(self, inputs, temperature=1.0)
Samples a point from the distribution.

    Args:
      inputs (jnp.ndarray): Distribution inputs. Shape is subclass-specific.
        Broadcasts along the first dimensions. For example, in the categorical
        distribution parameter shape is (C,), where C is the number of
        categories. If (B, C) is passed, the object will represent a batch of B
        categorical distributions with different parameters.
      temperature: sampling temperature; 1.0 is default, at 0.0 chooses
        the most probable (preferred) action.

    Returns:
      Sampled point of shape dependent on the subclass and on the shape of
      inputs.
Samples a point from the distribution.
Samples a point from the distribution .
def sample(self, inputs, temperature=1.0):
    """Samples a point from the distribution.

    Args:
      inputs (jnp.ndarray): Distribution inputs. Shape is subclass-specific.
        Broadcasts along the first dimensions. For example, in the categorical
        distribution parameter shape is (C,), where C is the number of
        categories. If (B, C) is passed, the object will represent a batch of B
        categorical distributions with different parameters.
      temperature: sampling temperature; 1.0 is default, at 0.0 chooses
        the most probable (preferred) action.

    Returns:
      Sampled point of shape dependent on the subclass and on the shape of
      inputs.
    """
    raise NotImplementedError
def sample ( self , inputs , temperature = 1.0 ) : raise NotImplementedError