





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


snake_case_     :       Union[str, Any]						=  {
    "configuration_blenderbot_small": [
        "BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotSmallConfig",
        "BlenderbotSmallOnnxConfig",
    ],
    "tokenization_blenderbot_small": ["BlenderbotSmallTokenizer"],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_     :       List[Any]						=  ["BlenderbotSmallTokenizerFast"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_     :       Dict						=  [
					    "BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "BlenderbotSmallForCausalLM",
					    "BlenderbotSmallForConditionalGeneration",
					    "BlenderbotSmallModel",
					    "BlenderbotSmallPreTrainedModel",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_     :       List[str]						=  [
					    "TFBlenderbotSmallForConditionalGeneration",
					    "TFBlenderbotSmallModel",
					    "TFBlenderbotSmallPreTrainedModel",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_     :       Tuple						=  [
					    "FlaxBlenderbotSmallForConditionalGeneration",
					    "FlaxBlenderbotSmallModel",
					    "FlaxBlenderbotSmallPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_blenderbot_small import (
					    BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    BlenderbotSmallConfig,
					    BlenderbotSmallOnnxConfig,
					)
					from .tokenization_blenderbot_small import BlenderbotSmallTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_blenderbot_small_fast import BlenderbotSmallTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_blenderbot_small import (
										    BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BlenderbotSmallForCausalLM,
										    BlenderbotSmallForConditionalGeneration,
										    BlenderbotSmallModel,
										    BlenderbotSmallPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_blenderbot_small import (
										    TFBlenderbotSmallForConditionalGeneration,
										    TFBlenderbotSmallModel,
										    TFBlenderbotSmallPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_blenderbot_small import (
										    FlaxBlenderbotSmallForConditionalGeneration,
										    FlaxBlenderbotSmallModel,
										    FlaxBlenderbotSmallPreTrainedModel,
										)

else:
					import sys

					snake_case_     :       str						=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)












'''simple docstring'''







def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			list[int]   ) ->	list[list[int]]:
						UpperCAmelCase_			:      int     						=  []
						if len(SCREAMING_SNAKE_CASE__   ) == 1:
												return [nums.copy()]
						for _ in range(len(SCREAMING_SNAKE_CASE__   )   ):
												UpperCAmelCase_			:      List[Any]     						=  nums.pop(0   )
												UpperCAmelCase_			:      Optional[Any]     						=  permute(SCREAMING_SNAKE_CASE__   )
												for perm in permutations:
																		perm.append(SCREAMING_SNAKE_CASE__   )
												result.extend(SCREAMING_SNAKE_CASE__   )
												nums.append(SCREAMING_SNAKE_CASE__   )
						return result





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			List[str]   ) ->	Any:

						def backtrack(SCREAMING_SNAKE_CASE__      :			Union[str, Any]   ):
												if start == len(SCREAMING_SNAKE_CASE__   ) - 1:
																		output.append(nums[:]   )
												else:
																		for i in range(SCREAMING_SNAKE_CASE__,			len(SCREAMING_SNAKE_CASE__   )   ):
																								UpperCAmelCase_						,       UpperCAmelCase_			:      Tuple     						=  nums[i], nums[start]
																								backtrack(start + 1   )
																								UpperCAmelCase_						,       UpperCAmelCase_			:      int     						=  nums[i], nums[start]  # backtrack

						UpperCAmelCase_			:      Optional[int]     						=  []
						backtrack(0   )
						return output


if __name__ == "__main__":
					import doctest

					# use res to print the data in permute2 function
					snake_case_     :       Tuple						=  permutea([1, 2, 3])
					print(res)
					doctest.testmod()





