\;j'VddlZddlZddlZgZdZdZdZdZdZ dZ dZ d Z d Z y) Nc tjjdgdd}tjddgdtjtj j jd }tjdgd }tj jj||| }tjj|}|||fS) zD Define a simple network composed by a single linear layer. input)Nrfloat32)nameshapedtyperg?) initializer)rr attr)rr )xweightbias) paddlestaticdatacreate_parameter ParamAttrnnr Constant functionallineartensorsum)rrr linear_outouts cG:\00. PROJECTS\API\Inventory\templateJSON\kerjaOCR\Lib\site-packages\paddle/utils/install_check.py_simple_networkrs MM   L   E $ $!f   &))*?*?*H*H*M NF  " "!I >D%%,,uV$,OJ --  J 'C #v c~tjddgddggtj}|jdddS)zK Prepare feeding data for simple network. The shape is [1, 2, 2]. ?g@g@g@)r r)nparrayrreshape)np_input_singles r _prepare_datar'*s: hhc S#J7rzzJO  " "1a ++rc ttjjdkDsJy#t$r"}t j d|Yd}~yd}~wwxYw)z* Check whether CUDA is available. rTzYou are using GPU version PaddlePaddle, but there is no GPU detected on your machine. Maybe CUDA devices is not set properly. Original Error is NF)lenrr cuda_places Exceptionloggingwarninges r_is_cuda_availabler04sZ 6==,,./!333  $$%3 (  ,/ AAAc ttjjdkDsJy#t$r"}t j d|Yd}~yd}~wwxYw)z) Check whether XPU is available. rTzYou are using XPU version PaddlePaddle, but there is no XPU detected on your machine. Maybe XPU devices is not set properly. Original Error is NF)r)rr xpu_placesr+r,r-r.s r_is_xpu_availabler4DsZ 6==++-.222  $$%3 (  r1cRtj|rtjdnE|rtjdn-|rtj|ntjdtjdtjj j d}tjdtjj j d }tjjd d || }t}tj|}||} tjj| } | jtjjd |j} | j!y)z Testing the simple network in dygraph mode using one CPU/GPU/XPU. Args: use_cuda (bool): Whether running with CUDA. use_xpu (bool): Whether running with XPU. gpuxpucpurg?)value)rr rr!r) weight_attr bias_attrMbP? learning_rate parametersN)rdisable_static set_devicerrr rLinearr' to_tensorrrbackward optimizerAdamr@step) use_cudause_xpu use_customcustom_device_namer;r<rinput_np input_tensorrropts r_run_dygraph_singlerPTsF % % ,-% "" 699#8#8#A#A#A#LK  !6!6!?!?c!?!JIYY   1+FH##H-L %J --  J 'CLLN     (9(9(;  CHHJrctjtjjtjj 5tjj }tjj }d|_tjj||5t\}}}tjj||jgd} ddd|rtjd} nE|rtjd} n-|rtj|d} ntj} tjj| } | j!|| j!|jt#ij djgdddtj$y#1swYxYw#1swY*xYw)z Testing the simple network with executor running directly, using one CPU/GPU/XPU. Args: use_cuda (bool): Whether running with CUDA. use_xpu (bool): Whether running with XPU. r")parameter_listrN)feed fetch_list)r enable_staticr scope_guardScopeProgram random_seed program_guardrappend_backwardr CUDAPlaceXPUPlace CustomPlaceCPUPlaceExecutorrunr'rA) rIrJrKrL train_prog startup_progrrr param_gradsplaceexes r_run_static_singlergysv   " "6==#6#6#8 9]]**, }},,. #$  ]] ( (\ B!0!2 E3 --77V[[M8KC $$Q'E OOA&E &&'91=EOO%Emm$$U+    **mo.+a."5"56  + :4 -C B : 9s&A$G14>G%2CG1%G. *G11G:c:Gddtjj}tjj |}tj |}tjj }tjjd|j}tjddgd}||}tjddgd}|||}|j|j|jy) z2 train script for parallel training check c(eZdZdZfdZdZxZS))train_for_run_parallel..LinearNetz? simple fc network for parallel training check ct|tjj dd|_tjj dd|_y)N r")super__init__rrrC_linear1_linear2)self __class__s rrnz2train_for_run_parallel..LinearNet.__init__s> G  "II,,R4DM"II,,R3DMrcB|j|j|S)z! forward )rpro)rqr s rforwardz1train_for_run_parallel..LinearNet.forwards==q!12 2r)__name__ __module__ __qualname____doc__rnrt __classcell__)rrs@r LinearNetrjs  4  3rrzr=r>rlrr"N)rrLayer distributedinit_parallel_env DataParallelMSELossrFrGr@randnrErH clear_grad) rzlayerdp_layerloss_fnadaminputsoutputslabelslosss rtrain_for_run_parallelrs 3FIIOO3  ((* KE""5)Hii!G    (;(;(= ! D\\2r(I .FvG \\2q'9 -F 7F #DMMOIIKOOrc`tjjtt |y)z Testing the simple network in data parallel mode, using multiple CPU/GPU. Args: use_cuda (bool): Whether running with CUDA. use_xpu (bool): Whether running with XPU. device_list (int): The specified devices. )nprocsN)rr|spawnrr)) device_lists r _run_parallelrs# 3C >> import paddle >>> paddle.utils.run_check() >>> # doctest: +SKIP('the output will change in different run') Running verify PaddlePaddle program ... I0818 15:35:08.335391 30540 program_interpreter.cc:173] New Executor is Running. I0818 15:35:08.398319 30540 interpreter_util.cc:529] Standalone Executor is Used. PaddlePaddle works well on 1 CPU. PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now. z(Running verify PaddlePaddle program ... FNrTr"zZMore than one kind of custom devices detected, but run check would only be executed on {}.GPUXPUCPU) device_countzPaddlePaddle works well on 1 .xcclPADDLE_DISTRI_BACKENDzPaddlePaddle works well on  zs.zXPaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.z%PaddlePaddle meets some problem with aqs. This may be caused by: 1. There is not enough GPUs visible on your system 2. Some GPUs are occupied by other process now 3. NVIDIA-NCCL2 is not installed correctly on your system. Please follow instruction on https://github.com/NVIDIA/nccl-tests to test your NCCL, or reinstall it following https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.htmlz Original Error is: z7PaddlePaddle is installed successfully ONLY for single z2! Let's start deep learning with PaddlePaddle now.)printris_compiled_with_cudar0is_compiled_with_xpur4r) frameworkcoreget_all_custom_device_typer,r-formatrr*r3listrangeget_custom_device_count cpu_placesrgrPosenvironrr+) rIrJrKrL device_strrrrr/s r run_checkrsp& 45HGJ ##%%'  $ $ &#% V   " " = = ? @1 D v$$??A BQ F OOlss$$))DDFqI   mm//1  mm..0 %%**EEGJ '   %%==&   mm..A.> {#Lx*6HI':7IJ )*Q 78 { a 6< 23 + & / ~Qzl"M N f  3L>:,OE E  045 Ej\R? ? sA I J2(AJ--J2)r,numpyr#r__all__rr'r0r4rPrgrrrrrrsG $,   "J#L'T NYr