'''simple docstring'''




import os

def _lowercase	(      lowerCamelCase__ = "input.txt"						)					->       int:





       """simple docstring"""


       with open(os.path.join(os.path.dirname(lowerCamelCase__						)							,    lowerCamelCase__						)						) as input_file:
              __UpperCAmelCase  :				str       				=		[
                  [int(lowerCamelCase__						) for element in line.split(","						)]
                  for line in input_file.readlines()
              ]

       __UpperCAmelCase  :				Dict       				=		len(lowerCamelCase__						)
       __UpperCAmelCase  :				Optional[int]       				=		len(matrix[0]						)

       __UpperCAmelCase  :				int       				=		[[-1 for _ in range(lowerCamelCase__						)] for _ in range(lowerCamelCase__						)]
       for i in range(lowerCamelCase__						):
              __UpperCAmelCase  :				List[str]       				=		matrix[i][0]

       for j in range(1							,    lowerCamelCase__						):
              for i in range(lowerCamelCase__						):
                     __UpperCAmelCase  :				Optional[Any]       				=		minimal_path_sums[i][j - 1] + matrix[i][j]

              for i in range(1							,    lowerCamelCase__						):
                     __UpperCAmelCase  :				str       				=		min(
                         minimal_path_sums[i][j]							,    minimal_path_sums[i - 1][j] + matrix[i][j]						)

              for i in range(rows - 2							,    -1							,    -1						):
                     __UpperCAmelCase  :				Dict       				=		min(
                         minimal_path_sums[i][j]							,    minimal_path_sums[i + 1][j] + matrix[i][j]						)

       return min(minimal_path_sums_row[-1] for minimal_path_sums_row in minimal_path_sums						)


if __name__ == "__main__":
  print(f"""{solution() = }""")







'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


_a   :	str 							=   {"configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConfig", "ViTOnnxConfig"]}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	str 							=   ["ViTFeatureExtractor"]
   _a   :	Dict 							=   ["ViTImageProcessor"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	int 							=   [
       "VIT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "ViTForImageClassification",
       "ViTForMaskedImageModeling",
       "ViTModel",
       "ViTPreTrainedModel",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	List[str] 							=   [
       "TFViTForImageClassification",
       "TFViTModel",
       "TFViTPreTrainedModel",
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a   :	Dict 							=   [
       "FlaxViTForImageClassification",
       "FlaxViTModel",
       "FlaxViTPreTrainedModel",
   ]

if TYPE_CHECKING:
   from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_vit import ViTFeatureExtractor
      from .image_processing_vit import ViTImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vit import (
          VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViTForImageClassification,
          ViTForMaskedImageModeling,
          ViTModel,
          ViTPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
   import sys

   _a   :	Dict 							=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






