






"""simple docstring"""







from collections import namedtuple

_UpperCamelCase     			=  namedtuple("""from_to""", """from_ to""")

_UpperCamelCase     			=  {
    """millimeter""": """mm""",
    """centimeter""": """cm""",
    """meter""": """m""",
    """kilometer""": """km""",
    """inch""": """in""",
    """inche""": """in""",  # Trailing 's' has been stripped off
    """feet""": """ft""",
    """foot""": """ft""",
    """yard""": """yd""",
    """mile""": """mi""",
}

_UpperCamelCase     			=  {
    """mm""": from_to(0.0_01, 1000),
    """cm""": from_to(0.01, 100),
    """m""": from_to(1, 1),
    """km""": from_to(1000, 0.0_01),
    """in""": from_to(0.02_54, 39.37_01),
    """ft""": from_to(0.30_48, 3.2_80_84),
    """yd""": from_to(0.91_44, 1.0_93_61),
    """mi""": from_to(1609.34, 0.0_00_62_13_71),
}

def _a (		_snake_case      ,       _snake_case      ,       _snake_case							):







      """simple docstring"""






      UpperCAmelCase							=       from_type.lower().rstrip("""s"""							)
      UpperCAmelCase							=       TYPE_CONVERSION.get(_snake_case      ,       _snake_case							)
      UpperCAmelCase							=       to_type.lower().rstrip("""s"""							)
      UpperCAmelCase							=       TYPE_CONVERSION.get(_snake_case      ,       _snake_case							)
      if new_from not in METRIC_CONVERSION:
            UpperCAmelCase							=       (
                F'''Invalid \'from_type\' value: {from_type!r}.\n'''
                F'''Conversion abbreviations are: {', '.join(_snake_case							)}'''
            )
            raise ValueError(_snake_case							)
      if new_to not in METRIC_CONVERSION:
            UpperCAmelCase							=       (
                F'''Invalid \'to_type\' value: {to_type!r}.\n'''
                F'''Conversion abbreviations are: {', '.join(_snake_case							)}'''
            )
            raise ValueError(_snake_case							)
      return value * METRIC_CONVERSION[new_from].from_ * METRIC_CONVERSION[new_to].to


if __name__ == "__main__":
  import doctest

  doctest.testmod()





import torch

from transformers import AutoTokenizer

class 				_UpperCamelCase (    _A     ):






			'''simple docstring'''

			def __init__(				self       :				List[str]  ,		snake_case_       :				Dict					):
							UpperCamelCase_:							int		=  AutoTokenizer.from_pretrained(snake_case_					)

			def 					lowerCAmelCase__		(				self       :				Union[str, Any]  ,		snake_case_       :				Optional[Any]					):

							if isinstance(snake_case_  ,		snake_case_					) and all(isinstance(_x  ,		snake_case_					) for _x in x					):
											UpperCamelCase_:							Tuple		=  None
											for l in x:
															UpperCamelCase_:							Optional[Any]		=  self.tokenizer(
															    snake_case_  ,		padding="""max_length"""  ,		max_length=384  ,		truncation=snake_case_  ,		return_tensors="""pt"""  ,		)
															UpperCamelCase_:							str		=  torch.tensor([len(snake_case_					)]					)
															if d is not None:
																			for k in d.keys():
																							UpperCamelCase_:							List[Any]		=  torch.cat((d[k], t[k])  ,		0					)
															else:
																			UpperCamelCase_:							Optional[int]		=  t

											UpperCamelCase_:							Union[str, Any]		=  torch.tensor(self.tokenizer.convert_tokens_to_ids("""[E]"""					)					)
											UpperCamelCase_:							List[str]		=  torch.tensor(self.tokenizer.convert_tokens_to_ids("""[/E]"""					)					)

							elif isinstance(snake_case_  ,		snake_case_					) and all(isinstance(_x  ,		snake_case_					) for _x in x					):
											UpperCamelCase_:							List[str]		=  self.tokenizer(
											    snake_case_  ,		padding="""max_length"""  ,		max_length=384  ,		truncation=snake_case_  ,		return_tensors="""pt"""  ,		)

							else:
											raise Exception(
											    """Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of"""
											    """ strings` for supports are supported."""					)

							return d




			def 					lowerCAmelCase__		(				self       :				int  ,		snake_case_       :				List[str]  ,		snake_case_       :				Optional[int]  ,		snake_case_       :				Optional[Any]  ,		snake_case_       :				Optional[int]  ,		snake_case_       :				List[Any]=0.70					):
							UpperCamelCase_:							int		=  []
							for idx in range(len(W_query["""input_ids"""]					)					):
											UpperCamelCase_:							List[str]		=  range(p_start.shape[1]					)

											UpperCamelCase_:							str		=  []
											for start_id in start_indexes:
															for end_id in end_indexes:
																			if start_id < end_id:
																							output.append(
																							    (
																							        start_id,
																							        end_id,
																							        p_start[idx][start_id].item(),
																							        p_end[idx][end_id].item(),
																							    )					)

											output.sort(key=lambda snake_case_					: (tup[2] * tup[3])  ,		reverse=snake_case_					)
											UpperCamelCase_:							Optional[int]		=  []
											for k in range(len(snake_case_					)					):
															if output[k][2] * output[k][3] >= thresh:
																			UpperCamelCase_,      UpperCamelCase_:							Tuple		=  output[k][0], output[k][1]
																			UpperCamelCase_:							Any		=  self.tokenizer.decode(W_query["""input_ids"""][idx][c_start_pos:c_end_pos]					)
																			temp.append((decoded, output[k][2] * output[k][3])					)

											final_outputs.append(snake_case_					)

							return final_outputs






