Ng<O~dZddlZddlZddlmZddlmZddlmZddl m Z m Z m Z m Z ddlZddlZddlZddlmZmZdd lmZmZdd lmZmZdd lmZdd lmZdd lm Z ej!e"Z#dZ$dZ%GddZ&dIdZ'dddddddddddddddddddeeddddddddej(ej)ddddddf$de eefde e*e e*e*fe e*e*e*ffde*de+d e+d!e,d"e-d#e*d$e+d%e e-d&e e e,e,fd'e e e,e,fd(e,d)e,d*e,d+e e,d,e,d-e,d.e e-d/e*d0e*d1e-d2e e,d3fd4e e,d3fd5e*d6e+d7e e,d8e e-d9e e*d:e e d;e+dej)d?e+d@e+dAe+dBe-dCe+fNdDZ/GdEdFej0j1j2Z3GdGdHe4Z5dS)Ja Loader Factory, Fast Collate, CUDA Prefetcher Prefetcher and Fast Collate inspired by NVIDIA APEX example at https://github.com/NVIDIA/apex/commit/d5e2bb4bdeedd27b1dfaf5bb2b24d6c000dee9be#diff-cf86c282ff7fba81fad27a559379d5bf Hacked together by / Copyright 2019, Ross Wightman N)suppress)partial)repeat)CallableOptionalTupleUnion)IMAGENET_DEFAULT_MEANIMAGENET_DEFAULT_STD)IterableImageDataset ImageDataset)OrderedDistributedSamplerRepeatAugSampler) RandomErasing)FastCollateMixup)create_transformc 6t|dtsJt|}t|ddtrt|dd}||z}tj|tj}tj|g|dddjRtj}t|D]}t||d|ksJt|D]S}||d||||zz<||||zzxxtj ||d|z cc<T||fSt|ddtj rtj d|Dtj}t||ksJtj|g|ddjRtj}t|D]0}||xxtj ||dz cc<1||fSt|ddtj rtj d|Dtj}t||ksJtj|g|ddjRtj}t|D])}||||d*||fSJ)zd A fast collation function optimized for uint8 images (np array or torch) and int64 targets (labels)r)dtyper cg|] }|d Sr .0bs L/var/www/html/ai-engine/env/lib/python3.11/site-packages/timm/data/loader.py z fast_collate../444!444cg|] }|d Srrrs rrz fast_collate..6rr) isinstancetuplelentorchzerosint64shapeuint8range from_numpynpndarraytensorTensorcopy_)batch batch_sizeinner_tuple_sizeflattened_batch_sizetargetsr-ijs r fast_collater7s  eAh & &&&&UJ%(1+u%%uQx{++),<<+2%+FFF2JU1Xa[^5IJJRWR]^^^z"" O OAuQx{##'77777+,, O O.3AhqkA N*+q1z>)***e.>uQx{1~.N.NN**** Ow E!HQK , ,,44e444EKHHH7||z))))j=58A;+<==U[QQQz"" 7 7A 1III)%(1+66 6IIIIw E!HQK . .,44e444EKHHH7||z))))j=58A;+<==U[QQQz"" ) )A 1IOOE!HQK ( ( ( (w rcpt|ttfstt||}n{t ||krKt j|}|f|z}t d|dnt ||ks Jd|S)Nz@Pretrained mean/std different shape than model, using avg value .z-normalization stats must match image channels) r!r"listrr#r+meanitem_loggerwarning)xnx_means r adapt_to_chsrB@s a% ' 'L &A,,   Q1"" IM_[\___````1vv{{{K{{{ Hrc eZdZeedejdejdddddf dZd Z d Z e d Z e d Z e d ZejdZdS)PrefetchLoadercudaFconstr rc &t||}t||}d|ddf} ||_||_|r tj}||_tjd|D||| |_tjd|D||| |_ |dkrt|| | | ||_ nd|_ tj o |jdk|_dS)Nr cg|]}|dzSrrr?s rrz+PrefetchLoader.__init__..gs # # #QW # # #r)devicercg|]}|dzSrKrrMs rrz+PrefetchLoader.__init__..is " " "QW " " "rrG) probabilitymode max_count num_splitsrNrF)rBloaderrNr$float16 img_dtyper-viewr;stdrrandom_erasingrF is_availabletypeis_cuda) selfrTr;rXchannelsrNrVfp16re_probre_modere_count re_num_splitsnormalization_shapes r__init__zPrefetchLoader.__init__Ns8D(++3)) (Aq1   & I"L # #d # # #F)EEEEITJ]E^E^ < " "c " " "6DDDDHDI\D]D]  R<<"/#"( ###D  #'D z..00JV[F5J rc#Kd}|jr?tj}t tjj|}n d}t }|jD]\}}|5||j d}||j d}||j  |j  |j}|j||}dddn #1swxYwY|s||fVnd}|1tj||}|} ||fVdS)NT)stream)rN non_blockingF)r\r$rFStreamrrgrrTtorNrVsub_r;div_rXrYcurrent_stream wait_stream)r]firstrgstream_context next_input next_targetinputtargets r__iter__zPrefetchLoader.