code: def test_output_embeds_base_model(self):
      model = TFFlaubertModel.from_pretrained(
          "jplu/tf-flaubert-small-cased"
      )
  
      input_ids = tf.convert_to_tensor(
          [[0, 158, 735, 2592, 1424, 6727, 82, 1]],
          dtype=tf.int32,
      )  # "J'aime flaubert !"
  
      output = model(input_ids)[0]
      expected_shape = tf.TensorShape((1, 8, 512))
      self.assertEqual(output.shape, expected_shape)
      # compare the actual values for a slice.
      expected_slice = tf.convert_to_tensor(
          [
              [
                  [-1.8768773, -1.566555, 0.27072418],
                  [-1.6920038, -0.5873505, 1.9329599],
                  [-2.9563985, -1.6993835, 1.7972052],
              ]
          ],
          dtype=tf.float32,
      )
  
      self.assertTrue(
          np.allclose(
              output[:, :3, :3].numpy(),
              expected_slice.numpy(),
              atol=1e-4,
          )
      )
  
imports: from __future__ import annotations
  import unittest
  from transformers import is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 for calling the TFFlaubertModelIntegrationTest obj's underlying member method code with example usage: obj.test_output_embeds_base_model() without return types