def METHOD_NAME(self):
    input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
    attention_mask = None
    if self.use_attention_mask:
        attention_mask = random_attention_mask([self.batch_size, self.seq_length])
    token_type_ids = None
    if self.use_token_type_ids:
        token_type_ids = ids_tensor([self.batch_size, self.seq_length], self.type_vocab_size)
    config = AlbertConfig(
        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,
        type_vocab_size=self.type_vocab_size,
        is_decoder=False,
        initializer_range=self.initializer_range,
    )
    return config, input_ids, token_type_ids, attention_mask