΅i3SSKrSSKrSSKJr SSKrSSKJr SSKJr SSK J r J r J r J r \ "5(d\"S5\RRS'SS jrS S \SS4S jjrS S \SS4S jjrS S \S\\\44S jjrS S \S\\\44SjjrS S \S\4SjjrS S \S\4SjjrS S \S\4SjjrS S \S\4SjjrS S \S\\\44SjjrS S \S\4SjjrS S\S \SS4Sjjr "SS5r!"SS\!5r"S\!SS4Sjr#S\!4Sjr$/SQr%g)!N)Any) _dummy_type)Device)_get_device_index _is_compiled _lazy_initis_initialized_xpu_XPUAllocatorreturnc`[5(a[RR5 gg)aBRelease all unoccupied cached memory currently held by the caching allocator so that those can be used in other XPU application. .. note:: :func:`~torch.xpu.empty_cache` doesn't increase the amount of XPU memory available for PyTorch. However, it may help reduce fragmentation of XPU memory in certain cases. N)r torch_C_xpu_emptyCacheJ/home/james-whalen/.local/lib/python3.13/site-packages/torch/xpu/memory.py empty_cachers"   "rdevicecT[USS9n[RRU5$)aReset the "peak" stats tracked by the XPU memory allocator. See :func:`~torch.xpu.memory_stats` for details. Peak stats correspond to the `"peak"` key in each individual stat dict. Args: device (torch.device or int or str, optional): selected device. Returns statistic for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Toptional)rrr_xpu_resetPeakMemoryStatsrs rreset_peak_memory_statsrs%v 5F 88 - -f 55rcT[USS9n[RRU5$)aReset the "accumulated" (historical) stats tracked by the XPU memory allocator. See :func:`~torch.xpu.memory_stats` for details. Accumulated stats correspond to the `"allocated"` and `"freed"` keys in each individual stat dict. Args: device (torch.device or int or str, optional): selected device. Returns statistic for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Tr)rrr _xpu_resetAccumulatedMemoryStatsrs rreset_accumulated_memory_statsr-s%v 5F 88 4 4V <= 1MB allocations). - ``small_pool``: statistics for the small allocation pool (for size < 1MB allocations). Metric type: - ``current``: current value of this metric. - ``peak``: maximum value of this metric. - ``allocated``: historical total increase in this metric. - ``freed``: historical total decrease in this metric. Args: device (torch.device or int or str, optional): selected device. Returns statistics for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). prefixobjr Nc>[U[5(a9[U5S:aUS- nUR5Hup#T"X-U5 M gTR X45 g)Nr.) isinstancedictlenitemsappend)r#r$kv_recurse_add_to_resultresults rr.,memory_stats.._recurse_add_to_resultlsR c4 6{Q#  &vz15$ MM6- (rr)strrr!sort collections OrderedDict)rstatsr.r/s @@r memory_statsr7DsZLF)s)))) (v 6E2u% KKM  " "6 **rc4[US9RSS5$)aReturn the current GPU memory occupied by tensors in bytes for a given device. Args: device (torch.device or int or str, optional): selected device. Returns statistic for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). .. note:: This is likely less than the amount shown in `xpu-smi` since some unused memory can be held by the caching allocator and some context needs to be created on GPU. rzallocated_bytes.all.currentrr7getrs rmemory_allocatedr;|s v & * *+H! LLrc4[US9RSS5$)aaReturn the maximum GPU memory occupied by tensors in bytes for a given device. By default, this returns the peak allocated memory since the beginning of this program. :func:`~torch.xpu.reset_peak_memory_stats` can be used to reset the starting point in tracking this metric. For example, these two functions can measure the peak allocated memory usage of each iteration in a training loop. Args: device (torch.device or int or str, optional): selected device. Returns statistic for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). rzallocated_bytes.all.peakrr9rs rmax_memory_allocatedr=s v & * *+Eq IIrc4[US9RSS5$)a6Return the current GPU memory managed by the caching allocator in bytes for a given device. Args: device (torch.device or int or str, optional): selected device. Returns statistic for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). rzreserved_bytes.all.currentrr9rs rmemory_reservedr?s v & * *+G KKrc4[US9RSS5$)aiReturn the maximum GPU memory managed by the caching allocator in bytes for a given device. By default, this returns the peak cached memory since the beginning of this program. :func:`~torch.xpu.reset_peak_memory_stats` can be used to reset the starting point in tracking this metric. For example, these two functions can measure the peak cached memory amount of each iteration in a training loop. Args: device (torch.device or int or str, optional): selected device. Returns statistic for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). rzreserved_bytes.all.peakrr9rs