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3a5bf0bc36
Fixes #144302 After checking the code of my third-party devices, I think these APIs are also relied on by us, so I exposed them according to the discussion in the issue. Pull Request resolved: https://github.com/pytorch/pytorch/pull/144746 Approved by: https://github.com/albanD
71 lines
2.3 KiB
C++
71 lines
2.3 KiB
C++
#pragma once
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#include <c10/core/TensorOptions.h>
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#include <torch/csrc/Export.h>
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// device_lazy_init() is always compiled, even for CPU-only builds.
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namespace torch::utils {
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/**
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* This mechanism of lazy initialization is designed for each device backend.
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* Currently, CUDA and XPU follow this design. This function `device_lazy_init`
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* MUST be called before you attempt to access any Type(CUDA or XPU) object
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* from ATen, in any way. It guarantees that the device runtime status is lazily
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* initialized when the first runtime API is requested.
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*
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* Here are some common ways that a device object may be retrieved:
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* - You call getNonVariableType or getNonVariableTypeOpt
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* - You call toBackend() on a Type
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*
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* It's important to do this correctly, because if you forget to add it you'll
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* get an oblique error message seems like "Cannot initialize CUDA without
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* ATen_cuda library" or "Cannot initialize XPU without ATen_xpu library" if you
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* try to use CUDA or XPU functionality from a CPU-only build, which is not good
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* UX.
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*/
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TORCH_PYTHON_API void device_lazy_init(at::DeviceType device_type);
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TORCH_PYTHON_API void set_requires_device_init(
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at::DeviceType device_type,
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bool value);
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inline bool is_device_lazy_init_supported(at::DeviceType device_type) {
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// Add more devices here to enable lazy initialization.
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return (
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device_type == at::DeviceType::CUDA ||
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device_type == at::DeviceType::XPU ||
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device_type == at::DeviceType::HPU ||
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device_type == at::DeviceType::MTIA ||
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device_type == at::DeviceType::PrivateUse1);
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}
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inline void maybe_initialize_device(at::Device& device) {
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if (is_device_lazy_init_supported(device.type())) {
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device_lazy_init(device.type());
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}
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}
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inline void maybe_initialize_device(std::optional<at::Device>& device) {
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if (!device.has_value()) {
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return;
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}
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maybe_initialize_device(device.value());
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}
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inline void maybe_initialize_device(const at::TensorOptions& options) {
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auto device = options.device();
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maybe_initialize_device(device);
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}
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inline void maybe_initialize_device(
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std::optional<at::DeviceType>& device_type) {
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if (!device_type.has_value()) {
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return;
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}
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maybe_initialize_device(device_type.value());
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}
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bool is_device_initialized(at::DeviceType device_type);
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} // namespace torch::utils
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