code: def set_bias(self, value):
      # Replaces the existing layers containing bias for correct (de)serialization.
      vocab_size = value["lm_head.bias"].shape[-1]
      self.bias_layer = TFCTRLBiasLayer(
          name="final_logits_bias",
          shape=[1, vocab_size],
          initializer="zeros",
          trainable=True,
      )
      self.bias_layer.build(None)
      self.bias_layer.bias.assign(value["lm_head.bias"])
  
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 5 for calling the TFCTRLLMHeadModel obj's underlying member method code with example usage: obj.set_bias(value) without return types