import torch
class Config:
    def __init__(self):
        self.image_size: int = 512  # the generated image resolution
        self.sample_rate: int = 44100  # the sample rate of the audio
        self.guidance_scale: float = 1  # the guidance scale for the diffusion process
        self.mixed_precision: str = "fp16"  # `no` for float32, `fp16` for automatic mixed precision
        self.hub_model_id: str = "alppo/amuse"  # the name of the repository to create on the HF Hub
        self.hub_dataset_id: str = "alppo/music"  # the name of the dataset to create on the HF Hub
        self.seed: int = 0
        self.device = "cuda" if torch.cuda.is_available() else "cpu"
        self.generated_track_path = "new_track.wav"


config = Config()