code: def fmax(
      x1: Union[tf.Tensor, tf.Variable],
      x2: Union[tf.Tensor, tf.Variable],
      /,
      *,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      x1, x2 = promote_types_of_inputs(x1, x2)
      x1 = tf.where(tf.math.is_nan(x1), x2, x1)
      x2 = tf.where(tf.math.is_nan(x2), x1, x2)
      return tf.experimental.numpy.maximum(x1, x2)
  
imports: import operator
  from typing import Union, Optional, Tuple, List, Sequence
  from numbers import Number
  import tensorflow
  from tensorflow.python.ops.numpy_ops import np_math_ops
  import ivy
  from ivy import promote_types_of_inputs
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from ..None import backend_version
label_desc: Use image node_id 5 for calling a global function with example usage: fmax() and returns: tf