torch.xpu¶

This package introduces support for the XPU backend, specifically tailored for Intel GPU optimization.

This package is lazily initialized, so you can always import it, and use is_available() to determine if your system supports XPU.

`StreamContext`	Context-manager that selects a given stream.
`current_device`	Return the index of a currently selected device.
`current_stream`	Return the currently selected `Stream` for a given device.
`device`	Context-manager that changes the selected device.
`device_count`	Return the number of XPU device available.
`device_of`	Context-manager that changes the current device to that of given object.
`get_device_capability`	Get the xpu capability of a device.
`get_device_name`	Get the name of a device.
`get_device_properties`	Get the properties of a device.
`init`	Initialize PyTorch's XPU state.
`is_available`	Return a bool indicating if XPU is currently available.
`is_initialized`	Return whether PyTorch's XPU state has been initialized.
`set_device`	Set the current device.
`set_stream`	Set the current stream.This is a wrapper API to set the stream.
`stream`	Wrap around the Context-manager StreamContext that selects a given stream.
`synchronize`	Wait for all kernels in all streams on a XPU device to complete.

Random Number Generator¶

`get_rng_state`	Return the random number generator state of the specified GPU as a ByteTensor.
`get_rng_state_all`	Return a list of ByteTensor representing the random number states of all devices.
`initial_seed`	Return the current random seed of the current GPU.
`manual_seed`	Set the seed for generating random numbers for the current GPU.
`manual_seed_all`	Set the seed for generating random numbers on all GPUs.
`seed`	Set the seed for generating random numbers to a random number for the current GPU.
`seed_all`	Set the seed for generating random numbers to a random number on all GPUs.
`set_rng_state`	Set the random number generator state of the specified GPU.
`set_rng_state_all`	Set the random number generator state of all devices.

Wrapper around a XPU event.

Wrapper around a XPU stream.

`empty_cache`	Release all unoccupied cached memory currently held by the caching allocator so that those can be used in other XPU application.
`max_memory_allocated`	Return the maximum GPU memory occupied by tensors in bytes for a given device.
`max_memory_reserved`	Return the maximum GPU memory managed by the caching allocator in bytes for a given device.
`memory_allocated`	Return the current GPU memory occupied by tensors in bytes for a given device.
`memory_reserved`	Return the current GPU memory managed by the caching allocator in bytes for a given device.
`memory_stats`	Return a dictionary of XPU memory allocator statistics for a given device.
`memory_stats_as_nested_dict`	Return the result of `memory_stats()` as a nested dictionary.
`reset_accumulated_memory_stats`	Reset the "accumulated" (historical) stats tracked by the XPU memory allocator.
`reset_peak_memory_stats`	Reset the "peak" stats tracked by the XPU memory allocator.