shDzSrSSKrSSKrSSKrSSKJrJrJr SSK J r SSK J r \Rr \Rr\R r\ S)Sj5rS*S jrS rS r\ S+S j5r\ \R,SS S4Sj5r\ \R,SS SS4Sj5r\ \R,SS 4Sj5r\ \R,SS SSS4Sj5r\R6\ S,Sj55rSrSrSrS-Sjr S.Sjr!Sr"\ S5r#\ S5r$\ S5r%\ S5r&\ S5r'\ \R6S55r(\ \R6S 55r)S*S!jr*\RVr+S"r,S#r-S$r.S%r/S/S&jr0S'r1\R6S(5r2\ "\Rf5r3\ "\Rh5r4\ "\Rj5r5g)0z% API that are reported to numba.cuda N) devicearraydevicesdriver)config)prepare_shape_strides_dtypeTclURS5nSU::aURS5nUb [S5eUSnURS5n[R"US5n[ XVUS S 9upVn[ R "XVUR5n[ R"US S 5n [ R"[5XUS 9n URSS5n U b8[U 5n U(a%[R(aU R5 OS n [R "XVXzU S9n U $)a Create a DeviceNDArray from a cuda-array-interface description. The ``owner`` is the owner of the underlying memory. The resulting DeviceNDArray will acquire a reference from it. If ``sync`` is ``True``, then the imported stream (if present) will be synchronized. versionrmaskNzMasked arrays are not supportedshapestridestypestrC)orderdatar)sizeownerstream)r r dtypegpu_datar)getNotImplementedErrornprrrmemory_size_from_infoitemsizeget_devptr_for_active_ctx MemoryPointercurrent_contextexternal_streamrCUDA_ARRAY_INTERFACE_SYNC synchronizer DeviceNDArray)descrsyncr r r r rrdevptrr stream_ptrrdas b/Users/tiagomarins/Projetos/claudeai/copy_bank/venv/lib/python3.13/site-packages/numba/cuda/api.pyfrom_cuda_array_interfacer)shhy!GG|xx  %&GH H MEhhy!G HHT)_ %E7 S*EE  ' ' GD  - -d6l1o >F   6E ;D(D)J , F44      " ").*0 2B Ic`[U5(d [S5e[URXS9$)aYCreate a DeviceNDArray from any object that implements the :ref:`cuda array interface `. A view of the underlying GPU buffer is created. No copying of the data is done. The resulting DeviceNDArray will acquire a reference from `obj`. If ``sync`` is ``True``, then the imported stream (if present) will be synchronized. z1*obj* doesn't implement the cuda array interface.)rr$) is_cuda_array TypeErrorr)__cuda_array_interface__)objr$s r( as_cuda_arrayr0?s3   KLL()E)E/2? ?r*c[US5$)zyTest if the object has defined the `__cuda_array_interface__` attribute. Does not verify the validity of the interface. r.)hasattr)r/s r(r,r,Ps 32 33r*cg)zoWhether 16-bit floats are supported. float16 is always supported in current versions of Numba - returns True. Tr4r*r(is_float16_supportedr5Xs r*clUc[R"XUSS9up4U$U(aURXS9 U$)ato_device(obj, stream=0, copy=True, to=None) Allocate and transfer a numpy ndarray or structured scalar to the device. To copy host->device a numpy array:: ary = np.arange(10) d_ary = cuda.to_device(ary) To enqueue the transfer to a stream:: stream = cuda.stream() d_ary = cuda.to_device(ary, stream=stream) The resulting ``d_ary`` is a ``DeviceNDArray``. To copy device->host:: hary = d_ary.copy_to_host() To copy device->host to an existing array:: ary = np.empty(shape=d_ary.shape, dtype=d_ary.dtype) d_ary.copy_to_host(ary) To enqueue the transfer to a stream:: hary = d_ary.copy_to_host(stream=stream) T)rcopy user_explicitr)r auto_devicecopy_to_device)r/rr7tonews r( to_devicer>`s@> z))#48<>   #- Ir*rcN[XUU5upn[R"XUUS9$)zdevice_array(shape, dtype=np.float64, strides=None, order='C', stream=0) Allocate