
'''simple docstring'''







from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE		:  Optional[Any]        =      {"configuration_gptj": ["GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTJConfig", "GPTJOnnxConfig"]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE		:  Dict        =      [
					    "GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "GPTJForCausalLM",
					    "GPTJForQuestionAnswering",
					    "GPTJForSequenceClassification",
					    "GPTJModel",
					    "GPTJPreTrainedModel",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE		:  Optional[Any]        =      [
					    "TFGPTJForCausalLM",
					    "TFGPTJForQuestionAnswering",
					    "TFGPTJForSequenceClassification",
					    "TFGPTJModel",
					    "TFGPTJPreTrainedModel",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE		:  List[str]        =      [
					    "FlaxGPTJForCausalLM",
					    "FlaxGPTJModel",
					    "FlaxGPTJPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_gptj import GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTJConfig, GPTJOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gptj import (
										    GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTJForCausalLM,
										    GPTJForQuestionAnswering,
										    GPTJForSequenceClassification,
										    GPTJModel,
										    GPTJPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_gptj import (
										    TFGPTJForCausalLM,
										    TFGPTJForQuestionAnswering,
										    TFGPTJForSequenceClassification,
										    TFGPTJModel,
										    TFGPTJPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_gptj import FlaxGPTJForCausalLM, FlaxGPTJModel, FlaxGPTJPreTrainedModel

else:
					import sys

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







def     __UpperCAmelCase							(       UpperCAmelCase_       :							str    )				->     str:

	'''simple docstring'''





	return " ".join(sorted(set(sentence.split()    )    )    )


if __name__ == "__main__":
	import doctest

	doctest.testmod()





