





"""simple docstring"""
def 						_SCREAMING_SNAKE_CASE       (_UpperCAmelCase :  str   ,			_UpperCAmelCase :  str   ,			_UpperCAmelCase :  int   ,			_UpperCAmelCase :  int   ,			_UpperCAmelCase :  int   ,			_UpperCAmelCase :  int   ,			):
 lowerCAmelCase  							=      list(_UpperCAmelCase       )
 lowerCAmelCase  							=      list(_UpperCAmelCase       )
 lowerCAmelCase  							=      len(_UpperCAmelCase       )
 lowerCAmelCase  							=      len(_UpperCAmelCase       )

 lowerCAmelCase  							=      [
     [0 for _ in range(len_destination_seq + 1       )] for _ in range(len_source_seq + 1       )
 ]
 lowerCAmelCase  							=      [
     ['0' for _ in range(len_destination_seq + 1       )] for _ in range(len_source_seq + 1       )
 ]

 for i in range(1   ,			len_source_seq + 1       ):
  lowerCAmelCase  							=      i * delete_cost
  lowerCAmelCase  							=      F'D{source_seq[i - 1]:c}'

 for i in range(1   ,			len_destination_seq + 1       ):
  lowerCAmelCase  							=      i * insert_cost
  lowerCAmelCase  							=      F'I{destination_seq[i - 1]:c}'

 for i in range(1   ,			len_source_seq + 1       ):
  for j in range(1   ,			len_destination_seq + 1       ):
   if source_seq[i - 1] == destination_seq[j - 1]:
    lowerCAmelCase  							=      costs[i - 1][j - 1] + copy_cost
    lowerCAmelCase  							=      F'C{source_seq[i - 1]:c}'
   else:
    lowerCAmelCase  							=      costs[i - 1][j - 1] + replace_cost
    lowerCAmelCase  							=      F'R{source_seq[i - 1]:c}' + str(destination_seq[j - 1]       )

   if costs[i - 1][j] + delete_cost < costs[i][j]:
    lowerCAmelCase  							=      costs[i - 1][j] + delete_cost
    lowerCAmelCase  							=      F'D{source_seq[i - 1]:c}'

   if costs[i][j - 1] + insert_cost < costs[i][j]:
    lowerCAmelCase  							=      costs[i][j - 1] + insert_cost
    lowerCAmelCase  							=      F'I{destination_seq[j - 1]:c}'

 return costs, ops

def 						_SCREAMING_SNAKE_CASE       (_UpperCAmelCase :  list[list[str]]   ,			_UpperCAmelCase :  int   ,			_UpperCAmelCase :  int       ):
 if i == 0 and j == 0:
  return []
 else:
  if ops[i][j][0] == "C" or ops[i][j][0] == "R":
   lowerCAmelCase  							=      assemble_transformation(_UpperCAmelCase   ,			i - 1   ,			j - 1       )
   seq.append(ops[i][j]       )
   return seq
  elif ops[i][j][0] == "D":
   lowerCAmelCase  							=      assemble_transformation(_UpperCAmelCase   ,			i - 1   ,			_UpperCAmelCase       )
   seq.append(ops[i][j]       )
   return seq
  else:
   lowerCAmelCase  							=      assemble_transformation(_UpperCAmelCase   ,			_UpperCAmelCase   ,			j - 1       )
   seq.append(ops[i][j]       )
   return seq


if __name__ == "__main__":
       __UpperCamelCase    ,__UpperCamelCase			:		Dict		    =   compute_transform_tables('''Python''', '''Algorithms''', -1, 1, 2, 2)

       __UpperCamelCase			:		int		    =   len(operations)
       __UpperCamelCase			:		Optional[Any]		    =   len(operations[0])
       __UpperCamelCase			:		Union[str, Any]		    =   assemble_transformation(operations, m - 1, n - 1)

       __UpperCamelCase			:		Optional[Any]		    =   list('''Python''')
       __UpperCamelCase			:		Optional[Any]		    =   0
       __UpperCamelCase			:		str		    =   0

       with open('''min_cost.txt''', '''w''') as file:
              for op in sequence:
                     print(''''''.join(string))

                     if op[0] == "C":
                            file.write('''%-16s''' % '''Copy %c''' % op[1])
                            file.write('''\t\t\t''' + ''''''.join(string))
                            file.write('''\r\n''')

                            cost -= 1
                     elif op[0] == "R":
                            __UpperCamelCase			:		int		    =   op[2]

                            file.write('''%-16s''' % ('''Replace %c''' % op[1] + ''' with ''' + str(op[2])))
                            file.write('''\t\t''' + ''''''.join(string))
                            file.write('''\r\n''')

                            cost += 1
                     elif op[0] == "D":
                            string.pop(i)

                            file.write('''%-16s''' % '''Delete %c''' % op[1])
                            file.write('''\t\t\t''' + ''''''.join(string))
                            file.write('''\r\n''')

