



'''simple docstring'''
class 							lowercase__	:





	def __init__( self					:				Dict ,lowerCamelCase__					:				int ):







							'''simple docstring'''
							_UpperCamelCase					:		Dict 				=   n
							_UpperCamelCase					:		Optional[int] 				=   [None] * self.n
							_UpperCamelCase					:		List[str] 				=   0  # index of the first element
							_UpperCamelCase					:		Dict 				=   0
							_UpperCamelCase					:		int 				=   0





	def __len__( self					:				Optional[int] ):







							'''simple docstring'''
							return self.size





	def 	UpperCamelCase_  ( self					:				Union[str, Any] ):







							'''simple docstring'''
							return self.size == 0





	def 	UpperCamelCase_  ( self					:				Union[str, Any] ):







							'''simple docstring'''
							return False if self.is_empty() else self.array[self.front]





	def 	UpperCamelCase_  ( self					:				Union[str, Any] ,lowerCamelCase__					:				Tuple ):







							'''simple docstring'''
							if self.size >= self.n:
													raise Exception('QUEUE IS FULL' )

							_UpperCamelCase					:		Optional[int] 				=   data
							_UpperCamelCase					:		Tuple 				=   (self.rear + 1) % self.n
							self.size += 1
							return self





	def 	UpperCamelCase_  ( self					:				Any ):







							'''simple docstring'''
							if self.size == 0:
													raise Exception('UNDERFLOW' )

							_UpperCamelCase					:		List[Any] 				=   self.array[self.front]
							_UpperCamelCase					:		Union[str, Any] 				=   None
							_UpperCamelCase					:		Optional[int] 				=   (self.front + 1) % self.n
							self.size -= 1
							return temp




"""simple docstring"""





from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_a														=		{
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_a														=		[
				    """AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """AutoformerForPrediction""",
				    """AutoformerModel""",
				    """AutoformerPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_autoformer import (
				    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    AutoformerConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_autoformer import (
								    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    AutoformerForPrediction,
								    AutoformerModel,
								    AutoformerPreTrainedModel,
								)

else:
				import sys

				_a														=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






