




'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A				: Optional[Any]					      =			{
    """configuration_imagegpt""": ["""IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ImageGPTConfig""", """ImageGPTOnnxConfig"""]
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A				: List[Any]					      =			["""ImageGPTFeatureExtractor"""]
  A				: int					      =			["""ImageGPTImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A				: str					      =			[
      """IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """ImageGPTForCausalImageModeling""",
      """ImageGPTForImageClassification""",
      """ImageGPTModel""",
      """ImageGPTPreTrainedModel""",
      """load_tf_weights_in_imagegpt""",
  ]


if TYPE_CHECKING:
  from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
    from .image_processing_imagegpt import ImageGPTImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_imagegpt import (
        IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        ImageGPTForCausalImageModeling,
        ImageGPTForImageClassification,
        ImageGPTModel,
        ImageGPTPreTrainedModel,
        load_tf_weights_in_imagegpt,
    )

else:
  import sys

  A				: str					      =			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










'''simple docstring'''
import os
def 							snake_case_    (  ):



    """simple docstring"""




    __lowercase     							=		os.path.dirname(os.path.realpath(a__     )     )
    __lowercase     							=		os.path.join(a__       ,"""triangle.txt"""     )

    with open(a__     ) as f:
        __lowercase     							=		f.readlines()

    __lowercase     							=		[[int(a__     ) for y in x.rstrip("""\r\n"""     ).split(""" """     )] for x in triangle]

    for i in range(1       ,len(a__     )     ):
        for j in range(len(a[i]     )     ):
            __lowercase     							=		a[i - 1][j] if j != len(a[i - 1]     ) else 0
            __lowercase     							=		a[i - 1][j - 1] if j > 0 else 0
            a[i][j] += max(a__       ,a__     )
    return max(a[-1]     )


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




