
from typing import TYPE_CHECKING

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


lowercase_											=	{
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_											=	["""SplinterTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_											=	[
      """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """SplinterForQuestionAnswering""",
      """SplinterForPreTraining""",
      """SplinterLayer""",
      """SplinterModel""",
      """SplinterPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
  from .tokenization_splinter import SplinterTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_splinter_fast import SplinterTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_splinter import (
        SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
        SplinterForPreTraining,
        SplinterForQuestionAnswering,
        SplinterLayer,
        SplinterModel,
        SplinterPreTrainedModel,
    )


else:
  import sys

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


from collections import defaultdict


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					defaultdict[str, int]			=						defaultdict(snake_case    )
  # Creating a dictionary containing count of each word
  for word in sentence.split():
    occurrence[word] += 1
  return occurrence


if __name__ == "__main__":
   for word, count in word_occurrence("""INPUT STRING""").items():
      print(f'''{word}: {count}''')
