Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,511 Bytes
a602628 4709141 a602628 4709141 a602628 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 |
"""
Utility functions for ACE-Step application
"""
import logging
import yaml
from pathlib import Path
from typing import Dict, Any
import sys
def setup_logging(log_level: str = "INFO") -> logging.Logger:
"""
Setup logging configuration.
Args:
log_level: Logging level
Returns:
Logger instance
"""
# Create logs directory
log_dir = Path("logs")
log_dir.mkdir(exist_ok=True)
# Setup logging
logging.basicConfig(
level=getattr(logging, log_level),
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=[
logging.FileHandler(log_dir / "ace_step.log"),
logging.StreamHandler(sys.stdout)
]
)
logger = logging.getLogger("ace_step")
logger.info("Logging initialized")
return logger
def load_config(config_path: str = "config.yaml") -> Dict[str, Any]:
"""
Load configuration from YAML file.
Args:
config_path: Path to config file
Returns:
Configuration dictionary
"""
config_file = Path(config_path)
if config_file.exists():
with open(config_file, 'r') as f:
config = yaml.safe_load(f)
else:
# Default configuration
config = {
"checkpoint_dir": "./checkpoints",
"dit_model_path": "acestep-v15-turbo",
"lm_model_path": "acestep-5Hz-lm-1.7B",
"model_path": "ACE-Step/ACE-Step-v1-3.5B",
"sample_rate": 44100,
"output_dir": "outputs",
"timeline_dir": "timelines",
"training_dir": "lora_training",
"chunk_duration": 30,
"force_mono": False,
"device": "auto",
"use_flash_attention": False,
"offload_to_cpu": False
}
# Save default config
with open(config_file, 'w') as f:
yaml.dump(config, f, default_flow_style=False)
return config
def format_duration(seconds: float) -> str:
"""
Format duration in seconds to human-readable string.
Args:
seconds: Duration in seconds
Returns:
Formatted string (e.g., "2:30")
"""
minutes = int(seconds // 60)
secs = int(seconds % 60)
return f"{minutes}:{secs:02d}"
def validate_audio_file(file_path: str) -> bool:
"""
Validate audio file.
Args:
file_path: Path to audio file
Returns:
True if valid, False otherwise
"""
import torchaudio
try:
audio, sr = torchaudio.load(file_path)
return True
except:
return False
def get_audio_info(file_path: str) -> Dict[str, Any]:
"""
Get audio file information.
Args:
file_path: Path to audio file
Returns:
Dictionary with audio info
"""
import torchaudio
try:
audio, sr = torchaudio.load(file_path)
return {
"duration": audio.shape[1] / sr,
"sample_rate": sr,
"channels": audio.shape[0],
"samples": audio.shape[1],
"format": Path(file_path).suffix
}
except Exception as e:
return {"error": str(e)}
def ensure_directories():
"""Create necessary directories if they don't exist."""
dirs = ["outputs", "timelines", "lora_training", "logs", "models"]
for dir_name in dirs:
Path(dir_name).mkdir(exist_ok=True)
|