
'''simple docstring'''
from __future__ import annotations

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """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!"       )
    snake_case_ :    Optional[Any]     			=						number_of_bytes // partitions
    snake_case_ :    Dict     			=						[]
    for i in range(__SCREAMING_SNAKE_CASE       ):
        snake_case_ :    List[Any]     			=						i * bytes_per_partition + 1
        snake_case_ :    Any     			=						(
            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'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a_											=						{
    "configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
    "tokenization_biogpt": ["BioGptTokenizer"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_											=						[
      "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BioGptForCausalLM",
      "BioGptForTokenClassification",
      "BioGptForSequenceClassification",
      "BioGptModel",
      "BioGptPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
  from .tokenization_biogpt import BioGptTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_biogpt import (
        BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        BioGptForCausalLM,
        BioGptForSequenceClassification,
        BioGptForTokenClassification,
        BioGptModel,
        BioGptPreTrainedModel,
    )


else:
  import sys

  a_											=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




