code: def prepare_config_and_inputs(self):
      input_ids = np.clip(
          ids_tensor(
              [self.batch_size, self.seq_length], self.vocab_size
          ),
          3,
          self.vocab_size,
      )
  
      input_mask = None
      if self.use_input_mask:
          input_mask = random_attention_mask(
              [self.batch_size, self.seq_length]
          )
  
      config = XGLMConfig(
          vocab_size=self.vocab_size,
          d_model=self.hidden_size,
          num_layers=self.num_hidden_layers,
          attention_heads=self.num_attention_heads,
          ffn_dim=self.ffn_dim,
          activation_function=self.activation_function,
          activation_dropout=self.activation_dropout,
          attention_dropout=self.attention_dropout,
          max_position_embeddings=self.max_position_embeddings,
          initializer_range=self.initializer_range,
          use_cache=True,
          bos_token_id=self.bos_token_id,
          eos_token_id=self.eos_token_id,
          pad_token_id=self.pad_token_id,
      )
  
      return (config, input_ids, input_mask)
  
imports: import tempfile
  import unittest
  import transformers
  from transformers import XGLMConfig, XGLMTokenizer, is_flax_available, is_torch_available
  from transformers.testing_utils import is_pt_flax_cross_test, require_flax, require_sentencepiece, slow
  from ...generation.test_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 FlaxXGLMModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  input_mask