
import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs


@pytest.mark.parametrize(
    'kwargs, expected'   ,	[
        ({'num_shards': 0, 'max_num_jobs': 1}, []),
        ({'num_shards': 10, 'max_num_jobs': 1}, [range(10			)]),
        ({'num_shards': 10, 'max_num_jobs': 10}, [range(_A   ,	i + 1			) for i in range(10			)]),
        ({'num_shards': 1, 'max_num_jobs': 10}, [range(1			)]),
        ({'num_shards': 10, 'max_num_jobs': 3}, [range(0   ,	4			), range(4   ,	7			), range(7   ,	10			)]),
        ({'num_shards': 3, 'max_num_jobs': 10}, [range(0   ,	1			), range(1   ,	2			), range(2   ,	3			)]),
    ]   ,	)
def 				A	( lowercase   ,	lowercase			)       ->  Dict:
		'''simple docstring'''

		UpperCamelCase          =					_distribute_shards(**_A			)
		assert out == expected


@pytest.mark.parametrize(
    'gen_kwargs, max_num_jobs, expected'   ,	[
        ({'foo': 0}, 10, [{'foo': 0}]),
        ({'shards': [0, 1, 2, 3]}, 1, [{'shards': [0, 1, 2, 3]}]),
        ({'shards': [0, 1, 2, 3]}, 4, [{'shards': [0]}, {'shards': [1]}, {'shards': [2]}, {'shards': [3]}]),
        ({'shards': [0, 1]}, 4, [{'shards': [0]}, {'shards': [1]}]),
        ({'shards': [0, 1, 2, 3]}, 2, [{'shards': [0, 1]}, {'shards': [2, 3]}]),
    ]   ,	)
def 				A	( lowercase   ,	lowercase   ,	lowercase			)       ->  str:
		'''simple docstring'''

		UpperCamelCase          =					_split_gen_kwargs(_A   ,	_A			)
		assert out == expected


@pytest.mark.parametrize(
    'gen_kwargs, expected'   ,	[
        ({'foo': 0}, 1),
        ({'shards': [0]}, 1),
        ({'shards': [0, 1, 2, 3]}, 4),
        ({'shards': [0, 1, 2, 3], 'foo': 0}, 4),
        ({'shards': [0, 1, 2, 3], 'other': (0, 1)}, 4),
        ({'shards': [0, 1, 2, 3], 'shards2': [0, 1]}, RuntimeError),
    ]   ,	)
def 				A	( lowercase   ,	lowercase			)       ->  Tuple:
		'''simple docstring'''

		if expected is RuntimeError:
				with pytest.raises(_A			):
						_number_of_shards_in_gen_kwargs(_A			)
		else:
				UpperCamelCase          =					_number_of_shards_in_gen_kwargs(_A			)
				assert out == expected


import logging
import os

from .state import PartialState


class     lowercase (		logging.LoggerAdapter       ):



		@staticmethod
		def __UpperCamelCase			(			A_	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					PartialState()
				return not main_process_only or (main_process_only and state.is_main_process)



		def __UpperCamelCase			(			self    ,				A_    ,				A_    ,				*A_    ,				**A_	)  -> Union[str, Any]:
				"""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.'	)
				UpperCamelCase          =					kwargs.pop('main_process_only'    ,				A_	)
				UpperCamelCase          =					kwargs.pop('in_order'    ,				A_	)

				if self.isEnabledFor(A_	):
						if self._should_log(A_	):
								UpperCamelCase     ,  UpperCamelCase          =					self.process(A_    ,				A_	)
								self.logger.log(A_    ,				A_    ,				*A_    ,				**A_	)

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






def 				A	( lowercase   ,	lowercase = None			)       ->  Dict:
		'''simple docstring'''

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