code: def __init__(self):
      k1 = tf.keras.Sequential(
          [
              tf.keras.layers.Dense(
                  32,
                  kernel_regularizer=tf.keras.regularizers.l1_l2(
                      l1=1e-5, l2=1e-4
                  ),
                  bias_regularizer=tf.keras.regularizers.l2(1e-4),
              ),
              tf.keras.layers.Dense(64),
              tf.keras.layers.BatchNormalization(),
          ],
          name="a",
      )
      k2 = tf.keras.layers.Dense(12, name="b")
      super(GnarlyNetwork, self).__init__(
          input_tensor_spec=tf.TensorSpec(dtype=tf.float32, shape=(2,)),
          state_spec=(),
          name=None,
      )
      self._k1 = k1
      self._k2 = k2
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow
  import tensorflow_probability
  from tf_agents import specs
  from tf_agents.distributions import utils
  from tf_agents.keras_layers import rnn_wrapper
  from tf_agents.networks import network
  from tf_agents.utils import common
label_desc: Use image node_id 1 to create a new GnarlyNetwork object from inherited base classes: network with example: obj = GnarlyNetwork()