code: def float_power(
      x1: Union[paddle.Tensor, float, list, tuple],
      x2: Union[paddle.Tensor, float, list, tuple],
      /,
      *,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      x1 = paddle.cast(x1, dtype="float64")
      x2 = paddle.cast(
          x2, dtype="float64"
      )  # Compute the element-wise power
      return paddle.cast(paddle.pow(x1, x2), dtype=paddle.float64)
  
imports: import operator
  from typing import Optional, Union, Tuple, List, Sequence
  from numbers import Number
  import paddle
  from ivy.utils.exceptions import IvyNotImplementedException
  from ivy.func_wrapper import with_supported_dtypes, with_unsupported_device_and_dtypes, with_unsupported_dtypes
  import ivy.functional.backends.paddle
  import ivy
  from ivy import promote_types_of_inputs
  from ivy.functional.backends.paddle.elementwise import _elementwise_helper
  from ..None import backend_version
label_desc: Use image node_id 6 for calling a global function with example usage: float_power() and returns: paddle