΅i(K%SrSSKrSSKrSSKJr SSKJr SSKJrJ r SSK r SSK r SSK J r Jr SSKJr SS KJr SS KJrJr S q\R."5r\R2"5r/q\\\/S4\\4\S '\ "\ RBS S5r"\"5q#Sr$\\ RBRJ\S'S\&4Sjr'\'"5(aC\ RBRPr(\ RBRRr*\ RBRVr,O\ "S5r(S\-S\-4Sjr*S\-S\-4Sjr,\"SS9S\-4Sj5r.S\&4Sjr/SBS\&S\&4Sjjr0S\&4Sjr1Sr2SCSjr3SCSjr4SCS jr5"S!S"5r6"S#S5r7"S$S%\75r8S\SS4S&jr9SDS\S\4S'jjr:\"S5SDS\S\;\\44S(jj5r<SDS\S\(4S)jjr=S\-4S*jr>S\-\-\ Rn-S\ Rn4S+jr?S\S,\S\&4S-jr@"S.S/5rAS0\ S1S\A4S2jrBSCS3jrCS0\SS4S4jrDSDS\S\4S5jjrESDS6\-S\S\4S7jjrFSDS\SS4S8jjrGS\\4S9jrHS\4S:jrIS\ RnS\ RBRJ4S;jrJSES<\-S\-\-\ Rn-SS4S=jjrKSES\-\-\ Rn-S\-4S>jjrLSS?KMJNrNJOrOJPrPJQrQJRrRJSrSJTrTJUrUJVrVJWrWJXrXJYrYJZrZJ[r[ SS@K\J]r]J^r^J_r_J`r`JaraJbrbJcrcJdrdJere /SAQrfg)Fz 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 :func:`is_available()` to determine if your system supports XPU. N)Callable) lru_cache)AnyOptional) _dummy_type_LazySeedTracker)Device)_get_device_index)EventStreamF _queued_calls_xpu_isInBadForkcgNFrL/home/james-whalen/.local/lib/python3.13/site-packages/torch/xpu/__init__.pyrsrrdefault_generatorsreturnc6[RR$)z(Return true if compile with XPU support.)torch_C_has_xpurrr _is_compiledr$s 88  r_XpuDevicePropertiesdevicec[S5eNz(PyTorch was compiled without XPU supportNotImplementedErrorrs r_exchange_devicer$1!"LMMrc[S5er r!r#s r_maybe_exchange_devicer'4r%r)maxsizec^[5(dg[RR5$)z*Return the number of XPU device available.r)rrr_xpu_getDeviceCountrrr device_countr+8s! >> 88 ' ' ))rc[5S:$)z7Return a bool indicating if XPU is currently available.r)r+rrr is_availabler-@s >A rincluding_emulationc[5(dgU=(d( [RR5R$)zKReturn a bool indicating if the current XPU device supports dtype bfloat16.F)r-rxpuget_device_propertieshas_bfloat16_conversions)r.s ris_bf16_supportedr3Fs0 >> F 99 * * , E Ercr[5(dg[RR5R$)zGReturn a bool indicating if the current XPU device supports dtype tf32.F)r-rr0r1'has_subgroup_matrix_multiply_accumulaterrris_tf32_supportedr6Ps' >> 99 * * , T TTrc:[=(a [5(+$)z8Return whether PyTorch's XPU state has been initialized.) _initialized_is_in_bad_forkrrris_initializedr:[s  1 111rc [5(aU"5 gURSS5(a*[RU[R "55 gURSS5(a*[R U[R "55 g[RU[R "545 g)Nseed_allFseed) r:get_lazy_seed_trackerqueue_seed_all traceback format_stack queue_seedrappend)callablekwargss r _lazy_callrG`s  ::j% ( (  - -h 8N8N8P Q ZZ & &  ) )(I4J4J4L M  (I,B,B,D!E Frc[5 g)zInitialize PyTorch's XPU state. This is a Python API about lazy initialization that avoids initializing XPU until the first time it is accessed. Does nothing if the XPU state is already initialized. N) _lazy_initrrrinitrJns Lrc [5(d[[S5(ag[ [5(a SSS5 g[ 5(a [ S5e[ 5(d [S5e[RR5 S[l [RS[R555 [H upU"5 M ['[S5 SqSSS5 g![ a1nS[#U5SSR%U53n[!U5UeSnAff=f!