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# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
import sys
if sys.version_info < (3, 8):
_is_python_greater_3_8 = False
else:
_is_python_greater_3_8 = True
def is_peft_available() -> bool:
return importlib.util.find_spec("peft") is not None
def is_unsloth_available() -> bool:
return importlib.util.find_spec("unsloth") is not None
def is_accelerate_greater_20_0() -> bool:
if _is_python_greater_3_8:
from importlib.metadata import version
accelerate_version = version("accelerate")
else:
import pkg_resources
accelerate_version = pkg_resources.get_distribution("accelerate").version
return accelerate_version >= "0.20.0"
def is_transformers_greater_than(version: str) -> bool:
_transformers_version = importlib.metadata.version("transformers")
return _transformers_version > version
def is_torch_greater_2_0() -> bool:
if _is_python_greater_3_8:
from importlib.metadata import version
torch_version = version("torch")
else:
import pkg_resources
torch_version = pkg_resources.get_distribution("torch").version
return torch_version >= "2.0"
def is_diffusers_available() -> bool:
return importlib.util.find_spec("diffusers") is not None
def is_bitsandbytes_available() -> bool:
import torch
# bnb can be imported without GPU but is not usable.
return importlib.util.find_spec("bitsandbytes") is not None and torch.cuda.is_available()
def is_torchvision_available() -> bool:
return importlib.util.find_spec("torchvision") is not None
def is_rich_available() -> bool:
return importlib.util.find_spec("rich") is not None
def is_wandb_available() -> bool:
return importlib.util.find_spec("wandb") is not None
def is_xpu_available() -> bool:
if is_accelerate_greater_20_0():
import accelerate
return accelerate.utils.is_xpu_available()
else:
if importlib.util.find_spec("intel_extension_for_pytorch") is None:
return False
try:
import torch
return hasattr(torch, "xpu") and torch.xpu.is_available()
except RuntimeError:
return False
def is_npu_available() -> bool:
"""Checks if `torch_npu` is installed and potentially if a NPU is in the environment"""
if importlib.util.find_spec("torch") is None or importlib.util.find_spec("torch_npu") is None:
return False
import torch
import torch_npu # noqa: F401
return hasattr(torch, "npu") and torch.npu.is_available()
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