code: def _expm1_pade_4_4_fwd(
      x,
  ):  # pylint: disable=missing-function-docstring
      x = tf.convert_to_tensor(x, dtype_hint=tf.float32)
      one = tf.ones([], x.dtype)
      dtype = dtype_util.as_numpy_dtype(x.dtype)
  
      for_large_x = exp_pade_4_4(x) - one
  
      # The leading coefficient is zero for the numerator.
      coeffs_p = np.array([1 / 42, 0, 1, 0], dtype)
      coeffs_q = np.array([1 / 1680, -1 / 84, 3 / 28, -1 / 2, 1], dtype)
      for_small_x = _horner(x, coeffs_p) / _horner(x, coeffs_q)
  
      abs_x = tf.math.abs(x)
      exponent_is_small_thresh = 1.0
      x_is_small = abs_x < exponent_is_small_thresh
      res = tf.where(x_is_small, for_small_x, for_large_x)
      return res, res
  
imports: import contextlib
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import dtype_util
label_desc: Use image node_id 14 for calling a global function with example usage: _expm1_pade_4_4_fwd(x) and returns: res,  res