
'''simple docstring'''

from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
     from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore


class   a_  (_a    ):
       __lowerCAmelCase    :				Union[str, Any]    =      c_float




       @property
       def 							__UpperCamelCase       (     self  ):
         return sizeof(self.value  )



def 	_UpperCAmelCase				(  _lowerCamelCase						:       int  ,      _lowerCamelCase						:       int  ,      _lowerCamelCase						:       int = 0		)    ->						int:
  # < 0 is possible if using a dynamic axis
  if dimension <= 0:
    _lowerCAmelCase       :  Optional[int]   				=					fixed_dimension

  dimension -= num_token_to_add
  return dimension


def 	_UpperCAmelCase				(  _lowerCamelCase						:       int  ,      _lowerCamelCase						:       ParameterFormat		)    ->						int:
  return num_parameters * dtype.size



def 	_UpperCAmelCase				(  _lowerCamelCase						:       str		)    ->						Optional[Union["AutoTokenizer", "AutoFeatureExtractor", "AutoProcessor"]]:
  from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

  try:
    return AutoProcessor.from_pretrained(_lowerCamelCase		)
  except (ValueError, OSError, KeyError):
    _lowerCAmelCase				,					_lowerCAmelCase       :  Optional[int]   				=					None, None
    try:
      _lowerCAmelCase       :  str   				=					AutoTokenizer.from_pretrained(_lowerCamelCase		)
    except (OSError, KeyError):
      pass
    try:
      _lowerCAmelCase       :  List[str]   				=					AutoFeatureExtractor.from_pretrained(_lowerCamelCase		)
    except (OSError, KeyError):
      pass

    if tokenizer is not None and feature_extractor is not None:
      raise ValueError(
          f'Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor.'		)
    elif tokenizer is None and feature_extractor is None:
      return None
    elif tokenizer is not None:
      return tokenizer
    else:
      return feature_extractor




'''simple docstring'''

import os


def 	_UpperCAmelCase				(  )    ->						int:
  _lowerCAmelCase       :  Optional[int]   				=					os.path.dirname(os.path.realpath(_lowerCamelCase		)		)
  _lowerCAmelCase       :  Optional[Any]   				=					os.path.join(_lowerCamelCase  ,      """triangle.txt"""		)

  with open(_lowerCamelCase		) as in_file:
    _lowerCAmelCase       :  List[Any]   				=					[[int(_lowerCamelCase		) for i in line.split()] for line in in_file]

  while len(_lowerCamelCase		) != 1:
    _lowerCAmelCase       :  Any   				=					triangle.pop()
    _lowerCAmelCase       :  List[str]   				=					triangle[-1]
    for j in range(len(_lowerCamelCase		) - 1		):
      curr_row[j] += max(last_row[j]  ,      last_row[j + 1]		)
  return triangle[0][0]


if __name__ == "__main__":
     print(solution())


