code: def test_initialization(self):
      (
          config,
          inputs_dict,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      configs_no_init = _config_zero_init(config)
      for model_class in self.all_model_classes:
          model = model_class(config=configs_no_init)
          for name, param in model.named_parameters():
              uniform_init_parms = ["conv"]
              ignore_init = ["lstm"]
              if param.requires_grad:
                  if any(x in name for x in uniform_init_parms):
                      self.assertTrue(
                          -1.0
                          <= (
                              (param.data.mean() * 1e9).round() / 1e9
                          ).item()
                          <= 1.0,
                          msg=f"Parameter {name} of model {model_class} seems not properly initialized",
                      )
                  elif not any(x in name for x in ignore_init):
                      self.assertIn(
                          (
                              (param.data.mean() * 1e9).round() / 1e9
                          ).item(),
                          [0.0, 1.0],
                          msg=f"Parameter {name} of model {model_class} seems not properly initialized",
                      )
  
imports: import copy
  import inspect
  import os
  import tempfile
  import unittest
  from typing import Dict, List, Tuple
  import numpy
  from datasets import Audio, load_dataset
  from transformers import AutoProcessor, EncodecConfig
  from transformers.testing_utils import is_torch_available, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 17 for calling the EncodecModelTest obj's underlying member method code with example usage: obj.test_initialization() without return types