Ace-Step-v1.5 / generate_examples.py
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#!/usr/bin/env python3
"""
Batch Generate Text2Music Examples using LM
Generates 50 examples and saves them to examples/text2music/
"""
import os
import json
import sys
from pathlib import Path
# Add project root to path
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))
from acestep.llm_inference import LLMHandler
from loguru import logger
from tqdm import tqdm
def generate_examples(num_examples=50, output_dir="examples/text2music", start_index=1):
"""
Generate examples using LM and save to JSON files
Args:
num_examples: Number of examples to generate
output_dir: Output directory for JSON files
start_index: Starting index for example files
"""
# Initialize LLM Handler
logger.info("Initializing LLM Handler...")
llm_handler = LLMHandler()
# Initialize LM
checkpoint_dir = os.path.join(project_root, "checkpoints")
# Use default LM model
available_models = llm_handler.get_available_5hz_lm_models()
if not available_models:
logger.error("No 5Hz LM models found in checkpoints directory")
return
# Prefer acestep-5Hz-lm-0.6B if available
lm_model = "acestep-5Hz-lm-0.6B" if "acestep-5Hz-lm-0.6B" in available_models else available_models[0]
logger.info(f"Using LM model: {lm_model}")
# Initialize LM
status_msg, success = llm_handler.initialize(
checkpoint_dir=checkpoint_dir,
lm_model_path=lm_model,
backend="vllm", # Use vllm for faster generation
device="auto",
offload_to_cpu=False,
dtype=None,
)
if not success:
logger.error(f"Failed to initialize LM: {status_msg}")
return
logger.info(f"LM initialized successfully: {status_msg}")
# Create output directory if it doesn't exist
os.makedirs(output_dir, exist_ok=True)
# Generate examples
successful_count = 0
failed_count = 0
for i in tqdm(range(num_examples), desc="Generating examples"):
example_num = start_index + i
output_file = os.path.join(output_dir, f"example_{example_num:02d}.json")
logger.info(f"Generating example {example_num}/{start_index + num_examples - 1}...")
try:
# Generate example using LM
metadata, status = llm_handler.understand_audio_from_codes(
audio_codes="NO USER INPUT", # Empty input triggers example generation
use_constrained_decoding=True,
temperature=0.85,
cfg_scale=1.0,
top_k=None,
top_p=0.9,
)
if not metadata:
logger.warning(f"Failed to generate example {example_num}: {status}")
failed_count += 1
continue
# Build JSON data with all available fields
example_data = {
"think": True, # Always true for LM-generated examples
"caption": metadata.get("caption", ""),
"lyrics": metadata.get("lyrics", ""),
}
# Add optional metadata fields if they exist and are not "N/A"
if "bpm" in metadata and metadata["bpm"] not in [None, "N/A", ""]:
try:
# Convert to int if it's a valid number
example_data["bpm"] = int(metadata["bpm"]) if isinstance(metadata["bpm"], (int, str)) else metadata["bpm"]
except (ValueError, TypeError):
example_data["bpm"] = metadata["bpm"]
if "duration" in metadata and metadata["duration"] not in [None, "N/A", ""]:
try:
# Convert to int if it's a valid number
example_data["duration"] = int(metadata["duration"]) if isinstance(metadata["duration"], (int, str)) else metadata["duration"]
except (ValueError, TypeError):
example_data["duration"] = metadata["duration"]
if "keyscale" in metadata and metadata["keyscale"] not in [None, "N/A", ""]:
example_data["keyscale"] = metadata["keyscale"]
if "language" in metadata and metadata["language"] not in [None, "N/A", ""]:
example_data["language"] = metadata["language"]
if "timesignature" in metadata and metadata["timesignature"] not in [None, "N/A", ""]:
example_data["timesignature"] = metadata["timesignature"]
# Save to JSON file
with open(output_file, 'w', encoding='utf-8') as f:
json.dump(example_data, f, ensure_ascii=False, indent=4)
logger.info(f"✅ Saved example {example_num} to {output_file}")
logger.info(f" Caption preview: {example_data['caption'][:100]}...")
successful_count += 1
except Exception as e:
logger.error(f"❌ Error generating example {example_num}: {str(e)}")
failed_count += 1
continue
# Summary
logger.info(f"\n{'='*60}")
logger.info(f"Generation complete!")
logger.info(f"Successful: {successful_count}/{num_examples}")
logger.info(f"Failed: {failed_count}/{num_examples}")
logger.info(f"Output directory: {output_dir}")
logger.info(f"{'='*60}\n")
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description="Generate text2music examples using LM")
parser.add_argument("--num", type=int, default=100, help="Number of examples to generate (default: 100)")
parser.add_argument("--output-dir", type=str, default="examples/text2music", help="Output directory (default: examples/text2music)")
parser.add_argument("--start-index", type=int, default=1, help="Starting index for example files (default: 1)")
args = parser.parse_args()
generate_examples(
num_examples=args.num,
output_dir=args.output_dir,
start_index=args.start_index
)