['[S5 f=f!,(df  g=f) Nis_initializingzuCannot re-initialize XPU in forked subprocess. To use XPU with multiprocessing, you must use the 'spawn' start methodz#Torch not compiled with XPU enabledTc36# UHo(dM Uv M g7fNr).0callss r _lazy_init..sX0NuRWUU0Ns  z5XPU call failed lazily at initialization with error: z' XPU call was originally invoked at: )r:hasattr_tls_initialization_lockr9 RuntimeErrorrAssertionErrorrr _xpu_initrLrextendr? get_calls Exceptionstrjoindelattrr8) queued_callorig_tracebackemsgs rrIrIws=74):;;          I ~~ !FG G  $X0B0L0L0NXX -/<+ 0M0= D+ , C  2!0OPSTUPVxXBBD''.BYAZ\$C.a/ 0 D+ ,A  sNEB E ED%E)E D?,D::D??EEE E%cB\rSrSrS\SS4SjrSrS\S\S \4S jrS r g) _DeviceGuardindexrNcXlSUlgNidxprev_idx)selfrgs r__init___DeviceGuard.__init__s rc`[RRUR5UlgrNrr0r$rlrmrns r __enter___DeviceGuard.__enter__ 22488< rtypevaluerAc`[RRUR5Ulgrrr0r'rmrlrnrwrxrAs r__exit___DeviceGuard.__exit__9933DMMBrrk) __name__ __module__ __qualname____firstlineno__intrortrr|__static_attributes__rrrreres4cd=SrrecF\rSrSrSrS\SS4SjrSrS\S\S \4S jrS r g) rzContext-manager that changes the selected device. Args: device (torch.device or int or str): device index to select. It's a no-op if this argument is a negative integer or ``None``. rNc0[USS9UlSUlg)NToptionalrj)r rlrm)rnrs rrodevice.__init__s$Vd; rc`[RRUR5UlgrNrrrss rrtdevice.__enter__rvrrwrxrAc`[RRUR5Ulgrrzr{s rr|device.__exit__r~rrk) rrrr__doc__rrortr|rrrrrrs9st=Src0^\rSrSrSrSU4SjjrSrU=r$) device_ofa Context-manager that changes the current device to that of given object. You can use both tensors and storages as arguments. If a given object is not allocated on a XPU, this is a no-op. Args: obj (Tensor or Storage): object allocated on the selected device. cj>UR(aUR5OSn[TU] U5 gri)is_xpu get_devicesuperro)rnobjrl __class__s rrodevice_of.__init__s$"%**cnn" rrrN)rrrrrror __classcell__)rs@rrrsrrcz[5 [U5nUS:a [RR U5 gg)zSet the current device. Args: device (torch.device or int or str): selected device. This function is a no-op if this argument is negative. rN)rIr rr_xpu_setDevicer#s r set_devicers1L v &F { 'rc,[U5R$)amGet the name of a device. Args: device (torch.device or int or str, optional): device for which to return the name. This function is a no-op if this argument is a negative integer. It uses the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Returns: str: the name of the device )r1namer#s rget_device_namers ! ( - --rc "[U5n[[[[[ S5[ [[4n[U5Vs0sH:nURS5(aM[[X5=oB5(dM8X4_M< sn$s snf)aGet the xpu capability of a device. Args: device (torch.device or int or str, optional): device for which to return the device capability. This function is a no-op if this argument is a negative integer. It uses the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Returns: dict[str, Any]: the xpu capability dictionary of the device N__) r1rfloatboolr]rwlisttupledictdir startswith isinstancegetattr)rpropsserializable_typeskeyrxs rget_device_capabilityrs} "& )EudCdT5$Ou: C~~d#  !44 J    sB &B B c@[5 [USS9n[U5$)zGet the properties of a device. Args: device (torch.device or int or str): device for which to return the properties of the device. Returns: _XpuDeviceProperties: the properties of the device Tr)rIr _get_device_propertiesr#s rr1r1s L v 5F !