ΧgddlZddlmZmZmZddlZddlmZddlm Z m Z eee e dfZ ddZdde ddfd Zdde ddfd Zdde dee effd Zdde dee effd Zdde de fd Zdde de fdZdde de fdZdde de fdZgdZdS)N)AnyDictUnion)Device)_get_device_indexis_initializedreturncbtr tjdSdS)aZRelease 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_emptyCacheL/var/www/html/ai-engine/env/lib/python3.11/site-packages/torch/xpu/memory.py empty_cacher s6#   """""##rdevicecbt|d}tj|S)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)rr r _xpu_resetPeakMemoryStatsrs rreset_peak_memory_statsrs,v 5 5 5F 8 - -f 5 55rcbt|d}tj|S)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)rr r _xpu_resetAccumulatedMemoryStatsrs rreset_accumulated_memory_statsr)s,v 5 5 5F 8 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 Nct|trCt|dkr|dz }|D]\}}||z|dS||fdS)Nr.) isinstancedictlenitemsappend)r!r"kv_recurse_add_to_resultresults rr,z,memory_stats.._recurse_add_to_resulths c4  )6{{Q#   6 61&&vz15555 6 6 MM63- ( ( ( ( (rr)strrrsort collections OrderedDict)rstatsr,r-s @@r memory_statsr4@sLF)s))))))))) (v 6 6 6E2u%%% KKMMM  "6 * **rcJt|ddS)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.currentrr4getrs rmemory_allocatedr8xs& v & & & * *+H! L LLrcJt|ddS)aReturn 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.peakrr6rs rmax_memory_allocatedr:s& v & & & * *+Eq I IIrcJt|ddS)aJReturn 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.currentrr6rs rmemory_reservedr<s& v & & & * *+G K KKrcJt|ddS)aReturn 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.peakrr6rs rmax_memory_reservedr>s& v & & & * *+Da H HHr) rr:r>r8r<r4rrr)r N)N)r1typingrrrr torch.typesrr.rr r/int _device_trrrrr4r8r:r<r>__all__rrrrDs########## //////// &#sD( )  # # # # 6 6I 6 6 6 6 6 = =9 = = = = =-- -T#s(^----5+5+5+d38n5+5+5+5+p M MY M# M M M M JJJcJJJJ"LLILLLLLII ISIIII"   r