code: def prepare_config_and_inputs(self):
      input_ids = np.clip(
          ids_tensor(
              [self.batch_size, self.seq_length - 1], self.vocab_size
          ),
          3,
          self.vocab_size,
      )
      input_ids = np.concatenate(
          (
              input_ids,
              2 * np.ones((self.batch_size, 1), dtype=np.int64),
          ),
          -1,
      )
  
      config = BloomConfig(
          vocab_size=self.vocab_size,
          hidden_size=self.hidden_size,
          n_layer=self.num_hidden_layers,
          n_head=self.num_attention_heads,
          hidden_dropout=self.hidden_dropout,
          attention_dropout=self.attention_probs_dropout_prob,
          eos_token_id=self.eos_token_id,
          bos_token_id=self.bos_token_id,
          pad_token_id=self.pad_token_id,
          is_encoder_decoder=False,
          use_cache=False,
      )
      inputs_dict = prepare_bloom_inputs_dict(config, input_ids)
      return config, inputs_dict
  
imports: import unittest
  import numpy
  from transformers import BloomConfig, BloomTokenizerFast, is_flax_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 FlaxBloomModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  inputs_dict