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","."]
code: def dummy_inputs(self):
      input_ids = torch.tensor(DUMMY_INPUTS)
      input_mask = torch.tensor(DUMMY_MASK)
      dummy_inputs = {
          "input_ids": input_ids,
          "attention_mask": input_mask,
      }
      return dummy_inputs
  
imports: import copy
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.nn
  from ...activations import ACT2FN
  from ...modeling_outputs import MoECausalLMOutputWithPast, MoEModelOutputWithPastAndCrossAttentions
  from ...modeling_utils import PreTrainedModel
  from ...utils import DUMMY_INPUTS, DUMMY_MASK, add_start_docstrings, add_start_docstrings_to_model_forward, is_torch_fx_proxy, logging
  from .configuration_gptsan_japanese import GPTSanJapaneseConfig
label_desc: Use image node_id 1 for calling the GPTSanJapanesePreTrainedModel obj's underlying member method code with example usage: obj.dummy_inputs() and returns: dummy_inputs