"""simple docstring"""




import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset





@pytest.mark.parametrize("""dataset_size"""     ,[None, 400 * 2**20, 600 * 2**20]      )
@pytest.mark.parametrize("""input_in_memory_max_size"""     ,["""default""", 0, 100 * 2**20, 900 * 2**20]      )
def 				SCREAMING_SNAKE_CASE	(     _lowerCamelCase		:			str     ,_lowerCamelCase		:			List[Any]     ,_lowerCamelCase		:			Optional[int]      )			-> Union[str, Any]:






  if input_in_memory_max_size != "default":
    monkeypatch.setattr(datasets.config     ,"""IN_MEMORY_MAX_SIZE"""     ,lowerCAmelCase_      )
  _lowerCAmelCase		:			Optional[Any]         =	datasets.config.IN_MEMORY_MAX_SIZE
  if input_in_memory_max_size == "default":
    assert in_memory_max_size == 0
  else:
    assert in_memory_max_size == input_in_memory_max_size
  if dataset_size and in_memory_max_size:
    _lowerCAmelCase		:			int         =	dataset_size < in_memory_max_size
  else:
    _lowerCAmelCase		:			int         =	False
  _lowerCAmelCase		:			Optional[Any]         =	is_small_dataset(lowerCAmelCase_      )
  assert result == expected








import logging
import os

from .state import PartialState


class      __lowerCAmelCase  (			logging.LoggerAdapter       ):






  """simple docstring"""





  @staticmethod
  def        lowerCAmelCase__	(  _lowerCAmelCase							:							int	) ->			Tuple:




     """simple docstring"""
     snake_case_            =       PartialState()
     return not main_process_only or (main_process_only and state.is_main_process)



  def        lowerCAmelCase__	(  self							:							Union[str, Any]     ,					_lowerCAmelCase							:							List[Any]     ,					_lowerCAmelCase							:							Tuple     ,					*_lowerCAmelCase							:							List[Any]     ,					**_lowerCAmelCase							:							Any	) ->			Optional[int]:




     """simple docstring"""
     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_            =       kwargs.pop("main_process_only"     ,					_lowerCAmelCase	)
     snake_case_            =       kwargs.pop("in_order"     ,					_lowerCAmelCase	)

     if self.isEnabledFor(_lowerCAmelCase	):
        if self._should_log(_lowerCAmelCase	):
           snake_case_     ,     snake_case_            =       self.process(_lowerCAmelCase     ,					_lowerCAmelCase	)
           self.logger.log(_lowerCAmelCase     ,					_lowerCAmelCase     ,					*_lowerCAmelCase     ,					**_lowerCAmelCase	)

        elif in_order:
           snake_case_            =       PartialState()
           for i in range(state.num_processes	):
              if i == state.process_index:
                 snake_case_     ,     snake_case_            =       self.process(_lowerCAmelCase     ,					_lowerCAmelCase	)
                 self.logger.log(_lowerCAmelCase     ,					_lowerCAmelCase     ,					*_lowerCAmelCase     ,					**_lowerCAmelCase	)
              state.wait_for_everyone()






def       _lowerCAmelCase    (				lowerCAmelCase_				:str		,    lowerCAmelCase_				:str = None				)->Any:
   '''simple docstring'''






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




