tensorflow_probability/python/distributions/wishart.py
def _multi_gamma_sequence(self, a, p, name="multi_gamma_sequence"):
    """Creates sequence used in multivariate (di)gamma; shape = shape(a)+[p]."""
    with self._name_scope(name):
      # Linspace only takes scalars, so we'll add in the offset afterwards.
      seq = tf.linspace(
          tf.constant(0., dtype=self.dtype), 0.5 - 0.5 * p, tf.cast(
              p, tf.int32))
      return seq + tf.expand_dims(a, [-1])
def _multi_gamma_sequence(self, a, p, name="multi_gamma_sequence"):
    """Creates sequence used in multivariate (di)gamma; shape = shape(a)+[p]."""
    with self._name_scope(name):
      # Linspace only takes scalars, so we'll add in the offset afterwards.
      seq = tf.linspace(
          tf.constant(0., dtype=self.dtype), 0.5 - 0.5 * p, tf.cast(
              p, tf.int32))
      return seq + tf.expand_dims(a, [-1])
Creates sequence used in multivariate (di)gamma; shape = shape(a)+[p].