tensorflow_probability/python/distributions/dirichlet_multinomial.py
def _variance_scale_term(self):
    """Helper to `_covariance` and `_variance` which computes a shared scale."""
    # Expand back the last dim so the shape of _variance_scale_term matches the
    # shape of self.concentration.
    c0 = self.total_concentration[..., tf.newaxis]
    return tf.sqrt((1. + c0 / self.total_count[..., tf.newaxis]) / (1. + c0))
def _variance_scale_term(self):
    # Expand back the last dim so the shape of _variance_scale_term matches the
    # shape of self.concentration.
    c0 = self.total_concentration[..., tf.newaxis]
    return tf.sqrt((1. + c0 / self.total_count[..., tf.newaxis]) / (1. + c0))
def _variance_scale_term ( self ) : # Expand back the last dim so the shape of _variance_scale_term matches the # shape of self.concentration. c0 = self . total_concentration [ ... , tf . newaxis ] return tf . sqrt ( ( 1. + c0 / self . total_count [ ... , tf . newaxis ] ) / ( 1. + c0 ) )
Helper to `_covariance` and `_variance` which computes a shared scale.
Helper to _covariance and _variance which computes a shared scale .