code: def _get_input_ids_and_config(self):
      (
          config,
          inputs,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      # cut to half length & take max batch_size 3
      max_batch_size = 2
      sequence_length = inputs["input_ids"].shape[-1] // 2
      input_ids = inputs["input_ids"][:max_batch_size, :sequence_length]
  
      attention_mask = jnp.ones_like(input_ids)
      attention_mask = attention_mask[:max_batch_size, :sequence_length]
  
      # generate max 5 tokens
      max_length = input_ids.shape[-1] + 5
      if (
          config.eos_token_id is not None
          and config.pad_token_id is None
      ):
          # hack to allow generate for models such as GPT2 as is done in `generate()`
          config.pad_token_id = config.eos_token_id
      return config, input_ids, attention_mask, max_length
  
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 1 for calling the FlaxGenerationTesterMixin obj's underlying member method code with example usage: obj._get_input_ids_and_config() and returns: config,  input_ids,  attention_mask,  max_length