n✓ 测试通过")
return True
except Exception as e:
print(f"\n✗ 测试失败: {e}")
import traceback
traceback.print_exc()
return False
finally:
simulator.cleanup()
def test_memory_management():
"""测试内存管理"""
print("\n测试2: 内存管理")
print("-"*70)
simulator = MacOSSimulator()
try:
simulator.simulate_apple_silicon()
simulator.simulate_mps_device()
# 模拟系统内存
import psutil
original_virtual_memory = psutil.virtual_memory
def mock_virtual_memory():
mock_mem = type('MockMemory', (), {
'total': 16 * 1024 * 1024 * 1024 # 16GB
})()
return mock_mem
self.patches.append(patch('psutil.virtual_memory', mock_virtual_memory))
from backend.tts_asr import _get_system_memory_mb, TTS_ASR_MPS_MEMORY_LIMIT_MB
mem_mb = _get_system_memory_mb()
print(f"✓ 系统内存: {mem_mb} MB")
# 计算预期的MPS内存限制60%
expected_limit = int(mem_mb * 0.6)
print(f"✓ 预期MPS限制: {expected_limit} MB (60%)")
print(f"✓ 配置MPS限制: {TTS_ASR_MPS_MEMORY_LIMIT_MB} MB")
print("\n✓ 测试通过")
return True
except Exception as e:
print(f"\n✗ 测试失败: {e}")
import traceback
traceback.print_exc()
return False
finally:
simulator.cleanup()
def test_model_size_selection():
"""测试模型大小选择"""
print("\n测试3: 模型大小选择")
print("-"*70)
test_cases = [
('auto', 'Apple Silicon默认'),
('tiny', '最小模型'),
('small', '推荐模型'),
('medium', '中等模型'),
('large', '大模型'),
('turbo', 'turbo模型'),
]
from backend.tts_asr import WHISPER_MODEL_SIZES, _get_recommended_model_size
for size, desc in test_cases:
os.environ['TTS_ASR_MODEL_SIZE'] = size
# 重新加载模块
if 'backend.tts_asr' in sys.modules:
del sys.modules['backend.tts_asr']
from backend.tts_asr import _get_recommended_model_size
if size == 'auto':
# 自动选择
recommended = _get_recommended_model_size()
print(f"{desc}: {recommended}")
else:
# 显式选择
os.environ['TTS_ASR_MODEL_SIZE'] = size
result = _get_recommended_model_size()
assert result == size, f"应该返回 {size},但返回了 {result}"
print(f"{desc}: {size} -> {WHISPER_MODEL_SIZES[size]}")
print("\n✓ 测试通过")
return True
def test_audio_processing():
"""测试音频处理"""
print("\n测试4: 音频处理")
print("-"*70)
from backend.tts_asr import (
_validate_audio_data,
_resample_audio_robust
)
# 测试音频验证
test_cases = [
(b'', False, "空数据"),
(b'short', False, "太短"),
(b'RIFF' + b'\x00' * 40, True, "有效WAV头"),
]
for data, expected, desc in test_cases:
result = _validate_audio_data(data)
assert result == expected, f"{desc}: 预期 {expected},得到 {result}"
print(f"✓ 音频验证 ({desc}): {'通过' if result == expected else '失败'}")
# 测试重采样
audio_16k = np.sin(np.linspace(0, 2*np.pi, 16000)).astype(np.float32)
# 16k -> 48k
audio_48k = _resample_audio_robust(audio_16k, 16000, 48000)
assert len(audio_48k) == 48000, f"48kHz音频长度错误: {len(audio_48k)}"
print(f"✓ 重采样 (16k -> 48k): 长度 {len(audio_16k)} -> {len(audio_48k)}")
# 48k -> 16k
audio_back = _resample_audio_robust(audio_48k, 48000, 16000)
assert len(audio_back) == 16000, f"16kHz音频长度错误: {len(audio_back)}"
print(f"✓ 重采样 (48k -> 16k): 长度 {len(audio_48k)} -> {len(audio_back)}")
print("\n✓ 测试通过")
return True
def test_environment_variables():
"""测试环境变量"""
print("\n测试5: 环境变量配置")
print("-"*70)
# 清理环境变量
env_vars = [
'TTS_ASR_DEVICE', 'TTS_ASR_MODEL_SIZE', 'TTS_ASR_QUANTIZE',
'TTS_ASR_OFFLINE_MODE', 'TTS_ASR_WARMUP', 'TTS_ASR_WARMUP_TIMEOUT',
'TTS_ASR_IDLE_TIMEOUT', 'TTS_ASR_MPS_MEMORY_LIMIT_MB'
]
original_values = {}
for var in env_vars:
original_values[var] = os.environ.get(var)
if var in os.environ:
del os.environ[var]
try:
# 测试默认值
from backend.tts_asr import (
TTS_ASR_DEVICE, TTS_ASR_MODEL_SIZE, TTS_ASR_QUANTIZE,
TTS_ASR_OFFLINE_MODE, TTS_ASR_WARMUP, TTS_ASR_WARMUP_TIMEOUT,
TTS_ASR_IDLE_TIMEOUT, TTS_ASR_MPS_MEMORY_LIMIT_MB
)
defaults = {
'TTS_ASR_DEVICE': 'auto',
'TTS_ASR_MODEL_SIZE': 'auto',
'TTS_ASR_QUANTIZE': False,
'TTS_ASR_OFFLINE_MODE': False,
'TTS_ASR_WARMUP': True,
'TTS_ASR_WARMUP_TIMEOUT': 120,
'TTS_ASR_IDLE_TIMEOUT': 0,
'TTS_ASR_MPS_MEMORY_LIMIT_MB': 8192,
}
for var, expected in defaults.items():
