code: def log_sub_exp(x, y, return_sign=False, name=None):
      """Compute `log(exp(max(x, y)) - exp(min(x, y)))` in a numerically stable way.
  
      Use `return_sign=True` unless `x >= y`, since we can't represent a negative in
      log-space.
  
      Args:
        x: Float `Tensor` broadcastable with `y`.
        y: Float `Tensor` broadcastable with `x`.
        return_sign: Whether or not to return the second output value `sign`. If
          it is known that `x >= y`, this is unnecessary.
        name: Python `str` name prefixed to Ops created by this function.
          Default value: `None` (i.e., `'log_sub_exp'`).
  
      Returns:
        logsubexp: Float `Tensor` of `log(exp(max(x, y)) - exp(min(x, y)))`.
        sign: Float `Tensor` +/-1 indicating the sign of `exp(x) - exp(y)`.
      """
      with tf.name_scope(name or "log_sub_exp"):
          dtype = dtype_util.common_dtype([x, y], dtype_hint=tf.float32)
          x = tf.convert_to_tensor(x, dtype=dtype, name="x")
          y = tf.convert_to_tensor(y, dtype=dtype, name="y")
          larger = tf.maximum(x, y)
          smaller = tf.minimum(x, y)
          zero = dtype_util.as_numpy_dtype(dtype)(0)
          result = larger + log1mexp(tf.maximum(larger - smaller, zero))
          if return_sign:
              ones = tf.ones([], result.dtype)
              return result, tf.where(x < y, -ones, ones)
          return result
  
imports: import collections
  import functools
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import variadic_reduce
  from tensorflow_probability.python.math.scan_associative import scan_associative
  from tensorflow.python.util import deprecation
label_desc: Use image node_id 14 for calling a global function with example usage: log_sub_exp(x, y, return_sign, name) and returns: result, result,  tf