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 _parameter_control_dependencies(self, is_init):
      if not self.validate_args:
          return []
      assertions = []
      if self.scale is not None and is_init != tensor_util.is_ref(
          self.scale
      ):
          assertions.append(
              assert_util.assert_none_equal(
                  self.scale,
                  tf.zeros([], dtype=self._scale.dtype),
                  message="Argument `scale` must be non-zero.",
              )
          )
      return assertions
  
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 8 for calling the Scale obj's underlying member method code with example usage: obj._parameter_control_dependencies(is_init) and returns: assertions, list