class_docstr: Compute `Y = g(X; scale) = scale * X`.
  
  Examples:
  
  ```python
  # Y = 2 * X
  b = Scale(scale=2.)
  ```
class_docstr_tok: ["Compute","`","Y","=","g","(","X",";","scale",")","=","scale","*","X","`",".","Examples",":","``","`","python","#","Y","=","2","*","X","b","=","Scale","(","scale=2",".",")","``","`"]
code: def _forward_log_det_jacobian(self, x):
      if self.log_scale is not None:
          return self.log_scale
      elif self.scale is not None:
          return tf.math.log(tf.abs(self.scale))
  
file_path: probability/tensorflow_probability/python/bijectors/scale.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import tensor_util
label_desc: Use image node_id 7 for calling the Scale obj's underlying member method code with example usage: obj._forward_log_det_jacobian(x) and returns: self, tf