import shutil
import torch
import gc


def is_disk_full(min_free_space_in_GB=10):
    total, used, free = shutil.disk_usage("/")
    free_gb = free / (1024 ** 3)
    
    if free_gb >= min_free_space_in_GB:
        print(f'enough space available ({free_gb} GB)')
        return False
    else:
        print('clean up!')
        return True
        
        
def free_gpu_memory(obj=None, label='Object'):
    """
    Frees GPU memory by deleting the passed object, collecting garbage,
    and clearing PyTorch's CUDA cache.

    Args:
        obj (optional): The model or pipeline to delete.
        label (str): Label for logging (e.g., 'model', 'pipeline').
    """
    if torch.cuda.is_available():
        print(f"\n[{label}] Before deletion: {torch.cuda.memory_allocated() / 1e6:.2f} MB")
    
    if obj is not None:
        del obj

    gc.collect()
    torch.cuda.empty_cache()

    if torch.cuda.is_available():
        print(f"[{label}] After deletion:  {torch.cuda.memory_allocated() / 1e6:.2f} MB\n")