tensorflow_probability/python/distributions/dirichlet_multinomial.py
def _maybe_assert_valid_concentration(self, concentration, validate_args):
    """Checks the validity of the concentration parameter."""
    if not validate_args:
      return concentration
    concentration = distribution_util.embed_check_categorical_event_shape(
        concentration)
    return distribution_util.with_dependencies([
        assert_util.assert_positive(
            concentration, message="Concentration parameter must be positive."),
    ], concentration)
def _maybe_assert_valid_concentration(self, concentration, validate_args):
    """Checks the validity of the concentration parameter."""
    if not validate_args:
      return concentration
    concentration = distribution_util.embed_check_categorical_event_shape(
        concentration)
    return distribution_util.with_dependencies([
        assert_util.assert_positive(
            concentration, message="Concentration parameter must be positive."),
    ], concentration)
def _maybe_assert_valid_concentration ( self , concentration , validate_args ) : if not validate_args : return concentration concentration = distribution_util . embed_check_categorical_event_shape ( concentration ) return distribution_util . with_dependencies ( [ assert_util . assert_positive ( concentration , message = "Concentration parameter must be positive." ) , ] , concentration )
Checks the validity of the concentration parameter.
Checks the validity of the concentration parameter .