code: def _parameter_properties(cls, dtype, num_classes=None):
      return dict(
          loc=parameter_properties.ParameterProperties(
              event_ndims=lambda _: None,
              event_ndims_tensor=(
                  lambda _: tf1.placeholder_with_default(1, shape=None)
              ),
          ),
          scale_tril=parameter_properties.ParameterProperties(
              event_ndims=lambda _: None,
              event_ndims_tensor=(
                  lambda _: tf1.placeholder_with_default(2, shape=None)
              ),
          ),
      )
  
imports: from absl import logging
  from absl.testing import parameterized
  import mock
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mixture_same_family
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import batch_shape_lib
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import test_util
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling the _MVNTriLWithDynamicParamNdims obj's underlying member method code with example usage: obj._parameter_properties(cls, dtype, num_classes) and returns: dict