code: def test_batch_left_padding(self):
      # Confirms that left-padding is working properly
      (
          model,
          tokenizer,
          sentences,
          expected_output_sentences,
      ) = self._get_beam_search_test_objects()
  
      inputs = tokenizer(sentences, return_tensors="tf", padding=True)
      inputs_non_padded = tokenizer(sentences[0], return_tensors="tf")
      output_non_padded = model.generate(
          **inputs_non_padded, do_sample=False, num_beams=2
      )
      num_paddings = (
          shape_list(inputs_non_padded["input_ids"])[-1]
          - tf.reduce_sum(
              tf.cast(inputs["attention_mask"][-1], tf.int64)
          ).numpy()
      )
      inputs_padded = tokenizer(sentences[1], return_tensors="tf")
      output_padded = model.generate(
          **inputs_padded,
          do_sample=False,
          num_beams=2,
          max_length=model.config.max_length - num_paddings,
      )
      non_padded_sentence = tokenizer.decode(
          output_non_padded[0], skip_special_tokens=True
      )
      padded_sentence = tokenizer.decode(
          output_padded[0], skip_special_tokens=True
      )
      self.assertListEqual(
          expected_output_sentences,
          [non_padded_sentence, padded_sentence],
      )
  
imports: import unittest
  from transformers import AutoTokenizer, GPTJConfig, is_tf_available
  from transformers.testing_utils import require_tf, slow, tooslow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
  from ...utils.test_modeling_tf_core import TFCoreModelTesterMixin
label_desc: Use image node_id 5 for calling the TFGPTJModelLanguageGenerationTest obj's underlying member method code with example usage: obj.test_batch_left_padding() without return types