from __future__ import annotations

from collections.abc import Callable

def      lowercase_							(     _lowerCamelCase				:			Callable[[int | float], int | float]						,      _lowerCamelCase				:			int | float						,      _lowerCamelCase				:			int | float						,      _lowerCamelCase				:			int = 100						,      ):
    lowercase__					:  List[Any]          =							x_start
    lowercase__					:  Optional[Any]          =							fnc(_lowerCamelCase)
    lowercase__					:  List[str]          =							0.0

    for _ in range(_lowerCamelCase):
        # Approximates small segments of curve as linear and solve
        # for trapezoidal area
        lowercase__					:  List[Any]          =							(x_end - x_start) / steps + xa
        lowercase__					:  List[Any]          =							fnc(_lowerCamelCase)
        area += abs(fxa + fxa) * (xa - xa) / 2

        # Increment step
        lowercase__					:  Optional[int]          =							xa
        lowercase__					:  Dict          =							fxa
    return area


if __name__ == "__main__":

      def      lowercase_							(     _lowerCamelCase				:			List[Any]):
          return x**3

      print('''f(x) = x^3''')
      print('''The area between the curve, x = -10, x = 10 and the x axis is:''')
      UpperCamelCase    				=		10
      while i <= 10_0000:
            UpperCamelCase    				=		trapezoidal_area(f, -5, 5, i)
            print(f"with {i} steps: {area}")
            i *= 10




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase    				=		{'''configuration_dinat''': ['''DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DinatConfig''']}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase    				=		[
          '''DINAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''DinatForImageClassification''',
          '''DinatModel''',
          '''DinatPreTrainedModel''',
          '''DinatBackbone''',
      ]

if TYPE_CHECKING:
      from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_dinat import (
                DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
                DinatBackbone,
                DinatForImageClassification,
                DinatModel,
                DinatPreTrainedModel,
            )

else:
      import sys

      UpperCamelCase    				=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