__iter__vs < &Z&&((F$UZ%6vFFFNNF%N'+{ ! ! #J !! A A']]$+D]QQ )nnDKdnSS ']]4>::?? JJOOPTPXYY &2!%!4!4Z!@!@J  A A A A A A A A A A A A A A A Vm####! ))++77???E FFVms+BDD D c*t|jSN)r#rTr]s r__len__zPrefetchLoader.__len__s4;rc|jjSrw)rTsamplerrxs rr{zPrefetchLoader.sampler {""rc|jjSrw)rTdatasetrxs rr~zPrefetchLoader.datasetr|rcft|jjtr|jjjSdS)NFr!rT collate_fnr mixup_enabledrxs rrzPrefetchLoader.mixup_enableds- dk,.> ? ? ;)7 75rcjt|jjtr||jj_dSdSrwr)r]r?s rrzPrefetchLoader.mixup_enableds7 dk,.> ? ? 534DK " 0 0 0 5 5rN)__name__ __module__ __qualname__r r r$rNfloat32rerurypropertyr{r~rsetterrrrrDrDLs '$5<''m&K&K&K&KP>   ##X###X#X 55555rrDallctjj}|j|ksJt |t rW||}tj|tj |tj|dzdS|dvsJ|dkr)tj|jdzdSdS)Nl)rpartr) r$utilsdataget_worker_infoidr!rrandomseed manual_seedr+) worker_idworker_seeding worker_infors r _worker_initrs+"2244K >Y & & & &.(++ =~k** D $ t{+,,,,,0000 U " " INN;+{; < < < < < # "rFrGrHg?g?bilinearrFTr~ input_sizer1 is_trainingno_augr`rarbre_splittrain_crop_modescaleratiohflipvflip color_jittercolor_jitter_probgrayscale_probgaussian_blur_prob auto_augmentnum_aug_repeatsnum_aug_splits interpolationr;.rX num_workers distributedcrop_pct crop_modecrop_border_pixelsr pin_memoryr_rVrNuse_prefetcheruse_multi_epochs_loaderpersistent_workersrtf_preprocessingc' Bd}'|r|pd}'t|fid|d|d| d| d| d| d | d |d |d |d |d|d|d|d|d|d|d|d|d|d|d|'d|&d|"d|dk|_t|tr||d}(|rtt|t jjjsP|r>|rt||}(nJt jjj |}(n t|}(n|dks Jd|$|"rtnt jjjj}t jjj})|#rt"})t%|t|t jjj o|(duo|||(|||t't(|% |$! }* |)|fi|*}+n5#t*$r(},|*d"|)|fi|*}+Yd},~,nd},~,wwxYw|"r(|r|s|nd#}-t/|+|||d|!|| |-|||'$ }+|+S)%a Args: dataset: The image dataset to load. input_size: Target input size (channels, height, width) tuple or size scalar. batch_size: Number of samples in a batch. is_training: Return training (random) transforms. no_aug: Disable augmentation for training (useful for debug). re_prob: Random erasing probability. re_mode: Random erasing fill mode. re_count: Number of random erasing regions. re_split: Control split of random erasing across batch size. scale: Random resize scale range (crop area, < 1.0 => zoom in). ratio: Random aspect ratio range (crop ratio for RRC, ratio adjustment factor for RKR). hflip: Horizontal flip probability. vflip: Vertical flip probability. color_jitter: Random color jitter component factors (brightness, contrast, saturation, hue). Scalar is applied as (scalar,) * 3 (no hue). color_jitter_prob: Apply color jitter with this probability if not None (for SimlCLR-like aug grayscale_prob: Probability of converting image to grayscale (for SimCLR-like aug). gaussian_blur_prob: Probability of applying gaussian blur (for SimCLR-like aug). auto_augment: Auto augment configuration string (see auto_augment.py). num_aug_repeats: Enable special sampler to repeat same augmentation across distributed GPUs. num_aug_splits: Enable mode where augmentations can be split across the batch. interpolation: