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# Motivation According to [[1/4] Intel GPU Runtime Upstreaming for Device](https://github.com/pytorch/pytorch/pull/116019), As mentioned in [[RFC] Intel GPU Runtime Upstreaming](https://github.com/pytorch/pytorch/issues/114842), this third PR covers the changes under `libtorch_python`. # Design This PR primarily offers device-related APIs in python frontend, including - `torch.xpu.is_available` - `torch.xpu.device_count` - `torch.xpu.current_device` - `torch.xpu.set_device` - `torch.xpu.device` - `torch.xpu.device_of` - `torch.xpu.get_device_name` - `torch.xpu.get_device_capability` - `torch.xpu.get_device_properties` - ==================== - `torch.xpu._DeviceGuard` - `torch.xpu._is_compiled` - `torch.xpu._get_device` # Additional Context We will implement the support of lazy initialization in the next PR. Pull Request resolved: https://github.com/pytorch/pytorch/pull/116850 Approved by: https://github.com/EikanWang, https://github.com/jgong5, https://github.com/gujinghui, https://github.com/malfet
12 lines
176 B
C++
12 lines
176 B
C++
#pragma once
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#include <torch/csrc/python_headers.h>
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PyMethodDef* THXPModule_methods();
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namespace torch::xpu {
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void initModule(PyObject* module);
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} // namespace torch::xpu
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