def _parameter_control_dependencies(self, is_init):
    if (not self.validate_args):
        return []
    assertions = []
    low = None
    high = None
    if (is_init != tensor_util.is_ref(self.low)):
        low = tf.convert_to_tensor(self.low)
        assertions.append(assert_util.assert_finite(low, message='`low` is not finite'))
    if (is_init != tensor_util.is_ref(self.high)):
        high = tf.convert_to_tensor(self.high)
        assertions.append(assert_util.assert_finite(high, message='`high` is not finite'))
    if (is_init != tensor_util.is_ref(self.loc)):
        assertions.append(assert_util.assert_finite(self.loc, message='`loc` is not finite'))
    if (is_init != tensor_util.is_ref(self.scale)):
        scale = tf.convert_to_tensor(self.scale)
        assertions.extend([assert_util.assert_positive(scale, message='`scale` must be positive'), assert_util.assert_finite(scale, message='`scale` is not finite')])
    if ((is_init != tensor_util.is_ref(self.low)) or (is_init != tensor_util.is_ref(self.high))):
        low = (tf.convert_to_tensor(self.low) if (low is None) else low)
        high = (tf.convert_to_tensor(self.high) if (high is None) else high)
        assertions.append(assert_util.assert_greater(high, low, message='TruncatedCauchy not defined when `low >= high`.'))
    return assertions
def _parameter_control_dependencies(self, is_init):
    if (not self.validate_args):
        return []
    assertions = []
    low = None
    high = None
    if (is_init != tensor_util.is_ref(self.low)):
        low = tf.convert_to_tensor(self.low)
        assertions.append(assert_util.assert_finite(low, message='`low` is not finite'))
    if (is_init != tensor_util.is_ref(self.high)):
        high = tf.convert_to_tensor(self.high)
        assertions.append(assert_util.assert_finite(high, message='`high` is not finite'))
    if (is_init != tensor_util.is_ref(self.loc)):
        assertions.append(assert_util.assert_finite(self.loc, message='`loc` is not finite'))
    if (is_init != tensor_util.is_ref(self.scale)):
        scale = tf.convert_to_tensor(self.scale)
        assertions.extend([assert_util.assert_positive(scale, message='`scale` must be positive'), assert_util.assert_finite(scale, message='`scale` is not finite')])
    if ((is_init != tensor_util.is_ref(self.low)) or (is_init != tensor_util.is_ref(self.high))):
        low = (tf.convert_to_tensor(self.low) if (low is None) else low)
        high = (tf.convert_to_tensor(self.high) if (high is None) else high)
        assertions.append(assert_util.assert_greater(high, low, message='TruncatedCauchy not defined when `low >= high`.'))
    return assertions