Image interpolation mode. mean: Image normalization mean. std: Image normalization standard deviation. num_workers: Num worker processes per DataLoader. distributed: Enable dataloading for distributed training. crop_pct: Inference crop percentage (output size / resize size). crop_mode: Inference crop mode. One of ['squash', 'border', 'center']. Defaults to 'center' when None. crop_border_pixels: Inference crop border of specified # pixels around edge of original image. collate_fn: Override default collate_fn. pin_memory: Pin memory for device transfer. fp16: Deprecated argument for half-precision input dtype. Use img_dtype. img_dtype: Data type for input image. device: Device to transfer inputs and targets to. use_prefetcher: Use efficient pre-fetcher to load samples onto device. use_multi_epochs_loader: persistent_workers: Enable persistent worker processes. worker_seeding: Control worker random seeding at init. tf_preprocessing: Use TF 1.0 inference preprocessing for testing model ports. Returns: DataLoader rrrrrrrrrrrrrrr;rXrrrr`rarbrcrrseparate)rN) num_repeatszORepeatAugment not currently supported in non-distributed or IterableDataset use)r) r1shufflerr{rr drop_lastworker_init_fnrrrG) r;rXr^rNr_rVr`rarbrc)r transformr!r set_loader_cfgr$rrIterableDatasetrrDistributedSamplerrr7 dataloaderdefault_collate DataLoaderMultiEpochsDataLoaderdictrr TypeErrorpoprD).r~rr1rrr`rarbrrrrrrrrrrrrrrr;rXrrrrrrrr_rVrNrrrrrrcr{ loader_class loader_argsrTeprefetch_re_probs. r create_loaderrsnM,&+! (Kv(  e  e ee"\,+&~.-"\$mT C!"#$)%&.-'()*+,-.$m/0*)12&~34 !##5G:'/008 ;777G w:gu{/?/OPP w  9 S*7PPP+*6II'RR088GG!###%v###%3d\\9I9T9d ;#.L-, w (8(HIIImgY]ombm|NKKK-   K6g5555 666,---g55556 &1H&H77b ]$'     Ms6 G G2 G--G2c*eZdZfdZdZdZxZS)rctj|i|d|_|jt |j|_nt |j|_d|_t|_dS)NFT)superre_DataLoader__initialized batch_sampler_RepeatSamplerr{ruiterator)r]argskwargs __class__s rrezMultiEpochsDataLoader.__init__tsy$)&)))(-%   %)$,77DLL!/0B!C!CD (,%((** rcj|jt|jnt|jjSrw)rr#r{rxs rryzMultiEpochsDataLoader.__len__~s-$($6$>s4<   CHZHbDcDccrc#tKtt|D]}t|jVdSrw)r)r#nextr)r]r5s rruzMultiEpochsDataLoader.__iter__sFs4yy!! & &At}%% % % % % & &r)rrrreryru __classcell__)rs@rrrrsY+++++ddd&&&&&&&rrceZdZdZdZdZdS)rzH Sampler that repeats forever. Args: sampler (Sampler) c||_dSrw)r{)r]r{s rrez_RepeatSampler.__init__s  rc#>K t|jEd{Vrw)iterr{rxs rruz_RepeatSampler.__iter__s2 *DL)) ) ) ) ) ) ) ) *rN)rrr__doc__rerurrrrrs< *****rr)r)6rloggingr contextlibr functoolsr itertoolsrtypingrrrr r$torch.utils.datanumpyr+ constantsr r r~r rdistributed_samplerrrrYrmixuprtransforms_factoryr getLoggerrr=r7rBrDrrrNintboolfloatstrrrrrrrobjectrrrrrs 333333333333 BBBBBBBB77777777LLLLLLLL))))))######000000 ' H % %   F    ^5^5^5^5^5^5^5^5B = = = =(")-/3/3!-1 "$&&* '"7!5!$(#',0)- !&+u|F33#(-#'#!&Orr|%99:r#uS#Xc3m0DDErr r  r  rrrr"#reUl+,reUl+,rrrr $E?!r"#r$"%r&sm'r()r*+r,-r.E3J/r05#: 1r23r45r65/7r8C=9r:%SM;r<X&=r>?r@ArB;CrD ErFGrH"&IrJ!KrLMrNOrrrrj&&&&&EK,7&&&( * * * * *V * * * * *r