an empty device ndarray. Similar to :meth:`numpy.empty`. )r r rr)rrr"r rr rrs r( device_arrayrAs4 88=?EE  $ $5,2 44r*c:[XUU5upn[R"XUR5n[ 5R UUS9n[ R"XXUS9n[ RRU[RS9n U RXtS9 U $)amanaged_array(shape, dtype=np.float64, strides=None, order='C', stream=0, attach_global=True) Allocate a np.ndarray with a buffer that is managed. Similar to np.empty(). Managed memory is supported on Linux / x86 and PowerPC, and is considered experimental on Windows and Linux / AArch64. :param attach_global: A flag indicating whether to attach globally. Global attachment implies that the memory is accessible from any stream on any device. If ``False``, attachment is *host*, and memory is only accessible by devices with Compute Capability 6.0 and later. ) attach_globalr r rrbuffertyper9) rrrrrmemallocmanagedrndarrayviewrManagedNDArray device_setup) r rr rrrCbytesizerEnpary managedviews r( managed_arrayrPs$88=?EE++EENNKH   . .x=J/LF JJU5$ &E**//%k.H.H/IKV3 r*c[XUU5upn[R"XUR5n[ 5R U5n[ R"XXUS9$)zpinned_array(shape, dtype=np.float64, strides=None, order='C') Allocate an :class:`ndarray ` with a buffer that is pinned (pagelocked). Similar to :func:`np.empty() `. rD)rrrrr memhostallocrrI)r rr rrMrEs r( pinned_arrayrSs^88=?EE++E,1NNENN *D 557 !' 77@   }6JI   0'.  == OOsCCc2[5R5$)z Synchronize the current context.)rr!r4r*r(r!r!s   ( ( **r*cURS(d$URS(dURS::ag[UR5Vs/sHoPM nnUR SS9 S/[ UR5-nUR RnUHupVXCU'X@RU-nM [U5$s snf)zO Given an array, compute strides for a new contiguous array of the same shape. C_CONTIGUOUS F_CONTIGUOUSrNc US$)Nrr4)xs r(0_contiguous_strides_like_array..s!A$r*)keyr) flagsndim enumerater sortlenrrr tuple)aryrq stridepermr stridei_perm_s r(_contiguous_strides_like_arrayrs yy CIIn$=Q( 46414J6OOO'cC $$G YY  F  ))F##  >7s CcVURS(aURS(dgg)NrornFr)ru)r{s r(_order_like_arrayrs yy >)Br*cn[U5n[U5n[URURUX1S9$)zX Call :func:`device_array() ` with information from the array. r@)rrrAr r)r{rr rs r(device_array_liker#s6 -S1G c "E ciisyy'# 44r*c p[U5n[U5n[URURUXQX#S9$)z\ Call :func:`mapped_array() ` with the information from the array. )r rr rrrXrY)rrr[r r)r{rrXrYr rs r(mapped_array_liker.s: -S1G c "E ciisyy'#X NNr*cn[U5n[U5n[URURUUS9$)z\ Call :func:`pinned_array() ` with the information from the array. )r rr r)rrrSr r)r{r rs r(pinned_array_liker9s6 -S1G c "E ciisyy'# %%r*c2[5R5$)zF Create a CUDA stream that represents a command queue for the device. )r create_streamr4r*r(rrEs   * * ,,r*c2[5R5$)af Get the default CUDA stream. CUDA semantics in general are that the default stream is either the legacy default stream or the per-thread default stream depending on which CUDA APIs are in use. In Numba, the APIs for the legacy default stream are always the ones in use, but an option to use APIs for the per-thread default stream may be provided in future. )rget_default_streamr4r*r(default_streamrMs   / / 11r*c2[5R5$)z% Get the legacy default CUDA stream. )rget_legacy_default_streamr4r*r(legacy_default_streamrYs   6 6 88r*c2[5R5$)z) Get the per-thread