code: def __init__(self, config: CNNTransposeHeadConfig) -> None:
      super().__init__(config)
  
      # Initial, inactivated Dense layer (always w/ bias). Use the
      # hidden layer initializer for this layer.
      initial_dense_weights_initializer = get_initializer_fn(
          config.initial_dense_weights_initializer, framework="tf2"
      )
      initial_dense_bias_initializer = get_initializer_fn(
          config.initial_dense_bias_initializer, framework="tf2"
      )
  
      # This layer is responsible for getting the incoming tensor into a proper
      # initial image shape (w x h x filters) for the suceeding Conv2DTranspose stack.
      self.initial_dense = tf.keras.layers.Dense(
          units=int(np.prod(config.initial_image_dims)),
          activation=None,
          kernel_initializer=(
              initial_dense_weights_initializer(
                  **config.initial_dense_weights_initializer_config
              )
              if config.initial_dense_weights_initializer_config
              else initial_dense_weights_initializer
          ),
          use_bias=True,
          bias_initializer=(
              initial_dense_bias_initializer(
                  **config.initial_dense_bias_initializer_config
              )
              if config.initial_dense_bias_initializer_config
              else initial_dense_bias_initializer
          ),
      )
  
      # The main CNNTranspose stack.
      self.cnn_transpose_net = TfCNNTranspose(
          input_dims=config.initial_image_dims,
          cnn_transpose_filter_specifiers=config.cnn_transpose_filter_specifiers,
          cnn_transpose_activation=config.cnn_transpose_activation,
          cnn_transpose_use_layernorm=config.cnn_transpose_use_layernorm,
          cnn_transpose_use_bias=config.cnn_transpose_use_bias,
          cnn_transpose_kernel_initializer=config.cnn_transpose_kernel_initializer,
          cnn_transpose_kernel_initializer_config=(
              config.cnn_transpose_kernel_initializer_config
          ),
          cnn_transpose_bias_initializer=config.cnn_transpose_bias_initializer,
          cnn_transpose_bias_initializer_config=(
              config.cnn_transpose_bias_initializer_config
          ),
      )
  
imports: import functools
  from typing import Optional
  import numpy
  from ray.rllib.core.models.base import Model
  from ray.rllib.core.models.configs import CNNTransposeHeadConfig, FreeLogStdMLPHeadConfig, MLPHeadConfig
  from ray.rllib.core.models.specs.checker import SpecCheckingError
  from ray.rllib.core.models.specs.specs_base import Spec
  from ray.rllib.core.models.specs.specs_base import TensorSpec
  from ray.rllib.core.models.tf.base import TfModel
  from ray.rllib.core.models.tf.primitives import TfCNNTranspose, TfMLP
  from ray.rllib.models.utils import get_initializer_fn
  from ray.rllib.utils import try_import_tf
  from ray.rllib.utils.annotations import override
label_desc: Use image node_id 1 to create a new TfCNNTransposeHead object from inherited base classes: TfModel with example: obj = TfCNNTransposeHead(config)