code: def nanmedian(
      input: Union[tf.Tensor, tf.Variable],
      /,
      *,
      axis: Optional[Union[Tuple[int], int]] = None,
      keepdims: bool = False,
      overwrite_input: bool = False,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      if overwrite_input:
          copied_input = tf.identity(input)
          return _nanmedian_helper(copied_input, axis, keepdims)
  
      else:
          result = _nanmedian_helper(input, axis, keepdims)
          return result
  
file_path: ivy/ivy/functional/backends/tensorflow/sub_backends/tf_probability/experimental/statistical.py
imports: from typing import Optional, Sequence, Tuple, Union
  import ivy
  from ivy.func_wrapper import with_supported_dtypes
  from ivy.functional.backends.numpy.experimental.statistical import _handle_axis, _quantile, _validate_quantile
  import tensorflow_probability
  import tensorflow
  from ....None import backend_version
label_desc: Use image node_id 3 for calling a global function with example usage: nanmedian() and returns: _nanmedian_helper, result