code: def prepare_config_and_inputs(self):
      input_ids = jnp.clip(
          ids_tensor(
              [self.batch_size, self.seq_length], self.vocab_size
          ),
          3,
          self.vocab_size,
      )
  
      attention_mask = None
      if self.use_attention_mask:
          attention_mask = random_attention_mask(
              [self.batch_size, self.seq_length]
          )
  
      config = BartConfig(
          vocab_size=self.vocab_size,
          d_model=self.hidden_size,
          encoder_layers=self.num_hidden_layers,
          decoder_layers=self.num_hidden_layers,
          encoder_attention_heads=self.num_attention_heads,
          decoder_attention_heads=self.num_attention_heads,
          encoder_ffn_dim=self.intermediate_size,
          decoder_ffn_dim=self.intermediate_size,
          dropout=self.hidden_dropout_prob,
          attention_dropout=self.attention_probs_dropout_prob,
          max_position_embeddings=self.max_position_embeddings,
          eos_token_id=self.eos_token_id,
          bos_token_id=self.bos_token_id,
          pad_token_id=self.pad_token_id,
          initializer_range=self.initializer_range,
          use_cache=False,
      )
  
      return config, input_ids, attention_mask
  
imports: import unittest
  import numpy
  import timeout_decorator
  from transformers import BartConfig, BartTokenizer, is_flax_available
  from transformers.testing_utils import require_flax, slow
  from ...generation.test_generation_flax_utils import FlaxGenerationTesterMixin
  from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 2 for calling the FlaxBartStandaloneDecoderModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  attention_mask