





def _a							(      lowerCamelCase:  Tuple   ,							lowerCamelCase:  Optional[Any]					)      ->		Dict:







      '''simple docstring'''






      __A			  =							(boundary[1] - boundary[0]) / steps
      __A			  =							boundary[0]
      __A			  =							boundary[1]
      __A			  =							make_points(a__   ,							a__   ,							a__					)
      __A			  =							0.0
      y += (h / 3.0) * f(a__					)
      __A			  =							2
      for i in x_i:
            y += (h / 3) * (4 - 2 * (cnt % 2)) * f(a__					)
            cnt += 1
      y += (h / 3.0) * f(a__					)
      return y



def _a							(      lowerCamelCase:  Optional[Any]   ,							lowerCamelCase:  Optional[int]   ,							lowerCamelCase:  int					)      ->		Optional[Any]:







      '''simple docstring'''






      __A			  =							a + h
      while x < (b - h):
            yield x
            __A			  =							x + h



def _a							(      lowerCamelCase:  Union[str, Any]					)      ->		Union[str, Any]:  # enter your function here







      '''simple docstring'''






      __A			  =							(x - 0) * (x - 0)
      return y



def _a							(      )      ->		Dict:







      '''simple docstring'''






      __A			  =							0.0  # Lower bound of integration
      __A			  =							1.0  # Upper bound of integration
      __A			  =							10.0  # define number of steps or resolution
      __A			  =							[a, b]  # define boundary of integration
      __A			  =							method_a(a__   ,							a__					)
      print(F"""y = {y}"""					)


if __name__ == "__main__":
       main()







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__				:      List[Any]    		=     {
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a__				:      List[str]    		=     [
          '''DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''DecisionTransformerGPT2Model''',
          '''DecisionTransformerGPT2PreTrainedModel''',
          '''DecisionTransformerModel''',
          '''DecisionTransformerPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_decision_transformer import (
          DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          DecisionTransformerConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_decision_transformer import (
                DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                DecisionTransformerGPTaModel,
                DecisionTransformerGPTaPreTrainedModel,
                DecisionTransformerModel,
                DecisionTransformerPreTrainedModel,
            )


else:
      import sys

      a__				:      str    		=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
