

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


lowerCAmelCase__						=	logging.get_logger(__name__)

lowerCAmelCase__						=	{
    """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__  (   snake_case     ):
			"""simple docstring"""







			__lowerCamelCase	    =    'layoutlmv2'


			def __init__(      self , lowercase=30522 , lowercase=768 , lowercase=12 , lowercase=12 , lowercase=3072 , lowercase="gelu" , lowercase=0.1 , lowercase=0.1 , lowercase=512 , lowercase=2 , lowercase=0.02 , lowercase=1e-12 , lowercase=0 , lowercase=1024 , lowercase=128 , lowercase=32 , lowercase=True , lowercase=256 , lowercase=64 , lowercase=True , lowercase=[7, 7, 256] , lowercase=128 , lowercase=128 , lowercase=True , lowercase=True , lowercase=False , lowercase=None , **lowercase , )					->  List[str]:
							'''simple docstring'''






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


			@classmethod
			def        UpperCamelCase						(      self    )					->  Union[str, Any]:
							'''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], [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        UpperCamelCase						(      self    )					->  Optional[int]:
							'''simple docstring'''






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

							return detectrona_config




from .balanced_parentheses import balanced_parentheses
from .stack import Stack



def    lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							str )     -> int:




				'''simple docstring'''





				return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(SCREAMING_SNAKE_CASE_		,    -1 )



def    lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							str )     -> str:




				'''simple docstring'''





				if not balanced_parentheses(SCREAMING_SNAKE_CASE_ ):
								raise ValueError("Mismatched parentheses" )
				A__            =     Stack()
				A__            =     []
				for char in expression_str:
								if char.isalpha() or char.isdigit():
												postfix.append(SCREAMING_SNAKE_CASE_ )
								elif char == "(":
												stack.push(SCREAMING_SNAKE_CASE_ )
								elif char == ")":
												while not stack.is_empty() and stack.peek() != "(":
																postfix.append(stack.pop() )
												stack.pop()
								else:
												while not stack.is_empty() and precedence(SCREAMING_SNAKE_CASE_ ) <= precedence(stack.peek() ):
																postfix.append(stack.pop() )
												stack.push(SCREAMING_SNAKE_CASE_ )
				while not stack.is_empty():
								postfix.append(stack.pop() )
				return " ".join(SCREAMING_SNAKE_CASE_ )


if __name__ == "__main__":
	from doctest import testmod

	testmod()
	lowerCAmelCase__						=	"""a+b*(c^d-e)^(f+g*h)-i"""

	print("""Infix to Postfix Notation demonstration:\n""")
	print("""Infix notation: """ + expression)
	print("""Postfix notation: """ + infix_to_postfix(expression))

