Files
pytorch/test/test_rename_privateuse1_to_existing_device.py
Jiapeng Li c09eba877f [Device] Add support for PrivateUse1 device type in parse_type function (#157609)
This pull request refactors the `parse_type` function in `c10/core/Device.cpp` to improve the handling of the `PrivateUse1` device type. The main change involves reordering the logic to check for the `PrivateUse1` device type earlier in the function for better clarity and efficiency.

This help to migrate existed backend to PrivateUse1 smoothly.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/157609
Approved by: https://github.com/jgong5, https://github.com/albanD
2025-07-17 01:27:44 +00:00

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1.7 KiB
Python

# Owner(s): ["module: PrivateUse1"]
import torch
from torch.testing._internal.common_utils import run_tests, TestCase
class DummyPrivateUse1Module:
@staticmethod
def is_available():
return True
@staticmethod
def is_autocast_enabled():
return True
@staticmethod
def get_autocast_dtype():
return torch.float16
@staticmethod
def set_autocast_enabled(enable):
pass
@staticmethod
def set_autocast_dtype(dtype):
pass
@staticmethod
def get_amp_supported_dtype():
return [torch.float16]
class TestRenamePrivateuseoneToExistingBackend(TestCase):
def test_external_module_register_with_existing_backend(self):
torch.utils.rename_privateuse1_backend("maia")
with self.assertRaisesRegex(RuntimeError, "has already been set"):
torch.utils.rename_privateuse1_backend("dummmy")
custom_backend_name = torch._C._get_privateuse1_backend_name()
self.assertEqual(custom_backend_name, "maia")
with self.assertRaises(AttributeError):
torch.maia.is_available()
with self.assertRaisesRegex(AssertionError, "Tried to use AMP with the"):
with torch.autocast(device_type=custom_backend_name):
pass
torch._register_device_module("maia", DummyPrivateUse1Module)
torch.maia.is_available() # type: ignore[attr-defined]
with torch.autocast(device_type=custom_backend_name):
pass
self.assertEqual(torch._utils._get_device_index("maia:1"), 1)
self.assertEqual(torch._utils._get_device_index(torch.device("maia:2")), 2)
if __name__ == "__main__":
run_tests()