

from __future__ import annotations

def 	__snake_case		(      __UpperCamelCase     :      int							,__UpperCamelCase     :      int  ):



      """simple docstring"""

      if partitions <= 0:
            raise ValueError("partitions must be a positive number!"  )
      if partitions > number_of_bytes:
            raise ValueError("partitions can not > number_of_bytes!"  )
      A_		   =							number_of_bytes // partitions
      A_		   =							[]
      for i in range(lowerCAmelCase__  ):
            A_		   =							i * bytes_per_partition + 1
            A_		   =							(
                number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
            )
            allocation_list.append(f'''{start_bytes}-{end_bytes}'''  )
      return allocation_list


if __name__ == "__main__":
      import doctest

      doctest.testmod()



"""simple docstring"""




import warnings

from ..trainer import Trainer
from ..utils import logging


lowercase_			     =  logging.get_logger(__name__)
class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		def __init__(  self							, _a=None							, **_a      ):
				warnings.warn(
				    '''`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` '''
				    '''instead.'''							, _a							, )
				super().__init__(args=_a							, **_a      )






