code: def test_greedy_generate_pt_fx(self):
      (
          config,
          input_ids,
          _,
          max_length,
      ) = self._get_input_ids_and_config()
      config.do_sample = False
      config.max_length = max_length
      config.decoder_start_token_id = 0
  
      for model_class in self.all_generative_model_classes:
          flax_model = model_class(config)
  
          pt_model_class_name = model_class.__name__[
              4:
          ]  # Skip the "Flax" at the beginning
          pt_model_class = getattr(transformers, pt_model_class_name)
          pt_model = pt_model_class(config).eval()
          pt_model = load_flax_weights_in_pytorch_model(
              pt_model, flax_model.params
          )
  
          flax_generation_outputs = flax_model.generate(
              input_ids
          ).sequences
          pt_generation_outputs = pt_model.generate(
              torch.tensor(input_ids, dtype=torch.long)
          )
  
          if (
              flax_generation_outputs.shape[-1]
              > pt_generation_outputs.shape[-1]
          ):
              flax_generation_outputs = flax_generation_outputs[
                  :, : pt_generation_outputs.shape[-1]
              ]
  
          self.assertListEqual(
              pt_generation_outputs.numpy().tolist(),
              flax_generation_outputs.tolist(),
          )
  
imports: import random
  import unittest
  import numpy
  import transformers
  from transformers import is_flax_available, is_torch_available
  from transformers.testing_utils import is_pt_flax_cross_test, require_flax
label_desc: Use image node_id 2 for calling the FlaxGenerationTesterMixin obj's underlying member method code with example usage: obj.test_greedy_generate_pt_fx() without return types