

'''simple docstring'''





from __future__ import annotations






def 				_lowerCAmelCase			(   __magic_name__						:     list[list[int]]						)				->  int:

						# preprocessing the first row
						for i in range(1   , len(matrix[0]						)						):
												matrix[0][i] += matrix[0][i - 1]

						# preprocessing the first column
						for i in range(1   , len(__magic_name__						)						):
												matrix[i][0] += matrix[i - 1][0]

						# updating the path cost for current position
						for i in range(1   , len(__magic_name__						)						):
												for j in range(1   , len(matrix[0]						)						):
																		matrix[i][j] += min(matrix[i - 1][j]   , matrix[i][j - 1]						)

						return matrix[-1][-1]


if __name__ == "__main__":
							import doctest

							doctest.testmod()











from typing import TYPE_CHECKING

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


__magic_name__  :  Optional[int]					=       {
    """configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
    """tokenization_biogpt""": ["""BioGptTokenizer"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  int					=       [
          """BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """BioGptForCausalLM""",
          """BioGptForTokenClassification""",
          """BioGptForSequenceClassification""",
          """BioGptModel""",
          """BioGptPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
      from .tokenization_biogpt import BioGptTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_biogpt import (
                BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                BioGptForCausalLM,
                BioGptForSequenceClassification,
                BioGptForTokenClassification,
                BioGptModel,
                BioGptPreTrainedModel,
            )


else:
      import sys

      __magic_name__  :  int					=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

