class_docstr: Here we also overwrite some of the tests of test_modeling_tf_common.py, as EfficientFormer does not use input_ids,
  inputs_embeds, attention_mask and seq_length.
class_docstr_tok: ["Here","we","also","overwrite","some","of","the","tests","of","test_modeling_tf_common.py",",","as","EfficientFormer","does","not","use","input_ids",",","inputs_embeds",",","attention_mask","and","seq_length","."]
code: def test_compile_tf_model(self):
      # We use a simplified version of this test for EfficientFormer because it requires training=False
      # and Keras refuses to let us force that during functional construction
      (
          config,
          _,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      for model_class in self.all_model_classes:
          # Prepare our model
          model = model_class(config)
          # These are maximally general inputs for the model, with multiple None dimensions
          # Hopefully this will catch any conditionals that fail for flexible shapes
          functional_inputs = {
              key: tf.keras.Input(
                  shape=val.shape[1:], dtype=val.dtype, name=key
              )
              for key, val in model.input_signature.items()
              if key in model.dummy_inputs
          }
          outputs_dict = model(functional_inputs)
          self.assertTrue(outputs_dict is not None)
  
imports: import inspect
  import unittest
  from typing import List
  import numpy
  from transformers import EfficientFormerConfig
  from transformers.testing_utils import require_tf, require_vision, slow
  from transformers.utils import cached_property, is_tf_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 13 for calling the TFEfficientFormerModelTest obj's underlying member method code with example usage: obj.test_compile_tf_model() without return types