
'''simple docstring'''






class 							_snake_case     :
	"""simple docstring"""





	def __init__(						self				: Optional[int]      ):
			lowerCAmelCase_   :       int    							=[]
			lowerCAmelCase_   :       int    							=0
			lowerCAmelCase_   :       Union[str, Any]    							=0




	def __str__(						self				: str      ):
			lowerCAmelCase_   :       Optional[int]    							='''<''' + str(self.entries      )[1:-1] + '''>'''
			return printed




	def 	__A      (						self				: Dict					,						UpperCamelCase_				: Optional[Any]      ):
			self.entries.append(UpperCamelCase_      )
			lowerCAmelCase_   :       Optional[Any]    							=self.length + 1




	def 	__A      (						self				: Dict      ):
			lowerCAmelCase_   :       Tuple    							=self.length - 1
			lowerCAmelCase_   :       Any    							=self.entries[self.front]
			# self.front-=1
			# self.entries = self.entries[self.front:]
			lowerCAmelCase_   :       List[str]    							=self.entries[1:]
			return dequeued




	def 	__A      (						self				: int					,						UpperCamelCase_				: Dict      ):
			for _ in range(UpperCamelCase_      ):
					self.put(self.get()      )




	def 	__A      (						self				: List[str]      ):
			return self.entries[0]




	def 	__A      (						self				: Any      ):
			return self.length








'''simple docstring'''






from typing import TYPE_CHECKING

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


__lowercase	=    {'''configuration_gptj''': ['''GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTJConfig''', '''GPTJOnnxConfig''']}

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

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    [
							    '''TFGPTJForCausalLM''',
							    '''TFGPTJForQuestionAnswering''',
							    '''TFGPTJForSequenceClassification''',
							    '''TFGPTJModel''',
							    '''TFGPTJPreTrainedModel''',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    [
							    '''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

							__lowercase	=    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






