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


lowercase__				:				int						=      logging.get_logger(__name__)

lowercase__				:				List[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 							SCREAMING_SNAKE_CASE__     (				SCREAMING_SNAKE_CASE_     ):

							"""simple docstring"""






							_snake_case  		=	'layoutlmv2'



							def __init__(	self  ,						SCREAMING_SNAKE_CASE_=30522  ,						SCREAMING_SNAKE_CASE_=768  ,						SCREAMING_SNAKE_CASE_=12  ,						SCREAMING_SNAKE_CASE_=12  ,						SCREAMING_SNAKE_CASE_=3072  ,						SCREAMING_SNAKE_CASE_="gelu"  ,						SCREAMING_SNAKE_CASE_=0.1  ,						SCREAMING_SNAKE_CASE_=0.1  ,						SCREAMING_SNAKE_CASE_=512  ,						SCREAMING_SNAKE_CASE_=2  ,						SCREAMING_SNAKE_CASE_=0.0_2  ,						SCREAMING_SNAKE_CASE_=1E-12  ,						SCREAMING_SNAKE_CASE_=0  ,						SCREAMING_SNAKE_CASE_=1024  ,						SCREAMING_SNAKE_CASE_=128  ,						SCREAMING_SNAKE_CASE_=32  ,						SCREAMING_SNAKE_CASE_=True  ,						SCREAMING_SNAKE_CASE_=256  ,						SCREAMING_SNAKE_CASE_=64  ,						SCREAMING_SNAKE_CASE_=True  ,						SCREAMING_SNAKE_CASE_=[7, 7, 256]  ,						SCREAMING_SNAKE_CASE_=128  ,						SCREAMING_SNAKE_CASE_=128  ,						SCREAMING_SNAKE_CASE_=True  ,						SCREAMING_SNAKE_CASE_=True  ,						SCREAMING_SNAKE_CASE_=False  ,						SCREAMING_SNAKE_CASE_=None  ,						**SCREAMING_SNAKE_CASE_  ,						)-> int:





													'''simple docstring'''






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



							@classmethod
							def      A__		(	self      )-> Optional[int]:





													'''simple docstring'''






													return {
													    "MODEL.MASK_ON": True,
													    "MODEL.PIXEL_STD": [5_7.3_7_5, 5_7.1_2_0, 5_8.3_9_5],
													    "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
													    "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
													    "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [128], [256], [512]],
													    "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
													    "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2000,
													    "MODEL.RPN.PRE_NMS_TOPK_TEST": 1000,
													    "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1000,
													    "MODEL.POST_NMS_TOPK_TEST": 1000,
													    "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": 101,
													    "MODEL.RESNETS.SIZES": [[32], [64], [128], [256], [512]],
													    "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      A__		(	self      )-> Optional[int]:





													'''simple docstring'''






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

													return detectrona_config









'''simple docstring'''







def 			_lowerCAmelCase(      UpperCAmelCase_      :	str					, UpperCAmelCase_      :	str					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int					, ) ->							tuple[list[list[int]], list[list[str]]]:
							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 			_lowerCAmelCase(      UpperCAmelCase_      :	list[list[str]]					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int						) ->							list[str]:
							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  						=			compute_transform_tables("""Python""", """Algorithms""", -1, 1, 2, 2)

		_UpperCamelCase  						=			len(operations)
		_UpperCamelCase  						=			len(operations[0])
		_UpperCamelCase  						=			assemble_transformation(operations, m - 1, n - 1)

		_UpperCamelCase  						=			list("""Python""")
		_UpperCamelCase  						=			0
		_UpperCamelCase  						=			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  						=			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))





