
# Copyright 2023 The HuggingFace Inc. 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 copy
import importlib.metadata
import json
import os
from dataclasses import dataclass
from typing import Any, Dict, Union

from packaging import version

from ..utils import is_torch_available, logging


if is_torch_available():
							import torch


UpperCamelCase_						:     int	       =							logging.get_logger(__name__)




@dataclass
class   __lowercase						:






	def __init__(self				: Dict      ,	snake_case				: List[str]=False      ,	snake_case				: int=False      ,	snake_case				: Tuple=6.0      ,	snake_case				: List[str]=None      ,	snake_case				: Tuple=False      ,	snake_case				: Union[str, Any]=False      ,	snake_case				: Dict=None      ,	snake_case				: Dict="fp4"      ,	snake_case				: str=False      ,	**snake_case				: Dict      ,	) ->			List[Any]:
							_lowercase       :	Tuple           =   load_in_abit
							_lowercase       :	str           =   load_in_abit
							_lowercase       :	Tuple           =   llm_inta_threshold
							_lowercase       :	Any           =   llm_inta_skip_modules
							_lowercase       :	Any           =   llm_inta_enable_fpaa_cpu_offload
							_lowercase       :	Union[str, Any]           =   llm_inta_has_fpaa_weight
							_lowercase       :	Any           =   bnb_abit_quant_type
							_lowercase       :	int           =   bnb_abit_use_double_quant

							if bnb_abit_compute_dtype is None:
													_lowercase       :	Optional[int]           =   torch.floataa
							elif isinstance(snake_case      ,	snake_case    ):
													_lowercase       :	Union[str, Any]           =   getattr(snake_case      ,	snake_case    )
							elif isinstance(snake_case      ,	torch.dtype    ):
													_lowercase       :	int           =   bnb_abit_compute_dtype
							else:
													raise ValueError("bnb_4bit_compute_dtype must be a string or a torch.dtype"    )

							self.post_init()






	def       _a(self				: Union[str, Any]    ) ->			Optional[int]:
							if not isinstance(self.llm_inta_threshold      ,	snake_case    ):
													raise ValueError("llm_int8_threshold must be a float"    )

							if self.llm_inta_skip_modules is not None and not isinstance(self.llm_inta_skip_modules      ,	snake_case    ):
													raise ValueError("llm_int8_skip_modules must be a list of strings"    )
							if not isinstance(self.llm_inta_enable_fpaa_cpu_offload      ,	snake_case    ):
													raise ValueError("llm_int8_enable_fp32_cpu_offload must be a boolean"    )

							if not isinstance(self.llm_inta_has_fpaa_weight      ,	snake_case    ):
													raise ValueError("llm_int8_has_fp16_weight must be a boolean"    )

							if self.bnb_abit_compute_dtype is not None and not isinstance(self.bnb_abit_compute_dtype      ,	torch.dtype    ):
													raise ValueError("bnb_4bit_compute_dtype must be torch.dtype"    )

							if not isinstance(self.bnb_abit_quant_type      ,	snake_case    ):
													raise ValueError("bnb_4bit_quant_type must be a string"    )

							if not isinstance(self.bnb_abit_use_double_quant      ,	snake_case    ):
													raise ValueError("bnb_4bit_use_double_quant must be a boolean"    )

							if self.load_in_abit and not version.parse(importlib.metadata.version("bitsandbytes"    )    ) >= version.parse(
							    "0.39.0"    ):
													raise ValueError(
													    "4 bit quantization requires bitsandbytes>=0.39.0 - please upgrade your bitsandbytes version"    )






	def       _a(self				: Tuple    ) ->			Union[str, Any]:
							return self.load_in_abit or self.load_in_abit






	def       _a(self				: Dict    ) ->			Union[str, Any]:
							if self.load_in_abit:
													return "llm_int8"
							elif self.load_in_abit and self.bnb_abit_quant_type == "fp4":
													return "fp4"
							elif self.load_in_abit and self.bnb_abit_quant_type == "nf4":
													return "nf4"
							else:
													return None






	@classmethod
	def       _a(cls				: List[Any]      ,	snake_case				: str      ,	snake_case				: Any      ,	**snake_case				: Tuple    ) ->			Optional[Any]:
							_lowercase       :	Dict           =   cls(**snake_case    )

							_lowercase       :	Optional[int]           =   []
							for key, value in kwargs.items():
													if hasattr(snake_case      ,	snake_case    ):
																			setattr(snake_case      ,	snake_case      ,	snake_case    )
																			to_remove.append(snake_case    )
							for key in to_remove:
													kwargs.pop(snake_case      ,	snake_case    )

							if return_unused_kwargs:
													return config, kwargs
							else:
													return config






	def       _a(self				: int      ,	snake_case				: Union[str, os.PathLike]    ) ->			Union[str, Any]:
							with open(snake_case      ,	"w"      ,	encoding="utf-8"    ) as writer:
													_lowercase       :	str           =   self.to_dict()
													_lowercase       :	Optional[int]           =   json.dumps(snake_case      ,	indent=2      ,	sort_keys=snake_case    ) + "\n"

													writer.write(snake_case    )






	def       _a(self				: Optional[Any]    ) ->			Dict[str, Any]:
							_lowercase       :	List[Any]           =   copy.deepcopy(self.__dict__    )
							_lowercase       :	str           =   str(output["bnb_4bit_compute_dtype"]    ).split("."    )[1]

							return output






	def __repr__(self				: Union[str, Any]    ) ->			int:
							return F"""{self.__class__.__name__} {self.to_json_string()}"""






	def       _a(self				: List[Any]      ,	snake_case				: bool = True    ) ->			str:
							if use_diff is True:
													_lowercase       :	Optional[Any]           =   self.to_diff_dict()
							else:
													_lowercase       :	List[str]           =   self.to_dict()
							return json.dumps(snake_case      ,	indent=2      ,	sort_keys=snake_case    ) + "\n"






	def       _a(self				: Optional[Any]    ) ->			Dict[str, Any]:
							_lowercase       :	Dict           =   self.to_dict()

							# get the default config dict
							_lowercase       :	Dict           =   BitsAndBytesConfig().to_dict()

							_lowercase       :	Dict           =   {}

							# only serialize values that differ from the default config
							for key, value in config_dict.items():
													if value != default_config_dict[key]:
																			_lowercase       :	Optional[Any]           =   value

							return serializable_config_dict






import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union




@dataclass
class   __lowercase						:
	_A       =   None
	_A       =   False
	_A       =   False
	_A       =   False
	_A       =   None
	_A       =   None
	_A       =   False
	_A       =   False
	_A       =   False
	_A       =   True
	_A       =   None
	_A       =   1
	_A       =   None
	_A       =   False
	_A       =   None
	_A       =   None






	def       _a(self				: str    ) ->			"DownloadConfig":
							return self.__class__(**{k: copy.deepcopy(snake_case    ) for k, v in self.__dict__.items()}    )




