class_docstr: TFOPT Pretrained Model that inheritates from transformers.TFPreTrainedModel
  
  Args:
      config: OPTConfig
class_docstr_tok: ["TFOPT","Pretrained","Model","that","inheritates","from","transformers.TFPreTrainedModel","Args",":","config",":","OPTConfig"]
code: def dummy_inputs(self):
      pad_token = 1
      input_ids = tf.cast(tf.convert_to_tensor(DUMMY_INPUTS), tf.int32)
      dummy_inputs = {
          "attention_mask": tf.math.not_equal(input_ids, pad_token),
          "input_ids": input_ids,
      }
      return dummy_inputs
  
imports: from typing import Optional, Tuple, Union
  import numpy
  import tensorflow
  from ...activations_tf import get_tf_activation
  from ...modeling_tf_outputs import TFBaseModelOutputWithPast, TFCausalLMOutputWithPast
  from ...modeling_tf_utils import DUMMY_INPUTS, TFCausalLanguageModelingLoss, TFModelInputType, TFPreTrainedModel, TFSharedEmbeddings, 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, replace_return_docstrings
  from .configuration_opt import OPTConfig
label_desc: Use image node_id 1 for calling the TFOPTPreTrainedModel obj's underlying member method code with example usage: obj.dummy_inputs() and returns: dummy_inputs