code: def __init__(self, config, input_embeddings, **kwargs):
      super().__init__(**kwargs)
      self.vocab_size = config.vocab_size
      # CTRL has numerical issues in XLA generate
      self.supports_xla_generation = False
  
      # The output weights are the same as the input embeddings, but there is
      # an output-only bias for each token.
      self.input_embeddings = input_embeddings
  
imports: import warnings
  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, TFSharedEmbeddings, get_initializer, keras_serializable, unpack_inputs
  from ...tf_utils import 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 TFCTRLLMHead object from inherited base classes: tf.keras.layers with example: obj = TFCTRLLMHead(config, input_embeddings)