Lightning-AI/pytorch-lightning · error · MisconfigurationException

`{accelerator_cls.__qualname__}` can not run on your system

Error message

`{accelerator_cls.__qualname__}` 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`: {available_accelerator}.

What it means

The requested accelerator class reports is_available() == False on this system. The error lists which accelerators ARE available so you can pick one. Raised during accelerator initialization from the registry.

Source

Thrown at src/lightning/pytorch/trainer/connectors/accelerator_connector.py:356

            return "mps"
        if CUDAAccelerator.is_available():
            return "cuda"
        raise MisconfigurationException("No supported gpu backend found!")

    def _set_parallel_devices_and_init_accelerator(self) -> None:
        if isinstance(self._accelerator_flag, Accelerator):
            self.accelerator: Accelerator = self._accelerator_flag
        else:
            self.accelerator = AcceleratorRegistry.get(self._accelerator_flag)
        accelerator_cls = self.accelerator.__class__

        if not accelerator_cls.is_available():
            available_accelerator = [
                acc_str
                for acc_str in self._accelerator_types
                if AcceleratorRegistry[acc_str]["accelerator"].is_available()
            ]
            raise MisconfigurationException(
                f"`{accelerator_cls.__qualname__}` 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"
                f" `Trainer`: {available_accelerator}."
            )

        self._set_devices_flag_if_auto_passed()
        self._devices_flag = accelerator_cls.parse_devices(self._devices_flag)
        if not self._parallel_devices:
            self._parallel_devices = accelerator_cls.get_parallel_devices(self._devices_flag)

    def _set_devices_flag_if_auto_passed(self) -> None:
        if self._devices_flag != "auto":
            return
        if (
            _IS_INTERACTIVE
            and isinstance(self.accelerator, CUDAAccelerator)
            and self.accelerator.auto_device_count() > 1

View on GitHub (pinned to 9fed5c27d2)

Solutions

1. Use one of the accelerators listed in the error message
2. Set accelerator='auto' to let Lightning pick an available one
3. Fix the environment: install CUDA/ROCm/MPS support so the desired accelerator becomes available

Example fix

# before
trainer = Trainer(accelerator="cuda", devices=1)
# after
trainer = Trainer(accelerator="auto", devices="auto")

from lightning.pytorch.accelerators import CPUAccelerator
accelerators = [a for a in (CPUAccelerator,) if a.is_available()]  # extend with CUDA/MPS as needed
accel_cls = MyAccelerator if MyAccelerator.is_available() else CPUAccelerator
trainer = Trainer(accelerator=accel_cls)

def accelerator_available(accel_cls) -> bool:
    return bool(accel_cls.is_available())

from lightning.pytorch.utilities.exceptions import MisconfigurationException
try:
    trainer = Trainer(accelerator="cuda")
except MisconfigurationException as e:
    if "is not available" in str(e):
        trainer = Trainer(accelerator="auto")
    else:
        raise

When it happens

Trigger: Trainer(accelerator=MPSAccelerator()) or accelerator='mps' on non-Apple hardware; CUDAAccelerator on a CPU-only box; also custom registered accelerators whose is_available() returns False.

Common situations: Sharing configs across heterogeneous machines (mac vs linux vs GPU nodes); deprecated/uninstalled accelerator backends (e.g. HPU/TPU without supporting libraries).

Related errors

• You selected an invalid accelerator name: `accelerator={acce
• accelerator set through both strategy class and accelerator
• Device should be CPU, got {device} instead.
• `devices` selected with `CPUAccelerator` should be an int >
• Device should be CUDA, got {device} instead.

AI-assisted analysis of Lightning-AI/pytorch-lightning@9fed5c27d2 (2026-08-28). Data as JSON: /api/errors/43b2c0107b1b33d5. Report an issue: GitHub.