





def        __lowercase       (				_SCREAMING_SNAKE_CASE     )			->       float:


      '''simple docstring'''


      return 10 - x * x



def        __lowercase       (				_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )			->       float:


      '''simple docstring'''


      if equation(_SCREAMING_SNAKE_CASE     ) * equation(_SCREAMING_SNAKE_CASE     ) >= 0:
            raise ValueError("""Wrong space!"""     )

      SCREAMING_SNAKE_CASE		=						a
      while (b - a) >= 0.01:
            # Find middle point
            SCREAMING_SNAKE_CASE		=						(a + b) / 2
            # Check if middle point is root
            if equation(_SCREAMING_SNAKE_CASE     ) == 0.0:
                  break
            # Decide the side to repeat the steps
            if equation(_SCREAMING_SNAKE_CASE     ) * equation(_SCREAMING_SNAKE_CASE     ) < 0:
                  SCREAMING_SNAKE_CASE		=						c
            else:
                  SCREAMING_SNAKE_CASE		=						c
      return c


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      print(bisection(-2, 5))
      print(bisection(0, 6))









from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_						       =	{
    """configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
    """tokenization_mvp""": ["""MvpTokenizer"""],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	["""MvpTokenizerFast"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	[
          """MVP_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """MvpForCausalLM""",
          """MvpForConditionalGeneration""",
          """MvpForQuestionAnswering""",
          """MvpForSequenceClassification""",
          """MvpModel""",
          """MvpPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
      from .tokenization_mvp import MvpTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_mvp_fast import MvpTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mvp import (
                MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
                MvpForCausalLM,
                MvpForConditionalGeneration,
                MvpForQuestionAnswering,
                MvpForSequenceClassification,
                MvpModel,
                MvpPreTrainedModel,
            )

else:
      import sys

      SCREAMING_SNAKE_CASE_						       =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


