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| # Copyright 2020-2025 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 os | |
| from itertools import chain | |
| from types import ModuleType | |
| from typing import Any | |
| from packaging import version | |
| from transformers.utils.import_utils import _is_package_available | |
| LIGER_KERNEL_MIN_VERSION = "0.5.8" | |
| # Use same as transformers.utils.import_utils | |
| _deepspeed_available = _is_package_available("deepspeed") | |
| _diffusers_available = _is_package_available("diffusers") | |
| _fastapi_available = _is_package_available("fastapi") | |
| _is_liger_kernel_available, _liger_kernel_version = _is_package_available("liger_kernel", return_version=True) | |
| _llm_blender_available = _is_package_available("llm_blender") | |
| _mergekit_available = _is_package_available("mergekit") | |
| _pydantic_available = _is_package_available("pydantic") | |
| _requests_available = _is_package_available("requests") | |
| _unsloth_available = _is_package_available("unsloth") | |
| _uvicorn_available = _is_package_available("uvicorn") | |
| _vllm_available = _is_package_available("vllm") | |
| _vllm_ascend_available = _is_package_available("vllm_ascend") | |
| _joblib_available = _is_package_available("joblib") | |
| def is_deepspeed_available() -> bool: | |
| return _deepspeed_available | |
| def is_diffusers_available() -> bool: | |
| return _diffusers_available | |
| def is_fastapi_available() -> bool: | |
| return _fastapi_available | |
| def is_liger_kernel_available(min_version: str = LIGER_KERNEL_MIN_VERSION) -> bool: | |
| return _is_liger_kernel_available and version.parse(_liger_kernel_version) >= version.parse(min_version) | |
| def is_llm_blender_available() -> bool: | |
| return _llm_blender_available | |
| def is_mergekit_available() -> bool: | |
| return _mergekit_available | |
| def is_pydantic_available() -> bool: | |
| return _pydantic_available | |
| def is_requests_available() -> bool: | |
| return _requests_available | |
| def is_unsloth_available() -> bool: | |
| return _unsloth_available | |
| def is_uvicorn_available() -> bool: | |
| return _uvicorn_available | |
| def is_vllm_available() -> bool: | |
| return _vllm_available | |
| def is_vllm_ascend_available() -> bool: | |
| return _vllm_ascend_available | |
| def is_joblib_available() -> bool: | |
| return _joblib_available | |
| class _LazyModule(ModuleType): | |
| """ | |
| Module class that surfaces all objects but only performs associated imports when the objects are requested. | |
| """ | |
| # Very heavily inspired by optuna.integration._IntegrationModule | |
| # https://github.com/optuna/optuna/blob/master/optuna/integration/__init__.py | |
| def __init__(self, name, module_file, import_structure, module_spec=None, extra_objects=None): | |
| super().__init__(name) | |
| self._modules = set(import_structure.keys()) | |
| self._class_to_module = {} | |
| for key, values in import_structure.items(): | |
| for value in values: | |
| self._class_to_module[value] = key | |
| # Needed for autocompletion in an IDE | |
| self.__all__ = list(import_structure.keys()) + list(chain(*import_structure.values())) | |
| self.__file__ = module_file | |
| self.__spec__ = module_spec | |
| self.__path__ = [os.path.dirname(module_file)] | |
| self._objects = {} if extra_objects is None else extra_objects | |
| self._name = name | |
| self._import_structure = import_structure | |
| # Needed for autocompletion in an IDE | |
| def __dir__(self): | |
| result = super().__dir__() | |
| # The elements of self.__all__ that are submodules may or may not be in the dir already, depending on whether | |
| # they have been accessed or not. So we only add the elements of self.__all__ that are not already in the dir. | |
| for attr in self.__all__: | |
| if attr not in result: | |
| result.append(attr) | |
| return result | |
| def __getattr__(self, name: str) -> Any: | |
| if name in self._objects: | |
| return self._objects[name] | |
| if name in self._modules: | |
| value = self._get_module(name) | |
| elif name in self._class_to_module.keys(): | |
| module = self._get_module(self._class_to_module[name]) | |
| value = getattr(module, name) | |
| else: | |
| raise AttributeError(f"module {self.__name__} has no attribute {name}") | |
| setattr(self, name, value) | |
| return value | |
| def _get_module(self, module_name: str): | |
| try: | |
| return importlib.import_module("." + module_name, self.__name__) | |
| except Exception as e: | |
| raise RuntimeError( | |
| f"Failed to import {self.__name__}.{module_name} because of the following error (look up to see its" | |
| f" traceback):\n{e}" | |
| ) from e | |
| def __reduce__(self): | |
| return (self.__class__, (self._name, self.__file__, self._import_structure)) | |
| class OptionalDependencyNotAvailable(BaseException): | |
| """Internally used error class for signalling an optional dependency was not found.""" | |