ACCC1380 commited on
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f50857f
1 Parent(s): b9b9058

Upload lora-scripts/sd-scripts/library/device_utils.py with huggingface_hub

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lora-scripts/sd-scripts/library/device_utils.py ADDED
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+ import functools
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+ import gc
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+
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+ import torch
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+
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+ try:
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+ HAS_CUDA = torch.cuda.is_available()
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+ except Exception:
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+ HAS_CUDA = False
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+
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+ try:
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+ HAS_MPS = torch.backends.mps.is_available()
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+ except Exception:
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+ HAS_MPS = False
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+
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+ try:
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+ import intel_extension_for_pytorch as ipex # noqa
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+
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+ HAS_XPU = torch.xpu.is_available()
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+ except Exception:
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+ HAS_XPU = False
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+
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+
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+ def clean_memory():
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+ gc.collect()
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+ if HAS_CUDA:
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+ torch.cuda.empty_cache()
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+ if HAS_XPU:
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+ torch.xpu.empty_cache()
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+ if HAS_MPS:
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+ torch.mps.empty_cache()
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+
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+
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+ def clean_memory_on_device(device: torch.device):
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+ r"""
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+ Clean memory on the specified device, will be called from training scripts.
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+ """
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+ gc.collect()
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+
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+ # device may "cuda" or "cuda:0", so we need to check the type of device
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+ if device.type == "cuda":
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+ torch.cuda.empty_cache()
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+ if device.type == "xpu":
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+ torch.xpu.empty_cache()
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+ if device.type == "mps":
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+ torch.mps.empty_cache()
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+
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+
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+ @functools.lru_cache(maxsize=None)
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+ def get_preferred_device() -> torch.device:
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+ r"""
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+ Do not call this function from training scripts. Use accelerator.device instead.
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+ """
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+ if HAS_CUDA:
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+ device = torch.device("cuda")
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+ elif HAS_XPU:
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+ device = torch.device("xpu")
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+ elif HAS_MPS:
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+ device = torch.device("mps")
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+ else:
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+ device = torch.device("cpu")
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+ print(f"get_preferred_device() -> {device}")
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+ return device
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+
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+
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+ def init_ipex():
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+ """
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+ Apply IPEX to CUDA hijacks using `library.ipex.ipex_init`.
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+
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+ This function should run right after importing torch and before doing anything else.
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+
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+ If IPEX is not available, this function does nothing.
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+ """
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+ try:
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+ if HAS_XPU:
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+ from library.ipex import ipex_init
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+
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+ is_initialized, error_message = ipex_init()
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+ if not is_initialized:
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+ print("failed to initialize ipex:", error_message)
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+ else:
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+ return
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+ except Exception as e:
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+ print("failed to initialize ipex:", e)