code: def test_load_with_mismatched_shapes(self):
      if not self.test_mismatched_shapes:
          return
      (
          config,
          inputs_dict,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      for model_class in self.all_model_classes:
          if model_class not in get_values(
              FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
          ):
              continue
  
          with self.subTest(msg=f"Testing {model_class}"):
              with tempfile.TemporaryDirectory() as tmp_dir:
                  model = model_class(config)
                  model.save_pretrained(tmp_dir)
  
                  # Fails when we don't set ignore_mismatched_sizes=True
                  with self.assertRaises(ValueError):
                      new_model = FlaxAutoModelForSequenceClassification.from_pretrained(
                          tmp_dir, num_labels=42
                      )
                  with self.assertRaises(ValueError):
                      new_model_without_prefix = (
                          FlaxAutoModel.from_pretrained(
                              tmp_dir, vocab_size=10
                          )
                      )
  
                  logger = logging.get_logger(
                      "transformers.modeling_flax_utils"
                  )
                  with CaptureLogger(logger) as cl:
                      new_model = FlaxAutoModelForSequenceClassification.from_pretrained(
                          tmp_dir,
                          num_labels=42,
                          ignore_mismatched_sizes=True,
                      )
                  self.assertIn("the shapes did not match", cl.out)
  
                  logits = new_model(**inputs_dict)["logits"]
                  self.assertEqual(logits.shape[1], 42)
  
                  with CaptureLogger(logger) as cl:
                      new_model_without_prefix = (
                          FlaxAutoModel.from_pretrained(
                              tmp_dir,
                              vocab_size=10,
                              ignore_mismatched_sizes=True,
                          )
                      )
                  self.assertIn("the shapes did not match", cl.out)
                  input_ids = ids_tensor((2, 8), 10)
                  if self.is_encoder_decoder:
                      new_model_without_prefix(
                          input_ids, decoder_input_ids=input_ids
                      )
                  else:
                      new_model_without_prefix(input_ids)
  
imports: import copy
  import inspect
  import json
  import random
  import tempfile
  from typing import List, Tuple
  import numpy
  import transformers
  from transformers import is_flax_available, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import CaptureLogger, is_pt_flax_cross_test, require_flax, torch_device
  from transformers.utils import CONFIG_NAME, GENERATION_CONFIG_NAME, logging
  from transformers.utils.generic import ModelOutput
label_desc: Use image node_id 18 for calling the FlaxModelTesterMixin obj's underlying member method code with example usage: obj.test_load_with_mismatched_shapes() without return types