default CUDA stream. )rget_per_thread_default_streamr4r*r(per_thread_default_streamras   : : <+>s+C&,&=&=c&B-2&4  b   sA$A&c/ # U(a SU;dS5eURSS5n/n/nUH|n[5RU[R"U5[R "U5SS9nUR U5 [R"XVUS9nUR U5 M~ [U5S:XaUSv OUv UHnUR5 M g!UHnUR5 M f=f7f) zKA context manager for temporarily mapping a sequence of host ndarrays. rz Only accept 'stream' as keyword.rTrU)rrrN) rrrrrrrrfrom_array_likeryfree)rkwsrr devarylistr{rdevarys r(rVrVs h#oI'II % WWXq !F FJ   % %c6+>+>s+C&,&=&=c&B-1&3  b,,SfM&!   z?a Q-   B GGI&B GGIsB-D0C% D%DDc4[5RUS9nU$)zg Create a CUDA event. Timing data is only recorded by the event if it is created with ``timing=True``. )timing)r create_event)revts r(eventrs   ( ( ( 7C Jr*cF[R"U5nUR$)z Make the context associated with device *device_id* the current context. Returns a Device instance. Raises exception on error. )r get_contextdevice) device_idcontexts r( select_devicers!!),G >>r*c*[5R$)z5Get current device associated with the current thread)rrr4r*r(get_current_devicers   # ##r*c"[R$)z%Return a list of all detected devices)rgpusr4r*r( list_devicesrs <<r*c.[R"5 g)z{ Explicitly clears all contexts in the current thread, and destroys all contexts if the current thread is the main thread. N)rresetr4r*r(rgrgs  MMOr*c,[R"XUS9$)N)rr7)rr:)r{rr7s r( _auto_devicers  " "3D AAr*c[5n[S[U5-5 SnUGHn/nURnURnUR nUR nUSSU-4/- nUSUR4/- nUSUR4/- nUSUR4/- nUSU(aS OS 4/- n[RS :XaUS U(aS OS4/- nUSU4/- nUS:aSnOUS:aSnUS- nOSnUS- n[SURURU4-5 UHup[U <SSU <35 M GM [S5 [SU[U54-5 US:$)z Detect supported CUDA hardware and print a summary of the detected hardware. Returns a boolean indicating whether any supported devices were detected. zFound %d CUDA devicesrzCompute Capabilityz%d.%dz PCI Device IDz PCI Bus IDUUIDWatchdogEnabledDisabledntz Compute ModeTCCWDDMzFP32/FP64 Performance Ratio)z[NOT SUPPORTED: CC < 3.5])rrz[SUPPORTED (DEPRECATED)]rz [SUPPORTED]zid %d %20s %40sz>40z: zSummary:z %d/%d devices are supported) rprintrycompute_capabilityKERNEL_EXEC_TIMEOUT TCC_DRIVER%SINGLE_TO_DOUBLE_PRECISION_PERF_RATIO PCI_DEVICE_ID PCI_BUS_IDuuidosnameid) devlistsupported_countdevattrscckernel_timeouttccfp32_to_fp64_ratiosupportrtvals r(detectrs nG !CL 01O  # #00nn FF '2677 ?C$5$5677 <011 6388$%% :Ny KLL 77d? ~u@A AE 02DEFF ;1G &[0G q O#G q O "cffchh%@@AHC S) *16 * )_c'l,K KL Q r*c#x# [5R5 Sv SSS5 g!,(df  g=f7f)a2 Temporarily disable memory deallocation. Use this to prevent resource deallocation breaking asynchronous execution. For example:: with defer_cleanup(): # all cleanup is deferred in here do_speed_critical_code() # cleanup can occur here Note: this context manager can be nested. N)r defer_cleanupr4r*r(rrs$   ( ( *  + * *s:) : 7:)NT)T)rTN)Nr)r)rFF)rT)6__doc__ contextlibrnumpyrcudadrvrrr numba.corernumba.cuda.api_utilrrequire_contextrrrr)r0r,r5r>float64rArPrSr[contextmanagerrkr!rrrrrrrrrrrrVrevent_elapsed_timerrrrgrrr profiling profile_start profile_stopr4r*r(rsm  11;))%%||%%P?"4$$N jj$c!44!zz4s1 $: jj$c % % jj$c!E2 8+ :4N%--2299==99      6.. $  B&R $ F,, -  4 45 v223 r*