code: def prepare_inputs_for_generation(
      self, input_ids, past=None, use_cache=None, **kwargs
  ):
      # only last token for inputs_ids if past is defined in kwargs
      if past:
          input_ids = tf.expand_dims(input_ids[:, -1], -1)
  
      return {
          "input_ids": input_ids,
          "past_key_values": past,
          "use_cache": use_cache,
      }
  
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 4 for calling the TFCTRLLMHeadModel obj's underlying member method code with example usage: obj.prepare_inputs_for_generation(input_ids, past, use_cache) and returns: dict