Describe the bug
Example pipelines break on machines with no mps.
To reproduce
Steps to reproduce the behavior:
- Run
make run examples/hgnn.py on a machine with no mps.
Expected behavior
It should be able to run on CUDA directly.
Additional context
make run examples/hgnn.py produces:
=== Run examples/hgnn.py ===
uv run python3 examples/hgnn.py
Loading and preparing dataset...
Enriching node features...
Creating dataloaders...
Starting training and evaluation...
Traceback (most recent call last):
File "/workspace/hyperbench/examples/hgnn.py", line 143, in <module>
with MultiModelTrainer(
^^^^^^^^^^^^^^^^^^
File "/workspace/hyperbench/hyperbench/train/trainer.py", line 174, in __init__
model_config.trainer = L.Trainer(
^^^^^^^^^^
File "/workspace/hyperbench/.venv/lib/python3.12/site-packages/lightning/pytorch/utilities/argparse.py", line 70, in insert_env_defaults
return fn(self, **kwargs)
^^^^^^^^^^^^^^^^^^
File "/workspace/hyperbench/.venv/lib/python3.12/site-packages/lightning/pytorch/trainer/trainer.py", line 417, in __init__
self._accelerator_connector = _AcceleratorConnector(
^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/hyperbench/.venv/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/accelerator_connector.py", line 145, in __init__
self._set_parallel_devices_and_init_accelerator()
File "/workspace/hyperbench/.venv/lib/python3.12/site-packages/lightning/pytorch/trainer/connectors/accelerator_connector.py", line 356, in _set_parallel_devices_and_init_accelerator
raise MisconfigurationException(
lightning.fabric.utilities.exceptions.MisconfigurationException: `MPSAccelerator` can not run on your system since the accelerator is not available. The following accelerator(s) is available and can be passed into `accelerator` argument of `Trainer`: ['cpu', 'cuda'].
Describe the bug
Example pipelines break on machines with no
mps.To reproduce
Steps to reproduce the behavior:
make run examples/hgnn.pyon a machine with nomps.Expected behavior
It should be able to run on CUDA directly.
Additional context
make run examples/hgnn.pyproduces: