code: def frexp(
      x: Union[tf.Tensor, tf.Variable],
      /,
      *,
      out: Optional[
          Union[
              Tuple[tf.Tensor, tf.Tensor],
              Tuple[tf.Variable, tf.Variable],
          ]
      ] = None,
  ) -> Union[
      Tuple[tf.Tensor, tf.Tensor], Tuple[tf.Variable, tf.Variable]
  ]:
      e = tf.math.floor(
          tf.math.log(tf.math.abs(x))
          / tf.cast(tf.math.log(2.0), x.dtype)
      )
      e = tf.cast(e, x.dtype)
      while tf.reduce_any(tf.abs(x / tf.math.pow(2, e)) >= 1):
          e += tf.cast(tf.abs(x / tf.math.pow(2, e)) >= 1, e.dtype)
      m = x / tf.math.pow(2, e)
      e = tf.cast(e, tf.int32)
      return m, e
  
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 24 for calling a global function with example usage: frexp() and returns: m,  e