




"""simple docstring"""




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


a_	   =    logging.get_logger(__name__)

@dataclass
class    UpperCAmelCase_  :
		def __init__(		self							,		UpperCamelCase_=False							,		UpperCamelCase_=False							,		UpperCamelCase_=6.0							,		UpperCamelCase_=None							,		UpperCamelCase_=False							,		UpperCamelCase_=False							,		UpperCamelCase_=None							,		UpperCamelCase_="fp4"							,		UpperCamelCase_=False							,		**UpperCamelCase_							,		)		->    List[str]:
					__lowercase       :   Dict        =    load_in_abit
					__lowercase       :   Union[str, Any]        =    load_in_abit
					__lowercase       :   Optional[int]        =    llm_inta_threshold
					__lowercase       :   Union[str, Any]        =    llm_inta_skip_modules
					__lowercase       :   Dict        =    llm_inta_enable_fpaa_cpu_offload
					__lowercase       :   List[str]        =    llm_inta_has_fpaa_weight
					__lowercase       :   Tuple        =    bnb_abit_quant_type
					__lowercase       :   Union[str, Any]        =    bnb_abit_use_double_quant

					if bnb_abit_compute_dtype is None:
								__lowercase       :   Tuple        =    torch.floataa
					elif isinstance(UpperCamelCase__							,		UpperCamelCase__    ):
								__lowercase       :   List[Any]        =    getattr(UpperCamelCase__							,		UpperCamelCase__    )
					elif isinstance(UpperCamelCase__							,		torch.dtype    ):
								__lowercase       :   Any        =    bnb_abit_compute_dtype
					else:
								raise ValueError('''bnb_4bit_compute_dtype must be a string or a torch.dtype'''    )

					self.post_init()
		def      _lowerCamelCase				(		self    )		->    int:


					if not isinstance(self.llm_inta_threshold							,		UpperCamelCase__    ):
								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							,		UpperCamelCase__    ):
								raise ValueError('''llm_int8_skip_modules must be a list of strings'''    )
					if not isinstance(self.llm_inta_enable_fpaa_cpu_offload							,		UpperCamelCase__    ):
								raise ValueError('''llm_int8_enable_fp32_cpu_offload must be a boolean'''    )

					if not isinstance(self.llm_inta_has_fpaa_weight							,		UpperCamelCase__    ):
								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							,		UpperCamelCase__    ):
								raise ValueError('''bnb_4bit_quant_type must be a string'''    )

					if not isinstance(self.bnb_abit_use_double_quant							,		UpperCamelCase__    ):
								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      _lowerCamelCase				(		self    )		->    Dict:
					return self.load_in_abit or self.load_in_abit
		def      _lowerCamelCase				(		self    )		->    Dict:


					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      _lowerCamelCase				(		cls							,		UpperCamelCase_							,		UpperCamelCase_							,		**UpperCamelCase_    )		->    Union[str, Any]:
					__lowercase       :   List[Any]        =    cls(**UpperCamelCase__    )

					__lowercase       :   Optional[Any]        =    []
					for key, value in kwargs.items():
								if hasattr(UpperCamelCase__							,		UpperCamelCase__    ):
											setattr(UpperCamelCase__							,		UpperCamelCase__							,		UpperCamelCase__    )
											to_remove.append(UpperCamelCase__    )
					for key in to_remove:
								kwargs.pop(UpperCamelCase__							,		UpperCamelCase__    )

					if return_unused_kwargs:
								return config, kwargs
					else:
								return config
		def      _lowerCamelCase				(		self							,		UpperCamelCase_    )		->    Tuple:


					with open(UpperCamelCase__							,		'''w'''							,		encoding='''utf-8'''    ) as writer:
								__lowercase       :   Optional[Any]        =    self.to_dict()
								__lowercase       :   List[Any]        =    json.dumps(UpperCamelCase__							,		indent=2							,		sort_keys=UpperCamelCase__    ) + "\n"

								writer.write(UpperCamelCase__    )
		def      _lowerCamelCase				(		self    )		->    Dict[str, Any]:
					__lowercase       :   Union[str, Any]        =    copy.deepcopy(self.__dict__    )
					__lowercase       :   Union[str, Any]        =    str(output['''bnb_4bit_compute_dtype''']    ).split('''.'''    )[1]

					return output
		def __repr__(		self    )		->    int:
					return F"""{self.__class__.__name__} {self.to_json_string()}"""
		def      _lowerCamelCase				(		self							,		UpperCamelCase_ = True    )		->    str:


					if use_diff is True:
								__lowercase       :   Dict        =    self.to_diff_dict()
					else:
								__lowercase       :   Optional[Any]        =    self.to_dict()
					return json.dumps(UpperCamelCase__							,		indent=2							,		sort_keys=UpperCamelCase__    ) + "\n"
		def      _lowerCamelCase				(		self    )		->    Dict[str, Any]:
					__lowercase       :   int        =    self.to_dict()

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

					__lowercase       :   List[Any]        =    {}

					# 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






"""simple docstring"""


import pytest

from datasets import inspect_metric, list_metrics, load_metric






@pytest.fixture
def     a__    (    __SCREAMING_SNAKE_CASE )	->	Union[str, Any]:
		monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings"					, set() )






@pytest.fixture
def     a__    (    __SCREAMING_SNAKE_CASE )	->	str:





		class     snake_case	:

						def __init__(	self							:				int     ,  UpperCamelCase__							:				Optional[int])->   Union[str, Any]:



								'''simple docstring'''


								__lowerCAmelCase:       str          =			metric_id





		class     snake_case	:
						SCREAMING_SNAKE_CASE_   :      List[Any]         =  [MetricMock(__snake_case  ) for metric_id in ["""accuracy""", """mse""", """precision""", """codeparrot/apps_metric"""]]

						def 							lowercase_     (	self							:				Tuple)->   Union[str, Any]:



								'''simple docstring'''


								return self._metrics


		monkeypatch.setattr("datasets.inspect.huggingface_hub"					, HfhMock() )






@pytest.mark.parametrize(
    "func, args"					, [(load_metric, ("metrics/mse",)), (list_metrics, ()), (inspect_metric, ("metrics/mse", "tmp_path"))] )
def     a__    (    __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE )	->	Optional[Any]:
		if "tmp_path" in args:
				__lowerCAmelCase:       Tuple          =			tuple(arg if arg != "tmp_path" else tmp_path for arg in args )
		with pytest.warns(__SCREAMING_SNAKE_CASE					, match="https://huggingface.co/docs/evaluate" ):
				func(*__SCREAMING_SNAKE_CASE )