actual = locals()[var]
assert actual == expected, f"{var}: 预期 {expected},得到 {actual}"
print(f"{var} = {actual}")
# 测试自定义值
print("\n自定义配置测试:")
os.environ['TTS_ASR_MODEL_SIZE'] = 'small'
os.environ['TTS_ASR_QUANTIZE'] = 'true'
os.environ['TTS_ASR_OFFLINE_MODE'] = 'true'
os.environ['TTS_ASR_MPS_MEMORY_LIMIT_MB'] = '4096'
# 重新加载
if 'backend.tts_asr' in sys.modules:
del sys.modules['backend.tts_asr']
from backend.tts_asr import (
TTS_ASR_MODEL_SIZE, TTS_ASR_QUANTIZE,
TTS_ASR_OFFLINE_MODE, TTS_ASR_MPS_MEMORY_LIMIT_MB
)
assert TTS_ASR_MODEL_SIZE == 'small'
assert TTS_ASR_QUANTIZE == True
assert TTS_ASR_OFFLINE_MODE == True
assert TTS_ASR_MPS_MEMORY_LIMIT_MB == 4096
print(f"✓ TTS_ASR_MODEL_SIZE = {TTS_ASR_MODEL_SIZE}")
print(f"✓ TTS_ASR_QUANTIZE = {TTS_ASR_QUANTIZE}")
print(f"✓ TTS_ASR_OFFLINE_MODE = {TTS_ASR_OFFLINE_MODE}")
print(f"✓ TTS_ASR_MPS_MEMORY_LIMIT_MB = {TTS_ASR_MPS_MEMORY_LIMIT_MB}")
print("\n✓ 测试通过")
return True
finally:
# 恢复原始值
for var, value in original_values.items():
if value is not None:
os.environ[var] = value
elif var in os.environ:
del os.environ[var]
def run_full_simulation():
"""运行完整模拟测试"""
print("\n" + "="*70)
print("完整macOS环境模拟测试")
print("="*70)
results = []
# 运行所有测试
results.append(("设备检测", test_device_detection_on_apple_silicon()))
results.append(("内存管理", test_memory_management()))
results.append(("模型选择", test_model_size_selection()))
results.append(("音频处理", test_audio_processing()))
results.append(("环境变量", test_environment_variables()))
# 汇总结果
print("\n" + "="*70)
print("测试结果汇总")
print("="*70)
for name, passed in results:
status = "✓ 通过" if passed else "✗ 失败"
print(f"{name}: {status}")
total = len(results)
passed = sum(1 for _, p in results if p)
print("\n" + "-"*70)
print(f"总计: {passed}/{total} 测试通过")
print("="*70)
return all(p for _, p in results)
def main():
parser = argparse.ArgumentParser(
description='macOS环境模拟测试工具',
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
示例:
# 运行完整模拟测试
python backend/tests/simulate_macos.py --full-simulation
# 仅模拟Apple Silicon环境
python backend/tests/simulate_macos.py --apple-silicon
# 仅模拟MPS设备
python backend/tests/simulate_macos.py --device mps
# 仅模拟CUDA设备
python backend/tests/simulate_macos.py --device cuda
"""
)
parser.add_argument(
'--full-simulation',
action='store_true',
help='运行完整模拟测试'
)
parser.add_argument(
'--apple-silicon',
action='store_true',
help='模拟Apple Silicon环境'
)
parser.add_argument(
'--device',
choices=['mps', 'cuda'],
help='模拟特定设备'
)
parser.add_argument(
'--test',
choices=['device', 'memory', 'model', 'audio', 'env'],
help='运行特定测试'
)
args = parser.parse_args()
# 确保可以导入backend模块
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
if args.full_simulation:
success = run_full_simulation()
sys.exit(0 if success else 1)
if args.apple_silicon:
simulator = MacOSSimulator()
try:
simulator.simulate_apple_silicon()
simulator.simulate_mps_device()
print("\n环境已模拟按Ctrl+D退出")
print("在Python环境中可以使用:")
print(" from backend.tts_asr import _is_apple_silicon")
print(" print(_is_apple_silicon()) # 应该返回 True")
# 进入交互模式
import code
code.interact(local=locals())
finally:
simulator.cleanup()
if args.device:
simulator = MacOSSimulator()
try:
if args.device == 'mps':
simulator.simulate_mps_device()
elif args.device == 'cuda':
simulator.simulate_cuda_device()
print("\n设备已模拟")
import code
code.interact(local=locals())
finally:
simulator.cleanup()
if args.test:
test_func = {
'device': test_device_detection_on_apple_silicon,
'memory': test_memory_management,
'model': test_model_size_selection,
'audio': test_audio_processing,
'env': test_environment_variables,
}
success = test_func[args.test]()
sys.exit(0 if success else 1)
# 默认运行完整测试
if not any([args.full_simulation, args.apple_silicon, args.device, args.test]):
parser.print_help()
if __name__ == '__main__':
main()