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[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
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@ -41,6 +41,9 @@ DeviceType parse_type(const std::string& device_string) {
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"'mkldnn' is no longer used as device type. So torch.device('mkldnn') will be "
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"'mkldnn' is no longer used as device type. So torch.device('mkldnn') will be "
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"deprecated and removed in the future. Please use other valid device types instead.");
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"deprecated and removed in the future. Please use other valid device types instead.");
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}
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}
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if (device_string == get_privateuse1_backend()) {
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return DeviceType::PrivateUse1;
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}
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auto device = std::find_if(
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auto device = std::find_if(
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types.begin(),
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types.begin(),
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types.end(),
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types.end(),
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@ -50,9 +53,6 @@ DeviceType parse_type(const std::string& device_string) {
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if (device != types.end()) {
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if (device != types.end()) {
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return device->second;
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return device->second;
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}
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}
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if (device_string == get_privateuse1_backend()) {
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return DeviceType::PrivateUse1;
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}
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std::vector<const char*> device_names;
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std::vector<const char*> device_names;
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for (const auto& it : types) {
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for (const auto& it : types) {
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if (it.first) {
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if (it.first) {
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59
test/test_rename_privateuse1_to_existing_device.py
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59
test/test_rename_privateuse1_to_existing_device.py
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@ -0,0 +1,59 @@
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# Owner(s): ["module: PrivateUse1"]
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import torch
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from torch.testing._internal.common_utils import run_tests, TestCase
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class DummyPrivateUse1Module:
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@staticmethod
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def is_available():
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return True
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@staticmethod
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def is_autocast_enabled():
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return True
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@staticmethod
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def get_autocast_dtype():
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return torch.float16
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@staticmethod
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def set_autocast_enabled(enable):
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pass
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@staticmethod
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def set_autocast_dtype(dtype):
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pass
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@staticmethod
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def get_amp_supported_dtype():
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return [torch.float16]
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class TestRenamePrivateuseoneToExistingBackend(TestCase):
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def test_external_module_register_with_existing_backend(self):
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torch.utils.rename_privateuse1_backend("maia")
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with self.assertRaisesRegex(RuntimeError, "has already been set"):
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torch.utils.rename_privateuse1_backend("dummmy")
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custom_backend_name = torch._C._get_privateuse1_backend_name()
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self.assertEqual(custom_backend_name, "maia")
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with self.assertRaises(AttributeError):
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torch.maia.is_available()
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with self.assertRaisesRegex(AssertionError, "Tried to use AMP with the"):
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with torch.autocast(device_type=custom_backend_name):
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pass
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torch._register_device_module("maia", DummyPrivateUse1Module)
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torch.maia.is_available() # type: ignore[attr-defined]
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with torch.autocast(device_type=custom_backend_name):
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pass
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self.assertEqual(torch._utils._get_device_index("maia:1"), 1)
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self.assertEqual(torch._utils._get_device_index(torch.device("maia:2")), 2)
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if __name__ == "__main__":
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run_tests()
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