mirror of
https://github.com/hiyouga/LLaMA-Factory.git
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887ee2b121
Co-authored-by: mrhaoxx <mr.haoxx@gmail.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
153 lines
3.7 KiB
Python
153 lines
3.7 KiB
Python
# Copyright 2025 HuggingFace Inc. and the LlamaFactory team.
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#
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# This code is inspired by the HuggingFace's transformers library.
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# https://github.com/huggingface/transformers/blob/v4.40.0/src/transformers/utils/import_utils.py
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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.metadata
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import importlib.util
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from functools import lru_cache
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from typing import TYPE_CHECKING
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import transformers.utils.import_utils as import_utils
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from packaging import version
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if TYPE_CHECKING:
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from packaging.version import Version
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def _is_package_available(name: str) -> bool:
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return importlib.util.find_spec(name) is not None
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def _get_package_version(name: str) -> "Version":
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try:
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return version.parse(importlib.metadata.version(name))
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except Exception:
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return version.parse("0.0.0")
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def is_pyav_available():
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return _is_package_available("av")
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def is_librosa_available():
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return _is_package_available("librosa")
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def is_fastapi_available():
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return _is_package_available("fastapi")
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def is_galore_available():
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return _is_package_available("galore_torch")
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def is_apollo_available():
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return _is_package_available("apollo_torch")
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def is_jieba_available():
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return _is_package_available("jieba")
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def is_gradio_available():
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return _is_package_available("gradio")
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def is_matplotlib_available():
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return _is_package_available("matplotlib")
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def is_hyper_parallel_available():
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return _is_package_available("hyper_parallel")
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def is_mcore_adapter_available():
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return _is_package_available("mcore_adapter")
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def is_pillow_available():
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return _is_package_available("PIL")
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def is_ray_available():
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return _is_package_available("ray")
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def is_kt_available():
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return _is_package_available("kt_kernel")
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def is_requests_available():
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return _is_package_available("requests")
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def is_rouge_available():
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return _is_package_available("rouge_chinese")
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def is_safetensors_available():
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return _is_package_available("safetensors")
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def is_sglang_available():
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return _is_package_available("sglang")
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def is_starlette_available():
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return _is_package_available("sse_starlette")
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@lru_cache
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def is_transformers_version_greater_than(content: str):
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return _get_package_version("transformers") >= version.parse(content)
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@lru_cache
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def is_torch_version_greater_than(content: str):
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return _get_package_version("torch") >= version.parse(content)
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def is_uvicorn_available():
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return _is_package_available("uvicorn")
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def is_vllm_available():
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return _is_package_available("vllm")
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_orig_is_package_available = import_utils._is_package_available
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class PackageAvailability(tuple):
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__slots__ = ()
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def __new__(cls, available: bool, pkg_version: str = "N/A"):
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return super().__new__(cls, (bool(available), pkg_version))
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def __bool__(self) -> bool:
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return self[0]
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def _patched_is_package_available(pkg_name: str, return_version: bool = False):
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available, version = _orig_is_package_available(pkg_name, return_version=return_version)
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return PackageAvailability(available, version)
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if is_transformers_version_greater_than("5.3.0"):
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import_utils._is_package_available = _patched_is_package_available
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