docstr: Generates input examples for tracing etc.
  Returns:
      A tuple of input examples.
docstr_tok: ["Generates","input","examples","for","tracing","etc",".","Returns",":","A","tuple","of","input","examples","."]
code: def input_example(self):
      """
      Generates input examples for tracing etc.
      Returns:
          A tuple of input examples.
      """
      sample = next(self.parameters())
      input_ids = torch.randint(
          low=0, high=2048, size=(2, 16), device=sample.device
      )
      token_type_ids = torch.randint(
          low=0, high=1, size=(2, 16), device=sample.device
      )
      attention_mask = torch.randint(
          low=0, high=1, size=(2, 16), device=sample.device
      )
      return tuple([input_ids, token_type_ids, attention_mask])
  
file_path: NeMo/nemo/collections/nlp/modules/common/gpt_module.py
imports: import os
  import re
  from typing import Dict, Optional
  import torch
  from nemo.core.classes import NeuralModule
  from nemo.core.classes.exportable import Exportable
  from nemo.core.neural_types import ChannelType, FloatType, IntType, MaskType, NeuralType, StringType, VoidType
  from nemo.utils import logging
label_desc: Use image node_id 4 for calling the GPTModule obj's underlying member method code with example usage: obj.input_example() and returns: tuple