code: def nansum(
      x: paddle.Tensor,
      /,
      *,
      axis: Optional[Union[Tuple[int, ...], int]] = None,
      dtype: Optional[paddle.dtype] = None,
      keepdims: Optional[bool] = False,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      result = paddle.nansum(
          x, axis=axis, dtype=dtype, keepdim=keepdims
      )
      if result.shape == [1]:
          result = paddle.fluid.layers.squeeze(result, [0])
      return result
  
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 10 for calling a global function with example usage: nansum() and returns: result