'''simple docstring'''




from __future__ import annotations

def 	UpperCamelCase_							(					_UpperCAmelCase  :      list[int | str]    )    ->    None:


       """simple docstring"""







       create_state_space_tree(_UpperCAmelCase			,	[]			,	0			,	[0 for i in range(len(_UpperCAmelCase    )    )]    )

def 	UpperCamelCase_							(					_UpperCAmelCase  :      list[int | str]			,	_UpperCAmelCase  :      list[int | str]			,	_UpperCAmelCase  :      int			,	_UpperCAmelCase  :      list[int]			,	)    ->    None:


       """simple docstring"""







       if index == len(_UpperCAmelCase    ):
              print(_UpperCAmelCase    )
              return

       for i in range(len(_UpperCAmelCase    )    ):
              if not index_used[i]:
                     current_sequence.append(sequence[i]    )
                     _UpperCAmelCase     :  List[str]							      =    True
                     create_state_space_tree(_UpperCAmelCase			,	_UpperCAmelCase			,	index + 1			,	_UpperCAmelCase    )
                     current_sequence.pop()
                     _UpperCAmelCase     :  int							      =    False
__SCREAMING_SNAKE_CASE       :     list[int | str]     =  [3, 1, 2, 4]
generate_all_permutations(sequence)

__SCREAMING_SNAKE_CASE       :     list[int | str]     =  ["A", "B", "C"]


generate_all_permutations(sequence_a)


'''simple docstring'''




from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE       :     Optional[int]     =  {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE       :     Tuple     =  ["""GPTNeoXTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE       :     Dict     =  [
      """GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GPTNeoXForCausalLM""",
      """GPTNeoXForQuestionAnswering""",
      """GPTNeoXForSequenceClassification""",
      """GPTNeoXForTokenClassification""",
      """GPTNeoXLayer""",
      """GPTNeoXModel""",
      """GPTNeoXPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gpt_neox import (
        GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTNeoXForCausalLM,
        GPTNeoXForQuestionAnswering,
        GPTNeoXForSequenceClassification,
        GPTNeoXForTokenClassification,
        GPTNeoXLayer,
        GPTNeoXModel,
        GPTNeoXPreTrainedModel,
    )


else:
  import sys

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

