



'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


_lowerCAmelCase										=     logging.get_logger(__name__)






class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_					):
		'''simple docstring'''




		__lowercase							:				List[Any]           =				'''maskformer-swin'''

		__lowercase							:				Optional[int]           =				{
		    '''num_attention_heads''': '''num_heads''',
		    '''num_hidden_layers''': '''num_layers''',
		}




		def __init__(   self  ,__UpperCAmelCase=224  ,__UpperCAmelCase=4  ,__UpperCAmelCase=3  ,__UpperCAmelCase=96  ,__UpperCAmelCase=[2, 2, 6, 2]  ,__UpperCAmelCase=[3, 6, 12, 24]  ,__UpperCAmelCase=7  ,__UpperCAmelCase=4.0  ,__UpperCAmelCase=True  ,__UpperCAmelCase=0.0  ,__UpperCAmelCase=0.0  ,__UpperCAmelCase=0.1  ,__UpperCAmelCase="gelu"  ,__UpperCAmelCase=False  ,__UpperCAmelCase=0.0_2  ,__UpperCAmelCase=1E-5  ,__UpperCAmelCase=None  ,__UpperCAmelCase=None  ,**__UpperCAmelCase  ,)   ->		int:
						super().__init__(**__UpperCAmelCase				)

						lowerCAmelCase__			:  Dict											= image_size
						lowerCAmelCase__			:  Optional[Any]											= patch_size
						lowerCAmelCase__			:  int											= num_channels
						lowerCAmelCase__			:  str											= embed_dim
						lowerCAmelCase__			:  Tuple											= depths
						lowerCAmelCase__			:  Optional[Any]											= len(__UpperCAmelCase				)
						lowerCAmelCase__			:  Any											= num_heads
						lowerCAmelCase__			:  str											= window_size
						lowerCAmelCase__			:  List[str]											= mlp_ratio
						lowerCAmelCase__			:  List[Any]											= qkv_bias
						lowerCAmelCase__			:  List[Any]											= hidden_dropout_prob
						lowerCAmelCase__			:  Any											= attention_probs_dropout_prob
						lowerCAmelCase__			:  Tuple											= drop_path_rate
						lowerCAmelCase__			:  int											= hidden_act
						lowerCAmelCase__			:  Any											= use_absolute_embeddings
						lowerCAmelCase__			:  str											= layer_norm_eps
						lowerCAmelCase__			:  Dict											= initializer_range
						# we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
						# this indicates the channel dimension after the last stage of the model
						lowerCAmelCase__			:  List[str]											= int(embed_dim * 2 ** (len(__UpperCAmelCase				) - 1)				)
						lowerCAmelCase__			:  Dict											= ["""stem"""] + [F"""stage{idx}""" for idx in range(1  ,len(__UpperCAmelCase				) + 1				)]
						lowerCAmelCase__			:  Any											= get_aligned_output_features_output_indices(
						    out_features=__UpperCAmelCase  ,out_indices=__UpperCAmelCase  ,stage_names=self.stage_names				)







'''simple docstring'''





class 	lowerCAmelCase_:
  '''simple docstring'''




  def __init__(   self  ,__UpperCAmelCase				)   ->		Tuple:
      lowerCAmelCase__			:  Union[str, Any]											= n
      lowerCAmelCase__			:  int											= [None] * self.n
      lowerCAmelCase__			:  Union[str, Any]											= 0  # index of the first element
      lowerCAmelCase__			:  Union[str, Any]											= 0
      lowerCAmelCase__			:  Union[str, Any]											= 0




  def __len__(   self				)   ->		int:
      return self.size




  def 							UpperCAmelCase_     (   self				)   ->		bool:
      return self.size == 0




  def 							UpperCAmelCase_     (   self				)   ->		Optional[Any]:
      return False if self.is_empty() else self.array[self.front]




  def 							UpperCAmelCase_     (   self  ,__UpperCAmelCase				)   ->		Union[str, Any]:
      if self.size >= self.n:
          raise Exception("""QUEUE IS FULL"""				)

      lowerCAmelCase__			:  str											= data
      lowerCAmelCase__			:  List[str]											= (self.rear + 1) % self.n
      self.size += 1
      return self






  def 							UpperCAmelCase_     (   self				)   ->		int:
      if self.size == 0:
          raise Exception("""UNDERFLOW"""				)

      lowerCAmelCase__			:  int											= self.array[self.front]
      lowerCAmelCase__			:  Optional[Any]											= None
      lowerCAmelCase__			:  int											= (self.front + 1) % self.n
      self.size -= 1
      return temp


