class_docstr: Ornstein-Uhlenbeck process (specification key: `ornstein_uhlenbeck`).
  
  Args:
      theta (float > 0.0): Theta value
          (<span style="color:#00C000"><b>default</b></span>: 0.15).
      sigma (float > 0.0): Sigma value
          (<span style="color:#00C000"><b>default</b></span>: 0.3).
      mu (float): Mu value
          (<span style="color:#00C000"><b>default</b></span>: 0.0).
      absolute (bool): Absolute value
          (<span style="color:#00C000"><b>default</b></span>: false).
      name (string): <span style="color:#0000C0"><b>internal use</b></span>.
      dtype (type): <span style="color:#0000C0"><b>internal use</b></span>.
      min_value (dtype-compatible value): <span style="color:#0000C0"><b>internal use</b></span>.
      max_value (dtype-compatible value): <span style="color:#0000C0"><b>internal use</b></span>.
code: def __init__(
      self,
      *,
      theta=0.15,
      sigma=0.3,
      mu=0.0,
      absolute=False,
      name=None,
      dtype=None,
      min_value=None,
      max_value=None,
  ):
      self.theta = theta
      self.mu = mu
      self.sigma = sigma
      self.absolute = absolute
  
      super().__init__(
          name=name,
          dtype=dtype,
          min_value=min_value,
          max_value=max_value,
      )
  
file_path: tensorforce/tensorforce/core/parameters/ornstein_uhlenbeck.py
imports: import tensorflow
  from tensorforce.core import TensorSpec, tf_util
  from tensorforce.core.parameters import Parameter
label_desc: Use image node_id 1 to create a new OrnsteinUhlenbeck object from inherited base classes: Parameter with example: obj = OrnsteinUhlenbeck()