code: def input_signature(self):
      return {
          "input_ids": tf.TensorSpec(
              (None, None, None), tf.int32, name="input_ids"
          ),
          "attention_mask": tf.TensorSpec(
              (None, None, None), tf.int32, name="attention_mask"
          ),
          "mc_token_ids": tf.TensorSpec(
              (None, None), tf.int32, name="token_type_ids"
          ),
      }
  
imports: from __future__ import annotations
  from dataclasses import dataclass
  from typing import Optional, Tuple, Union
  import numpy
  import tensorflow
  from ...activations_tf import get_tf_activation
  from ...modeling_tf_outputs import TFBaseModelOutput, TFCausalLMOutput, TFSequenceClassifierOutput
  from ...modeling_tf_utils import TFCausalLanguageModelingLoss, TFConv1D, TFModelInputType, TFPreTrainedModel, TFSequenceClassificationLoss, TFSequenceSummary, TFSharedEmbeddings, get_initializer, keras_serializable, unpack_inputs
  from ...tf_utils import check_embeddings_within_bounds, shape_list, stable_softmax
  from ...utils import ModelOutput, add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from .configuration_openai import OpenAIGPTConfig
label_desc: Use image node_id 3 for calling the TFOpenAIGPTDoubleHeadsModel obj's underlying member method code with example usage: obj.input_signature() and returns: dict