code: def create_and_check_gpt2_weight_initialization(self, config, *args):
      model = GPT2Model(config)
      model_std = model.config.initializer_range / math.sqrt(
          2 * model.config.n_layer
      )
      for key in model.state_dict().keys():
          if "c_proj" in key and "weight" in key:
              self.parent.assertLessEqual(
                  abs(torch.std(model.state_dict()[key]) - model_std),
                  0.001,
              )
              self.parent.assertLessEqual(
                  abs(torch.mean(model.state_dict()[key]) - 0.0), 0.01
              )
  
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 17 for calling the GPT2ModelTester obj's underlying member method code with example usage: obj.create_and_check_gpt2_weight_initialization(config) without return types