rmax_memory_reservedrAs v & * *+Da HHrch[5 [USS9n[RR U5$)aReturn the global free and total GPU memory for a given device. Args: device (torch.device or int or str, optional): selected device. Returns statistic for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Returns: int: the memory available on the device in units of bytes. int: the total memory on the device in units of bytes Tr)r rrr_xpu_getMemoryInfors r mem_get_inforDs*L v 5F 88 & &v ..rch[5 [USS9n[RR U5$)a: Retrieve the memory fraction currently set for a process on a given XPU device. This fraction represents the portion of the total device memory that the caching allocator is allowed to use. The allowed memory is calculated as: .. math:: \text{allowed\_memory} = \text{total\_memory} \times \text{fraction} Args: device (torch.device or int or str, optional): selected device. It uses the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Returns: float: The memory fraction in the range 0.0 to 1.0. Tr)r rrr_xpu_getMemoryFractionrs rget_per_process_memory_fractionrGs*L v 5F 88 * *6 22rfractionc[5 [USS9n[U[5(d [ S5e[ R RX5 g)a  Set the memory fraction for a single process on XPU device. This function limits the amount of memory that the caching allocator can allocate on the specified XPU device. The allowed memory is computed as: .. math:: \text{allowed\_memory} = \text{total\_memory} \times \text{fraction} If the process attempts to allocate more than this allowed memory, an out-of-memory error will be raised by the allocator. Arguments: fraction (float): Range: 0~1. Allowed memory equals total_memory * fraction. device (torch.device or int or str, optional): selected device. It uses the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). .. note:: In general, the total available free memory is less than the total capacity. Trz3Invalid type for fraction argument, must be `float`N)r rr'float TypeErrorrr_xpu_setMemoryFraction)rHrs rset_per_process_memory_fractionrMs@$L v 5F h & &MNN HH##H5rcT\rSrSrSrS\R R4SjrSr Sr g) _XPUAllocatorz,Wrapper over internal XPU memory allocators. allocatorcXlgN _allocator)selfrQs r__init___XPUAllocator.__init__s#rcUR$rSrT)rVs rrQ_XPUAllocator.allocators rrTN) __name__ __module__ __qualname____firstlineno____doc__rrr rWrQ__static_attributes__rrrrOrOs 7$%(("<"<$rrOc.\rSrSrSrS\S\S\4SjrSrg) XPUPluggableAllocatoriz2XPU memory allocator loaded from a shared library.path_to_lib_file alloc_fn_name free_fn_namec[R"U5n[XB5n[XC5n[R"U[R5R n[R"U[R5R nUbUc [ S5e[RRXx5Ul g)aXPU memory allocator loaded dynamically from a shared library. This lets users provide custom allocation and free functions implemented in a separate shared library. The allocator is registered through ``torch._C._xpu_customAllocator`` and becomes available for use via ``torch.memory.xpu.change_current_allocator``. Arguments: path_to_lib_file (str): Filesystem path to the shared library file containing the allocation and free functions. alloc_fn_name (str): Name of the allocation function exported from the shared library. The function must have the signature: ``void* alloc_fn(size_t size, int device, sycl::queue* queue);`` free_fn_name (str): Name of the free function exported from the shared library. The function must have the signature: ``void free_fn(void* ptr, size_t size, sycl::queue* queue);`` Nz9Failed to load allocator symbols from the shared library.) ctypesCDLLgetattrcastc_void_pvalue RuntimeErrorrr_xpu_customAllocatorrU) rVrcrdre allocator_lib alloc_fn_ptr free_fn_ptr alloc_fn_addr free_fn_addrs rrWXPUPluggableAllocator.__init__s0 $45 }< m:  L&//BHH {{;@FF  L$8K   ((77 TrrTN)r[r\r]r^r_r2rWr`rrrrbrbs$=&U&US&UPS&UrrbrQc^[RRUR55 g)a Change the currently used memory allocator to be the one provided. .. note:: If the current allocator has already been used/initialized, this function will error. Arguments: allocator (torch.xpu.memory._XPUAllocator): allocator to be set as the active one. N)rr_xpu_changeCurrentAllocatorrQ)rQs rchange_current_allocatorrw/s HH(()<)<)>?rcP[[RR55$)zlReturn the allocator being currently used. Returns: _XPUAllocator: the allocator being currently used. )rOrr_xpu_getAllocatorrrr_get_current_allocatorrz<s 335 66r)rbrwrrGr=rArDr;r?r7r!rrrM)r NrS)&r4rgtypingrr torch._utilsr torch.typesrr1rrr r r__dict__rrrr(r2r!r7intr;r=r?rAtuplerDrJrGrMrOrbrwrz__all__rrrrs  $II~~-89L-MEHH)* # 6F 6d 6 =6 =T =--$sCx.-5+5+4S>5+p MV Ms M JJ3J"LFLcLII#I"//5c?/"3F3e3(6e6V6t64)UM)UX @ @$ @7 7 r