code: def create_and_check_t5_with_lm_head(
      self, config, input_ids, input_mask, token_labels
  ):
      model = TFT5ForConditionalGeneration(config=config)
      inputs_dict = {
          "input_ids": input_ids,
          "decoder_input_ids": input_ids,
          "decoder_attention_mask": input_mask,
      }
  
      result = model(inputs_dict)
  
      self.parent.assertEqual(
          result.logits.shape,
          (self.batch_size, self.seq_length, self.vocab_size),
      )
  
imports: from __future__ import annotations
  import unittest
  from transformers import T5Config, is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
  from transformers.utils import cached_property
  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 4 for calling the TFT5ModelTester obj's underlying member method code with example usage: obj.create_and_check_t5_with_lm_head(config, input_ids, input_mask, token_labels) without return types