





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__							:      Tuple         =    {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ReformerConfig"""]}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    ["""ReformerTokenizer"""]

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__							:      Optional[int]         =    ["""ReformerTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__							:      Union[str, Any]         =    [
      """REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """ReformerAttention""",
      """ReformerForMaskedLM""",
      """ReformerForQuestionAnswering""",
      """ReformerForSequenceClassification""",
      """ReformerLayer""",
      """ReformerModel""",
      """ReformerModelWithLMHead""",
      """ReformerPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_reformer import ReformerTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_reformer_fast import ReformerTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_reformer import (
        REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        ReformerAttention,
        ReformerForMaskedLM,
        ReformerForQuestionAnswering,
        ReformerForSequenceClassification,
        ReformerLayer,
        ReformerModel,
        ReformerModelWithLMHead,
        ReformerPreTrainedModel,
    )

else:
  import sys

  SCREAMING_SNAKE_CASE__							:      List[Any]         =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




def a(lowercase__						):





	'''simple docstring'''
	snake_case_   		=			len(lowercase__						)
	for _ in range(lowercase__						):
		for i in range(_ % 2      ,			arr_size - 1      ,			2						):
			if arr[i + 1] < arr[i]:
				snake_case_		,							snake_case_   		=			arr[i + 1], arr[i]

	return arr


if __name__ == "__main__":
		A									=  list(range(10, 0, -1))
		print(f"""Original: {arr}. Sorted: {odd_even_transposition(arr)}""")
