torch.xpu.get_device_properties#
- torch.xpu.get_device_properties(device=None)[source]#
Get the properties of a device. Returns _XpuDeviceProperties containing the following device properties:
name(str): device name.platform_name(str): SYCL platform name.vendor(str): device vendor.device_id(int): device identifier (product ID).driver_version(str): driver version.version(str): runtime version.max_compute_units(int): number of parallel compute units.gpu_eu_count(int): number of EUs (Execution Unit).max_work_group_size: (int): maximum number of work-items permitted in a work-group.max_num_sub_groups(int): maximum number of sub-groups supported in a work-group.sub_group_sizes: (list[int]): a list of supported sub-group sizes.local_mem_size(int): device local memory capacity that can be allocated per work-group in bytes.has_fp16(bool): whether float16 dtype is supported.has_fp64(bool): whether float64 dtype is supported.has_atomic64(bool): whether 64-bit atomic operations are supported.has_bfloat16_conversions(bool): whether bfloat16 conversions are supported.has_subgroup_matrix_multiply_accumulate(bool): whether DPAS (Dot Product Accumulate Systolic) is supported.has_subgroup_matrix_multiply_accumulate_tensor_float32(bool): whether DPAS with tf32 inputs is supported.has_subgroup_2d_block_io(bool): whether 2D block I/O for efficient matrix multiplication is supported.total_memory(int): device global memory in bytes.gpu_subslice_count(int): number of subslice.architecture(int): device architecture identifier (experimental).type(str): device type, e.g. ‘cpu’, ‘gpu’, accelerator’, ‘host’, ‘unknown’.uuid(Any): device UUID (Universal Unique ID), 16 bytes.
- Parameters:
device (torch.device or int or str) – device for which to return the properties of the device.
- Returns:
the properties of the device
- Return type:
_XpuDeviceProperties
