How to ensure run_t5_mlm_flax.py uses GPU?

Beginners
1

I tried to reproduce the fine-tuning of the T5 masked language model (MLM) in Transformer.
It is based on the article here.

The fine-tuning part is done with the run_t5_mlm_flax.py script.

python run_t5_mlm_flax.py \
	--output_dir="./norwegian-t5-base" \
	--model_type="t5" \
	--config_name="./norwegian-t5-base" \
	--tokenizer_name="./norwegian-t5-base" \
	--dataset_name="oscar" \
	--dataset_config_name="unshuffled_deduplicated_no" \
	--max_seq_length="512" \
	--per_device_train_batch_size="32" \
	--per_device_eval_batch_size="32" \
	--adafactor \
	--learning_rate="0.005" \
	--weight_decay="0.001" \
	--warmup_steps="2000" \
	--overwrite_output_dir \
	--logging_steps="500" \
	--save_steps="10000" \
	--eval_steps="2500" \
	--push_to_hub

However, when I run this code the GPU doesn’t seem recognized.
For example watch -n0.1 nvidia-smi command doesn’t show the GPU being used.
I confirmed that the GPU is recognized by FLAX/JAX?

In [1]: import jax
 ...:
 ...: print("Number of available GPUs:", jax.device_count())
 ...: print("Default GPU:", jax.default_backend())
Number of available GPUs: 1
Default GPU: gpu

How can I make sure the run_mlm_flax.py use the GPU machine?