





"""simple docstring"""




from ...configuration_utils import PretrainedConfig
from ...utils import is_detectrona_available, logging


lowerCamelCase_					:						str      = logging.get_logger(__name__)

lowerCamelCase_					:						Dict      = {
    'layoutlmv2-base-uncased': 'https://huggingface.co/microsoft/layoutlmv2-base-uncased/resolve/main/config.json',
    'layoutlmv2-large-uncased': 'https://huggingface.co/microsoft/layoutlmv2-large-uncased/resolve/main/config.json',
    # See all LayoutLMv2 models at https://huggingface.co/models?filter=layoutlmv2
}

# soft dependency
if is_detectrona_available():
   import detectrona

class 			_UpperCAmelCase  (       lowerCAmelCase__		):



      '''simple docstring'''
      lowercase_				:			Dict        =       """layoutlmv2"""

      def __init__(					self ,				snake_case_=3_0_5_2_2 ,				snake_case_=7_6_8 ,				snake_case_=1_2 ,				snake_case_=1_2 ,				snake_case_=3_0_7_2 ,				snake_case_="gelu" ,				snake_case_=0.1 ,				snake_case_=0.1 ,				snake_case_=5_1_2 ,				snake_case_=2 ,				snake_case_=0.02 ,				snake_case_=1E-12 ,				snake_case_=0 ,				snake_case_=1_0_2_4 ,				snake_case_=1_2_8 ,				snake_case_=3_2 ,				snake_case_=True ,				snake_case_=2_5_6 ,				snake_case_=6_4 ,				snake_case_=True ,				snake_case_=[7, 7, 2_5_6] ,				snake_case_=1_2_8 ,				snake_case_=1_2_8 ,				snake_case_=True ,				snake_case_=True ,				snake_case_=False ,				snake_case_=None ,				**snake_case_ ,				):

        """simple docstring"""

        super().__init__(
            vocab_size=_A ,				hidden_size=_A ,				num_hidden_layers=_A ,				num_attention_heads=_A ,				intermediate_size=_A ,				hidden_act=_A ,				hidden_dropout_prob=_A ,				attention_probs_dropout_prob=_A ,				max_position_embeddings=_A ,				type_vocab_size=_A ,				initializer_range=_A ,				layer_norm_eps=_A ,				pad_token_id=_A ,				**_A ,				)
        A_  :	Any    						=  max_ad_position_embeddings
        A_  :	List[Any]    						=  max_rel_pos
        A_  :	List[str]    						=  rel_pos_bins
        A_  :	Any    						=  fast_qkv
        A_  :	Optional[int]    						=  max_rel_ad_pos
        A_  :	List[str]    						=  rel_ad_pos_bins
        A_  :	Dict    						=  convert_sync_batchnorm
        A_  :	List[Any]    						=  image_feature_pool_shape
        A_  :	Union[str, Any]    						=  coordinate_size
        A_  :	Dict    						=  shape_size
        A_  :	Union[str, Any]    						=  has_relative_attention_bias
        A_  :	Union[str, Any]    						=  has_spatial_attention_bias
        A_  :	Any    						=  has_visual_segment_embedding
        A_  :	Optional[Any]    						=  (
            detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
        )

      @classmethod
      def  lowerCamelCase_      (					self  ):

        """simple docstring"""

        return {
            "MODEL.MASK_ON": True,
            "MODEL.PIXEL_STD": [57.3_75, 57.1_20, 58.3_95],
            "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
            "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
            "MODEL.ANCHOR_GENERATOR.SIZES": [[3_2], [6_4], [1_2_8], [2_5_6], [5_1_2]],
            "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
            "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2_0_0_0,
            "MODEL.RPN.PRE_NMS_TOPK_TEST": 1_0_0_0,
            "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1_0_0_0,
            "MODEL.POST_NMS_TOPK_TEST": 1_0_0_0,
            "MODEL.ROI_HEADS.NAME": "StandardROIHeads",
            "MODEL.ROI_HEADS.NUM_CLASSES": 5,
            "MODEL.ROI_HEADS.IN_FEATURES": ["p2", "p3", "p4", "p5"],
            "MODEL.ROI_BOX_HEAD.NAME": "FastRCNNConvFCHead",
            "MODEL.ROI_BOX_HEAD.NUM_FC": 2,
            "MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION": 1_4,
            "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead",
            "MODEL.ROI_MASK_HEAD.NUM_CONV": 4,
            "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7,
            "MODEL.RESNETS.DEPTH": 1_0_1,
            "MODEL.RESNETS.SIZES": [[3_2], [6_4], [1_2_8], [2_5_6], [5_1_2]],
            "MODEL.RESNETS.ASPECT_RATIOS": [[0.5, 1.0, 2.0]],
            "MODEL.RESNETS.OUT_FEATURES": ["res2", "res3", "res4", "res5"],
            "MODEL.RESNETS.NUM_GROUPS": 3_2,
            "MODEL.RESNETS.WIDTH_PER_GROUP": 8,
            "MODEL.RESNETS.STRIDE_IN_1X1": False,
        }

      def  lowerCamelCase_      (					self  ):

        """simple docstring"""

        A_  :	int    						=  detectrona.config.get_cfg()
        for k, v in self.detectrona_config_args.items():
          A_  :	Optional[Any]    						=  k.split('.'  )
          A_  :	Dict    						=  detectrona_config
          for attribute in attributes[:-1]:
            A_  :	Any    						=  getattr(_A ,				_A  )
          setattr(_A ,				attributes[-1] ,				_A  )

        return detectrona_config






"""simple docstring"""




def 						UpperCAmelCase__		(					_UpperCAmelCase			, _UpperCAmelCase ):






  """simple docstring"""





  A_  :	Any    						=  len(_UpperCAmelCase )
  # Create a stack and push index of fist element to it
  A_  :	List[Any]    						=  []
  st.append(0 )

  # Span value of first element is always 1
  A_  :	List[str]    						=  1

  # Calculate span values for rest of the elements
  for i in range(1			, _UpperCAmelCase ):
    # Pop elements from stack while stack is not
    # empty and top of stack is smaller than price[i]
    while len(_UpperCAmelCase ) > 0 and price[st[0]] <= price[i]:
      st.pop()

    # If stack becomes empty, then price[i] is greater
    # than all elements on left of it, i.e. price[0],
    # price[1], ..price[i-1]. Else the price[i]  is
    # greater than elements after top of stack
    A_  :	Union[str, Any]    						=  i + 1 if len(_UpperCAmelCase ) <= 0 else (i - st[0])

    # Push this element to stack
    st.append(_UpperCAmelCase )





def 						UpperCAmelCase__		(					_UpperCAmelCase			, _UpperCAmelCase ):






  """simple docstring"""





  for i in range(0			, _UpperCAmelCase ):
    print(arr[i]			, end=' ' )


# Driver program to test above function
lowerCamelCase_					:						List[Any]      = [10, 4, 5, 90, 1_20, 80]
lowerCamelCase_					:						Optional[Any]      = [0 for i in range(len(price) + 1)]

# Fill the span values in array S[]
calculation_span(price, S)





print_array(S, len(price))