& ))rcR[5 [RR5$)z0Return the index of a currently selected device.)rIrr_xpu_getDevicerrrcurrent_devicersL 88 " " $$rc[U[5(a[R"U5nU$[U[5(a[R"SU5nU$)zReturn the torch.device type object from the passed in device. Args: device (torch.device or int or str): selected device. r0)rr]rrrr#s r _get_devicersJ &#f% M FC eV, Mrpeerc|[5 [USS9n[USS9n[RR X5$)aQuery whether a device can access a peer device's memory. Args: device (torch.device or int or str): selected device. peer (torch.device or int or str): peer device to query access to. Returns: bool: ``True`` if ``device`` can access ``peer``, ``False`` otherwise. Tr)rIr rr_xpu_canDeviceAccessPeer)rrs rcan_device_access_peerr(s6L v 5F TD 1D 88 , ,V ::rc^\rSrSr%Sr\S\S'S\SSS4SjrS rS \ S \ S \ 4S jr Sr g) StreamContexti8aContext-manager that selects a given stream. All XPU kernels queued within its context will be enqueued on a selected stream. Args: Stream (Stream): selected stream. This manager is a no-op if it's ``None``. .. note:: Streams are per-device. torch.xpu.Stream cur_streamstreamrNc\Xl[SS5UlURcSUlgg)NTrj)rr rl)rnrs rroStreamContext.__init__Fs+ $T40 88 DH rcURnUbURS:Xag[RR S5UlUR R UR :waL[ UR 5 [RR UR 5UlSSS5 [RRU5 g!,(df  N.=fri) rrlrr0current_streamsrc_prev_streamrdst_prev_stream set_stream)rnrs rrtStreamContext.__enter__Ls[[  R $yy77=    & &**;*; ; ))*',yy'?'? @Q@Q'R$+ Z(+*s >/C C#rwrxrAc0URnUbURS:XagURRUR:wa)[R R UR5 [R R UR5 gri)rrlrrrr0rr)rnrwrxrArs rr|StreamContext.__exit__Xsj[[  R     & &**;*; ; II !5!5 6 T112r)rrlrr) rrrrrr__annotations__rortrr|rrrrrr8sM +,,x(:; )3S333rrrrc[U5$)zWrap around the Context-manager StreamContext that selects a given stream. Arguments: stream (Stream): selected stream. This manager is a no-op if it's ``None``. )rrs rrrcs   rcB[RRUUUS9 g)zset stream specified by the stream id, device index and device type Args: stream_id (int): not visible to the user, used to assigned to the specific stream. device_index (int): selected device index. device_type (int): selected device type.  stream_id device_index device_typeN)rr_xpu_setStreamrs r_set_stream_by_idrls$ HH!rcrUcg[5 [URURURS9 g)aSet the current stream. This is a wrapper API to set the stream. Usage of this function is discouraged in favor of the ``stream`` context manager. Args: stream (Stream): selected stream. This function is a no-op if this argument is ``None``. Nr)rIrrrrrs rrrzs4~L""((&&rc[5 [RR[ USS95n[ USUSUSS9$)a:Return the currently selected :class:`Stream` for a given device. Args: device (torch.device or int, optional): selected device. Returns the currently selected :class:`Stream` for the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Trrr r)rIrr_xpu_getCurrentStreamr r )r streamdatas rrrsJL//&40J Q-jmTU rdata_ptrc[5 [RRU[ USS95n[ USUSUSS9$)aReturn a :class:`Stream` from an external SYCL queue. This function is