ltx2_training_pipeline ¶

def __init__(self,
             model_path: str,
             fastvideo_args: TrainingArgs,
             required_config_modules: list[str] | None = None,
             loaded_modules: dict[str, torch.nn.Module] | None = None) -> None:
    fastvideo_args.inference_mode = False
    self.lora_training = fastvideo_args.lora_training
    if self.lora_training and fastvideo_args.lora_rank is None:
        raise ValueError("lora rank must be set when using lora training")

    set_random_seed(fastvideo_args.seed)  # for lora param init
    super().__init__(model_path, fastvideo_args, required_config_modules, loaded_modules)  # type: ignore
    self.tracker = DummyTracker()
    self.validation_ref_videos_logged = False