Getting the same error even after using the slightly older versions.

[ayush714]

I am getting this error, by using below code:-

ValueError: Configurable 'make_layer_stack' doesn't have a parameter named 'use_universal_transformer'.
In file "gs://unifiedqa/models/large/operative_config.gin", line 83
decoder/make_layer_stack.use_universal_transformer = False
MODEL_SIZE = "large"
BASE_PRETRAINED_DIR = "gs://unifiedqa/models/large"
PRETRAINED_DIR = BASE_PRETRAINED_DIR
MODEL_DIR = os.path.join(MODEL_DIR, MODEL_SIZE)

model_parallelism, train_batch_size, keep_checkpoint_max = {
    "small": (1, 256, 16),
    "base": (2, 128, 8),
    "large": (8, 64, 4),
    "3B": (8, 16, 1),
    "11B": (8, 16, 1)}[MODEL_SIZE]
tf.io.gfile.makedirs(MODEL_DIR)
ON_CLOUD = False
model = t5.models.MtfModel(
    model_dir=MODEL_DIR,
    tpu=None,
    model_parallelism=model_parallelism,
    batch_size=train_batch_size,
    sequence_length={"inputs": 128, "targets": 32},
    learning_rate_schedule=0.003,
    save_checkpoints_steps=5000,
    keep_checkpoint_max=keep_checkpoint_max if ON_CLOUD else None,
    iterations_per_loop=100,
)
FINETUNE_STEPS = 9

logInfo("Started Training the model")
start = time()
model.finetune(
    mixture_or_task_name="qa_t5_meshs",
    pretrained_model_dir=PRETRAINED_DIR,
    finetune_steps=FINETUNE_STEPS
)
logInfo("Completed model training.", time_taken=time() - start)

I have seen one answer in issues, but I don't know what you're trying to say.

[ayush714]

I am getting the different error if I try to use 0.12 version

[chen-yifu]

Hi @ayush714 , has this issue been solved? Thanks