class_docstr: An abstract class to handle weights initialization and a simple interface for downloading and loading pretrained
  models.
class_docstr_tok: ["An","abstract","class","to","handle","weights","initialization","and","a","simple","interface","for","downloading","and","loading","pretrained","models","."]
docstr: Dummy inputs to build the network.
  
  Returns:
      `Dict[str, tf.Tensor]`: The dummy inputs.
docstr_tok: ["Dummy","inputs","to","build","the","network",".","Returns",":","`","Dict","[","str",",","tf.Tensor","]","`",":","The","dummy","inputs","."]
code: def dummy_inputs(self):
      """
      Dummy inputs to build the network.
  
      Returns:
          `Dict[str, tf.Tensor]`: The dummy inputs.
      """
      dummy = {"input_ids": tf.constant(DUMMY_INPUTS)}
      # Add `encoder_hidden_states` to make the cross-attention layers' weights initialized
      if self.config.add_cross_attention:
          batch_size, seq_len = tf.constant(DUMMY_INPUTS).shape
          shape = (batch_size, seq_len) + (self.config.hidden_size,)
          h = tf.random.uniform(shape=shape)
          dummy["encoder_hidden_states"] = h
  
      return dummy
  
imports: from dataclasses import dataclass
  from typing import List, Optional, Tuple, Union
  import numpy
  import tensorflow
  from ...activations_tf import get_tf_activation
  from ...modeling_tf_outputs import TFBaseModelOutputWithPastAndCrossAttentions, TFCausalLMOutputWithCrossAttentions, TFSequenceClassifierOutputWithPast
  from ...modeling_tf_utils import TFCausalLanguageModelingLoss, TFConv1D, TFModelInputType, TFPreTrainedModel, TFSequenceClassificationLoss, TFSequenceSummary, TFSharedEmbeddings, get_initializer, keras_serializable, unpack_inputs
  from ...tf_utils import shape_list, stable_softmax
  from ...utils import DUMMY_INPUTS, ModelOutput, add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from .configuration_gpt2 import GPT2Config
label_desc: Use image node_id 1 for calling the TFGPT2PreTrainedModel obj's underlying member method code with example usage: obj.dummy_inputs() and returns: dummy