github-actions[bot]
64 lines
1.9 KiB
Python
Executable File
64 lines
1.9 KiB
Python
Executable File
#!/usr/bin/env python
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"""
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Train LTXV models using configuration from YAML files.
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This script provides a command-line interface for training LTXV models using
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either LoRA fine-tuning or full model fine-tuning. It loads configuration from
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a YAML file and passes it to the trainer.
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Basic usage:
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python scripts/train.py CONFIG_PATH [--disable-progress-bars]
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Resume is automatic when a training state file exists next to the loaded checkpoint.
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To start fresh, set `checkpoints.no_resume: true` in the YAML config.
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For multi-GPU/FSDP training, configure and launch via Accelerate:
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accelerate config
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accelerate launch scripts/train.py CONFIG_PATH
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"""
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from pathlib import Path
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import typer
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import yaml
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from rich.console import Console
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from ltx_trainer.config import LtxTrainerConfig
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from ltx_trainer.trainer import LtxvTrainer
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console = Console()
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app = typer.Typer(
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pretty_exceptions_enable=False,
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no_args_is_help=True,
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help="Train LTXV models using configuration from YAML files.",
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)
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@app.command()
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def main(
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config_path: str = typer.Argument(..., help="Path to YAML configuration file"),
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disable_progress_bars: bool = typer.Option(
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False,
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"--disable-progress-bars",
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help="Disable progress bars (useful for multi-process runs)",
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),
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) -> None:
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"""Train the model using the provided configuration file."""
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config_path = Path(config_path)
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if not config_path.exists():
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typer.echo(f"Error: Configuration file {config_path} does not exist.")
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raise typer.Exit(code=1)
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with open(config_path, "r") as file:
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config_data = yaml.safe_load(file)
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try:
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trainer_config = LtxTrainerConfig(**config_data)
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except Exception as e:
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typer.echo(f"Error: Invalid configuration data: {e}")
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raise typer.Exit(code=1) from e
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trainer = LtxvTrainer(trainer_config)
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trainer.train(disable_progress_bars=disable_progress_bars)
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if __name__ == "__main__":
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app()
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