code: def get_config(
      self,
      gradient_checkpointing=False,
      scale_attn_by_inverse_layer_idx=False,
      reorder_and_upcast_attn=False,
  ):
      return GPT2Config(
          vocab_size=self.vocab_size,
          n_embd=self.hidden_size,
          n_layer=self.num_hidden_layers,
          n_head=self.num_attention_heads,
          n_inner=self.intermediate_size,
          activation_function=self.hidden_act,
          resid_pdrop=self.hidden_dropout_prob,
          attn_pdrop=self.attention_probs_dropout_prob,
          n_positions=self.max_position_embeddings,
          type_vocab_size=self.type_vocab_size,
          initializer_range=self.initializer_range,
          use_cache=True,
          bos_token_id=self.bos_token_id,
          eos_token_id=self.eos_token_id,
          pad_token_id=self.pad_token_id,
          gradient_checkpointing=gradient_checkpointing,
          scale_attn_by_inverse_layer_idx=scale_attn_by_inverse_layer_idx,
          reorder_and_upcast_attn=reorder_and_upcast_attn,
      )
  
imports: import datetime
  import gc
  import math
  import unittest
  from transformers import GPT2Config, is_torch_available
  from transformers.testing_utils import backend_empty_cache, require_torch, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the GPT2ModelTester obj's underlying member method code with example usage: obj.get_config(gradient_checkpointing, scale_attn_by_inverse_layer_idx, reorder_and_upcast_attn) and returns: GPT2Config