code: def __init__(self, config, *inputs, **kwargs):
      super().__init__(config, *inputs, **kwargs)
      self.transformer = TFCTRLMainLayer(config, name="transformer")
      self.bias_layer = TFCTRLBiasLayer(
          name="lm_head",
          shape=[1, config.vocab_size],
          initializer="zeros",
          trainable=True,
      )
  
imports: from __future__ import annotations
  from typing import Optional, Tuple, Union
  import numpy
  import tensorflow
  from ...modeling_tf_outputs import TFBaseModelOutputWithPast, TFCausalLMOutputWithPast, TFSequenceClassifierOutput
  from ...modeling_tf_utils import TFCausalLanguageModelingLoss, TFModelInputType, TFPreTrainedModel, TFSequenceClassificationLoss, get_initializer, keras_serializable, unpack_inputs
  from ...tf_utils import check_embeddings_within_bounds, shape_list, stable_softmax
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_ctrl import CTRLConfig
label_desc: Use image node_id 1 to create a new TFCTRLLMHeadModel object from inherited base classes: TFCTRLPreTrainedModel, TFCausalLanguageModelingLoss with example: obj = TFCTRLLMHeadModel(config)