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