class_docstr: Compute `Y = log(X)`. This is `Invert(Exp())`.
class_docstr_tok: ["Compute","`","Y","=","log","(","X",")","`",".","This","is","`","Invert","(","Exp","(",")",")","`","."]
code: def __init__(self, validate_args=False, name="log"):
      parameters = dict(locals())
      with tf.name_scope(name) as name:
          bijector = Exp(validate_args=validate_args)
          super(Log, self).__init__(
              bijector=bijector,
              validate_args=validate_args,
              parameters=parameters,
              name=name,
          )
  
file_path: probability/tensorflow_probability/python/bijectors/exp.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import power_transform
label_desc: Use image node_id 1 to create a new Log object from inherited base classes: bijector_lib, invert with example: obj = Log(validate_args, name)