






import logging
import os

from .state import PartialState



class 							SCREAMING_SNAKE_CASE__		(       logging.LoggerAdapter		):





					"""simple docstring"""






					@staticmethod
					def  _lowercase  (      __A  :						Optional[int] ):
						snake_case__				:   Optional[int]     =						PartialState()
						return not main_process_only or (main_process_only and state.is_main_process)






					def  _lowercase  (      self  :						Dict							,	__A  :						str							,	__A  :						Any							,	*__A  :						Tuple							,	**__A  :						Union[str, Any] ):
						if PartialState._shared_state == {}:
							raise RuntimeError(
							    "You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility." )
						snake_case__				:   int     =						kwargs.pop("main_process_only"							,	__A )
						snake_case__				:   int     =						kwargs.pop("in_order"							,	__A )

						if self.isEnabledFor(__A ):
							if self._should_log(__A ):
								snake_case__,		snake_case__				:   Optional[Any]     =						self.process(__A							,	__A )
								self.logger.log(__A							,	__A							,	*__A							,	**__A )

							elif in_order:
								snake_case__				:   Tuple     =						PartialState()
								for i in range(state.num_processes ):
									if i == state.process_index:
										snake_case__,		snake_case__				:   Dict     =						self.process(__A							,	__A )
										self.logger.log(__A							,	__A							,	*__A							,	**__A )
									state.wait_for_everyone()







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str  ,						snake_case_      :							str = None     ):
	if log_level is None:
		snake_case__				:   str     =						os.environ.get("ACCELERATE_LOG_LEVEL"  ,						snake_case_     )
	snake_case__				:   Any     =						logging.getLogger(snake_case_     )
	if log_level is not None:
		logger.setLevel(log_level.upper()     )
		logger.root.setLevel(log_level.upper()     )
	return MultiProcessAdapter(snake_case_  ,						{}     )











import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate



@dataclass(frozen=UpperCamelCase_		)
class 							SCREAMING_SNAKE_CASE__		(       UpperCamelCase_		):





					"""simple docstring"""






					a_			=	field(default="text-classification"				,     metadata={"include_in_asdict_even_if_is_default": True}		)
					a_			=	Features({"text": Value("string"		)}		)
					a_			=	Features({"labels": ClassLabel}		)
					a_			=	"text"
					a_			=	"labels"



					def  _lowercase  (      self  :						Tuple							,	__A  :						List[Any] ):
						if self.label_column not in features:
							raise ValueError(f'''Column {self.label_column} is not present in features.''' )
						if not isinstance(features[self.label_column]							,	__A ):
							raise ValueError(f'''Column {self.label_column} is not a ClassLabel.''' )
						snake_case__				:   Any     =						copy.deepcopy(self )
						snake_case__				:   Optional[Any]     =						self.label_schema.copy()
						snake_case__				:   List[str]     =						features[self.label_column]
						snake_case__				:   Dict     =						label_schema
						return task_template






					@property
					def  _lowercase  (      self  :						Tuple ):
						return {
						    self.text_column: "text",
						    self.label_column: "labels",
						}



