


def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->Union[str, Any]:







      """simple docstring"""

      lowercase			:   str					   =		(boundary[1] - boundary[0]) / steps
      lowercase			:   List[str]					   =		boundary[0]
      lowercase			:   List[Any]					   =		boundary[1]
      lowercase			:   List[str]					   =		make_points(_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     )
      lowercase			:   List[Any]					   =		0.0
      y += (h / 3.0) * f(_UpperCamelCase     )
      lowercase			:   Optional[int]					   =		2
      for i in x_i:
            y += (h / 3) * (4 - 2 * (cnt % 2)) * f(_UpperCamelCase     )
            cnt += 1
      y += (h / 3.0) * f(_UpperCamelCase     )
      return y




def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     )    ->List[Any]:







      """simple docstring"""

      lowercase			:   List[str]					   =		a + h
      while x < (b - h):
            yield x
            lowercase			:   int					   =		x + h




def 			__lowercase	(						_UpperCamelCase     )    ->Optional[int]:  # enter your function here







      """simple docstring"""

      lowercase			:   Any					   =		(x - 0) * (x - 0)
      return y




def 			__lowercase	(						)    ->Optional[int]:







      """simple docstring"""

      lowercase			:   Dict					   =		0.0  # Lower bound of integration
      lowercase			:   Tuple					   =		1.0  # Upper bound of integration
      lowercase			:   List[Any]					   =		1_0.0  # define number of steps or resolution
      lowercase			:   List[Any]					   =		[a, b]  # define boundary of integration
      lowercase			:   Tuple					   =		method_a(_UpperCamelCase,    _UpperCamelCase     )
      print(f"""y = {y}"""     )


if __name__ == "__main__":
  main()





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a   				=      {
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   				=      [
      '''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   				=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

