docstr: ivy.Container static method variant of ivy.float_power. This method
  simply wraps the function, and so the docstring for ivy.float_power
  also applies to this method with minimal changes.
  
  Parameters
  ----------
  x1
      container with the base input arrays.
  x2
      container with the exponent input arrays
  out
      optional output container, for writing the result to.
  
  Returns
  -------
  ret
      Container including arrays with base arrays raised to the powers
      of exponents arrays, element-wise .
  
  Examples
  --------
  >>> x1 = ivy.Container(a=ivy.array([1, 2, 3]),                               b=ivy.array([2, 10]))
  >>> x2 = ivy.Container(a=ivy.array([1, 3, 1]), b=0)
  >>> ivy.Container.static_float_power(x1, x2)
  {
      a: ivy.array([1,  8,  3])
      b: ivy.array([1, 1])
  }
code: def static_float_power(
      x1: Union[
          ivy.Array, ivy.NativeArray, ivy.Container, float, list, tuple
      ],
      x2: Union[
          ivy.Array, ivy.NativeArray, ivy.Container, float, list, tuple
      ],
      /,
      *,
      key_chains: Optional[
          Union[List[str], Dict[str, str], ivy.Container]
      ] = None,
      to_apply: Union[bool, ivy.Container] = True,
      prune_unapplied: Union[bool, ivy.Container] = False,
      map_sequences: Union[bool, ivy.Container] = False,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.float_power. This method
          simply wraps the function, and so the docstring for ivy.float_power
          also applies to this method with minimal changes.
  
          Parameters
          ----------
          x1
              container with the base input arrays.
          x2
              container with the exponent input arrays
          out
              optional output container, for writing the result to.
  
          Returns
          -------
          ret
              Container including arrays with base arrays raised to the powers
              of exponents arrays, element-wise .
  
          Examples
          --------
          >>> x1 = ivy.Container(a=ivy.array([1, 2, 3]),\
                                 b=ivy.array([2, 10]))
          >>> x2 = ivy.Container(a=ivy.array([1, 3, 1]), b=0)
          >>> ivy.Container.static_float_power(x1, x2)
          {
              a: ivy.array([1,  8,  3])
              b: ivy.array([1, 1])
          }
          """
      return ContainerBase.cont_multi_map_in_function(
          "float_power",
          x1,
          x2,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          out=out,
      )
  
imports: from typing import Optional, Union, List, Dict, Tuple, Sequence
  from numbers import Number
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 11 for calling the _ContainerWithElementWiseExperimental obj's underlying member method code with example usage: obj.static_float_power() and returns: ContainerBase