                            cost += 2
                     else:
                            string.insert(i, op[1])

                            file.write('''%-16s''' % '''Insert %c''' % op[1])
                            file.write('''\t\t\t''' + ''''''.join(string))
                            file.write('''\r\n''')

                            cost += 2

                     i += 1

              print(''''''.join(string))
              print('''Cost: ''', cost)

              file.write('''\r\nMinimum cost: ''' + str(cost))












"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import is_detectrona_available, logging


__UpperCamelCase			:		List[Any]		    =   logging.get_logger(__name__)

__UpperCamelCase			:		Union[str, Any]		    =   {
    '''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 	a				(					a__   ):
 snake_case__    	=    '''layoutlmv2'''



 def __init__(			self							,    _snake_case=3_05_22							,    _snake_case=7_68							,    _snake_case=12							,    _snake_case=12							,    _snake_case=30_72							,    _snake_case="gelu"							,    _snake_case=0.1							,    _snake_case=0.1							,    _snake_case=5_12							,    _snake_case=2							,    _snake_case=0.02							,    _snake_case=1E-12							,    _snake_case=0							,    _snake_case=10_24							,    _snake_case=1_28							,    _snake_case=32							,    _snake_case=True							,    _snake_case=2_56							,    _snake_case=64							,    _snake_case=True							,    _snake_case=[7, 7, 2_56]							,    _snake_case=1_28							,    _snake_case=1_28							,    _snake_case=True							,    _snake_case=True							,    _snake_case=False							,    _snake_case=None							,    **_snake_case							,    ):







  """simple docstring"""






  super().__init__(
      vocab_size=_snake_case							,    hidden_size=_snake_case							,    num_hidden_layers=_snake_case							,    num_attention_heads=_snake_case							,    intermediate_size=_snake_case							,    hidden_act=_snake_case							,    hidden_dropout_prob=_snake_case							,    attention_probs_dropout_prob=_snake_case							,    max_position_embeddings=_snake_case							,    type_vocab_size=_snake_case							,    initializer_range=_snake_case							,    layer_norm_eps=_snake_case							,    pad_token_id=_snake_case							,    **_snake_case							,    )
  lowerCAmelCase  							=      max_ad_position_embeddings
  lowerCAmelCase  							=      max_rel_pos
  lowerCAmelCase  							=      rel_pos_bins
  lowerCAmelCase  							=      fast_qkv
  lowerCAmelCase  							=      max_rel_ad_pos
  lowerCAmelCase  							=      rel_ad_pos_bins
  lowerCAmelCase  							=      convert_sync_batchnorm
  lowerCAmelCase  							=      image_feature_pool_shape
  lowerCAmelCase  							=      coordinate_size
  lowerCAmelCase  							=      shape_size
  lowerCAmelCase  							=      has_relative_attention_bias
  lowerCAmelCase  							=      has_spatial_attention_bias
  lowerCAmelCase  							=      has_visual_segment_embedding
  lowerCAmelCase  							=      (
      detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
  )



 @classmethod
 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  return {
      "MODEL.MASK_ON": True,
      "MODEL.PIXEL_STD": [57.375, 57.120, 58.395],
      "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
      "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
      "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [1_28], [2_56], [5_12]],
      "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
      "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 20_00,
      "MODEL.RPN.PRE_NMS_TOPK_TEST": 10_00,
      "MODEL.RPN.POST_NMS_TOPK_TRAIN": 10_00,
      "MODEL.POST_NMS_TOPK_TEST": 10_00,
      "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": 14,
      "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead",
      "MODEL.ROI_MASK_HEAD.NUM_CONV": 4,
      "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7,
      "MODEL.RESNETS.DEPTH": 1_01,
      "MODEL.RESNETS.SIZES": [[32], [64], [1_28], [2_56], [5_12]],
      "MODEL.RESNETS.ASPECT_RATIOS": [[0.5, 1.0, 2.0]],
      "MODEL.RESNETS.OUT_FEATURES": ["res2", "res3", "res4", "res5"],
      "MODEL.RESNETS.NUM_GROUPS": 32,
      "MODEL.RESNETS.WIDTH_PER_GROUP": 8,
      "MODEL.RESNETS.STRIDE_IN_1X1": False,
  }



 def 					UpperCamelCase__   (			self			):







  """simple docstring"""






  lowerCAmelCase  							=      detectrona.config.get_cfg()
  for k, v in self.detectrona_config_args.items():
   lowerCAmelCase  							=      k.split('.'			)
   lowerCAmelCase  							=      detectrona_config
   for attribute in attributes[:-1]:
    lowerCAmelCase  							=      getattr(_snake_case							,    _snake_case			)
   setattr(_snake_case							,    attributes[-1]							,    _snake_case			)

  return detectrona_config