used to wrap SYCL queue created in other libraries in order to facilitate data exchange and multi-library interactions. .. note:: This function doesn't manage the queue life-cycle, it is the user responsibility to keep the referenced queue alive while this returned stream is being used. The different SYCL queue pointers will result in distinct :class:`Stream` objects, even if the SYCL queues they dereference are equivalent. Args: data_ptr(int): Integer representation of the `sycl::queue*` value passed externally. device(torch.device or int, optional): the device where the queue was originally created. It is the user responsibility to ensure the device is specified correctly. Trrr rr)rIrr_xpu_getStreamFromExternalr r )rrrs rget_stream_from_externalrsM L44#FT:J Q-jmTU rch[5 [USS9n[RR U5$)aWait for all kernels in all streams on a XPU device to complete. Args: device (torch.device or int, optional): device for which to synchronize. It uses the current device, given by :func:`~torch.xpu.current_device`, if :attr:`device` is ``None`` (default). Tr)rIr rr_xpu_synchronizer#s r synchronizers*L v 5F 88 $ $V ,,rc[5(d/$[RR5nUc/$UR 5$)z> ++-J    rcl[5n[U5S:XagSSRSU553$)zIReturn XPU AOT(ahead-of-time) build flags this library was compiled with.rrSz-device ,c3$# UHov M g7frNr)rOarchs rrQ$get_gencode_flags..s: t s)rlenr^) arch_lists rget_gencode_flagsrs5I 9~ chh: ::; <>[T5nURT5 grN)r set_offset)default_generator final_devicers rcb!_set_rng_state_offset..cbs*<8$$V,rr)rrG)rrrrs` @r_set_rng_state_offsetrs"v&L--rNrcb[5 [U5n[U5nUR5$)a4Return the random number generator state offset of the specified GPU. Args: device (torch.device or int, optional): The device to return the RNG state offset of. Default: ``'xpu'`` (i.e., ``torch.device('xpu')``, the current XPU device). .. warning:: This function eagerly initializes XPU. )rIrr get_offset)rrrs r_get_rng_state_offsetrs-Lv&L&|4  ' ' ))r)change_current_allocator empty_cacheget_per_process_memory_fractionmax_memory_allocatedmax_memory_reserved mem_get_infomemory_allocatedmemory_reserved memory_statsmemory_stats_as_nested_dictreset_accumulated_memory_statsreset_peak_memory_statsset_per_process_memory_fractionXPUPluggableAllocator) get_rng_stateget_rng_state_all initial_seed manual_seedmanual_seed_allr=r< set_rng_stateset_rng_state_all)1r r rr rrrrrrrr+rrrrr1rrr r rrJr r-r3r:r6r rrrrrrrrrrr=r<rrrrrrstreamsr)TrrN)r0)gr threadingrAcollections.abcr functoolsrtypingrrrtorch._C torch._utilsrr torch.typesr _utilsr rr r r8localrULockrVrrrr]rrrr9r?r Generatorrrr_xpu_exchangeDevicer$_xpu_maybeExchangeDevicer'rr+r-r3r6r:rGrJrIrerrrrrrr1rrrrrrrrrrrrrrrmemoryrrrrrrrrrrrrrr randomr r r r rr=r<rr__all__rrrr"s$ 6%"  ~~'t (2t8 d3i '(%(($6 F%'02E%((,,-2d >> 8888xx33"XX>>''=>NNNNsNsN 1*c**d 44U4U2 G%P  (   (v ($ ( .F .c . 4&DcN2* **"%% c ELL0 U\\  ;6 ; ;D ; (3(3V!8./!M! v$&6V$sFf2 - -$ -tCy=3= -5<< -EHH,>,> -5: sU\\1 & *#)ell": *s *"   2 r