code: def prepare_config_and_inputs(self):
      input_ids = ids_tensor(
          [self.batch_size, self.seq_length], self.vocab_size
      )
  
      input_mask = None
      if self.use_input_mask:
          input_mask = np.tril(
              np.ones((self.batch_size, self.seq_length))
          )
  
      config = LlamaConfig(
          vocab_size=self.vocab_size,
          hidden_size=self.hidden_size,
          num_hidden_layers=self.num_hidden_layers,
          num_attention_heads=self.num_attention_heads,
          intermediate_size=self.intermediate_size,
          hidden_act=self.hidden_act,
          hidden_dropout_prob=self.hidden_dropout_prob,
          attention_probs_dropout_prob=self.attention_probs_dropout_prob,
          max_position_embeddings=self.max_position_embeddings,
          use_cache=True,
          is_decoder=False,
          initializer_range=self.initializer_range,
      )
  
      return (config, input_ids, input_mask)
  
imports: import unittest
  import numpy
  from transformers import LlamaConfig, is_flax_available, is_tokenizers_available
  from transformers.testing_utils import require_flax, slow
  from ...generation.test_flax_utils import FlaxGenerationTesterMixin
  from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
label_desc: Use image node_id 2 for calling the FlaxLlamaModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  input_mask