code: def prepare_config_and_inputs(self):
      input_ids = tf.clip_by_value(
          ids_tensor(
              [self.batch_size, self.seq_length], self.vocab_size
          ),
          clip_value_min=0,
          clip_value_max=3,
      )
  
      input_mask = None
      if self.use_input_mask:
          input_mask = random_attention_mask(
              [self.batch_size, self.seq_length]
          )
  
      config = self.get_config()
  
      head_mask = floats_tensor(
          [self.num_hidden_layers, self.num_attention_heads], 2
      )
  
      return (
          config,
          input_ids,
          input_mask,
          head_mask,
      )
  
imports: from __future__ import annotations
  import unittest
  from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
  from transformers.testing_utils import require_tf, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 3 for calling the TFXGLMModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  input_mask,  head_mask