code: def test_checkpoint_sharding_from_hub(self):
      model = FlaxBertModel.from_pretrained(
          "ArthurZ/flax-tiny-random-bert-sharded"
      )
      # the model above is the same as the model below, just a sharded version.
      ref_model = FlaxBertModel.from_pretrained(
          "hf-internal-testing/tiny-bert-flax-only"
      )
      for p1, p2 in zip(
          flatten_dict(model.params).values(),
          flatten_dict(ref_model.params).values(),
      ):
          assert np.allclose(np.array(p1), np.array(p2))
  
imports: import copy
  import inspect
  import json
  import random
  import tempfile
  import unittest
  from typing import List, Tuple
  import numpy
  import transformers
  from huggingface_hub import HfFolder, delete_repo, set_access_token
  from requests.exceptions import HTTPError
  from transformers import BertConfig, is_flax_available, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import TOKEN, USER, CaptureLogger, is_pt_flax_cross_test, is_staging_test, require_flax, torch_device
  from transformers.utils import logging
  from transformers.utils.generic import ModelOutput
label_desc: Use image node_id 29 for calling the FlaxModelTesterMixin obj's underlying member method code with example usage: obj.test_checkpoint_sharding_from_hub() without return types