kh?OHdZddlZddlZddlmZddlmZddlmZddl m Z m Z m Z m Z ddlZddlZddlZddlmZmZdd lmZmZdd lmZmZdd lmZdd lmZdd lm Z ejBe"Z#dZ$dZ%GddZ&dIdZ'dddddddddddddddddddeeddddddddejPejRddddddf$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+dejRd?e+d@e+dAe+dBe-dCe+fNdDZ/GdEdFej`jbjdZ3GdGdHe4Z5y)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 4t|dtsJt|}t|ddtr0t|ddtj}t|dd}||z}t j |t j}t j |g|dddjt j}t|D]}t||d|k(sJt|D]a}||d||||zz<|r0||||zzxxt j||d|z cc<F||||zzxx||d|z cc<c||fSt|ddtjrt j|D cgc]} | d c} t j}t||k(sJt j |g|ddjt j}t|D](}||xxt j||dz cc<*||fSt|ddt jrt j|D cgc]} | d c} t j}t||k(sJt j |g|ddjt j}t|D]}||j||d||fSJcc} wcc} w)zd A fast collation function optimized for uint8 images (np array or torch) and int64 targets (labels)r)dtyper ) isinstancetuplelennpndarraytorchzerosint64shapeuint8range from_numpytensorTensorcopy_) batch batch_sizeis_npinner_tuple_sizeflattened_batch_sizetargetsr"ijbs L/var/www/teggl/fontify/venv/lib/python3.12/site-packages/timm/data/loader.py fast_collater/s eAh && &UJ%(1+u%58A; 3uQx{+),<<++2%++F2JU1Xa[^5I5IJRWR]R]^z" AAuQx{#'77 77+, A.3AhqkA N*+1q:~-.%2B2B58A;q>2RR.1q:~-.%(1+a.@.  A Aw E!HQK ,,,e4!4EKKH7|z)))j=58A;+<+<=U[[Qz" 7A 1I))%(1+6 6I 7w E!HQK .,,e4!4EKKH7|z)))j=58A;+<+<=U[[Qz" )A 1IOOE!HQK ( )wu 5 5s  L4 Lc.t|ttfstt||}|St ||k7rDt j |j}|f|z}tjd|d|St ||k(sJd|S)Nz@Pretrained mean/std different shape than model, using avg value .z-normalization stats must match image channels) rrlistrrrmeanitem_loggerwarning)xnx_means r. adapt_to_chsr:Ds a% ' &A,  H Q1" IMZ[\Z]]^_` H1v{KKK{ HcTeZdZeedej dddddddf d ejjjd e e d fd e e d fd e dej de ejdede dede de fdZdZdZedZedZedZej0dZy)PrefetchLoadercudaNFconstr rloaderr3.stdchannelsdevice img_dtypefp16re_probre_modere_count re_num_splitsc t||}t||}d|ddf} ||_||_|rtj}|xstj |_tj|D cgc]} | dz c} ||j| |_ tj|D cgc]} | dz c} ||j| |_ |dkDrt|| | | ||_ nd|_ |jdk(xrtjj|_|jdk(xrtj"j|_ycc} wcc} w)Nr )rErr@) probabilitymode max_count num_splitsrEr?npu)r:rBrErfloat16float32rFr"viewr3rCrrandom_erasingtyper? is_availableis_cudarRis_npu)selfrBr3rCrDrErFrGrHrIrJrKnormalization_shaper7s r.__init__zPrefetchLoader.__init__Rs8D(+3) (Aq1   I"3emmLL" #QW #F)EEITJ]E^ <<! "QW "6DDHDI\D]  R<"/#"( #D #'D {{f,J1H1H1J kkU*Guyy/E/E/G  $ "s + E( E"c#Kd}|jrPtjj|j}t tjj |}nd|jrPtjj|j}t tjj |}nd}t}|jD]V\}}|5|j|jd}|j|jd}|j|jj|jj|j }|j"|j#|}ddd|sfnd}||jr:tjj%|jj'|nE|jr9tjj%|jj'||}|}Yfy#1swYxYww)NT)rE)stream)rE non_blockingF)rYrr?StreamrErr_rZrRrrBtorFsub_r3div_rCrVcurrent_stream wait_stream)r[firstr_stream_context next_input next_targetinputtargets r.__iter__zPrefetchLoader.__iter__{s <<ZZ&&dkk&:F$UZZ%6%6vFN [[YY%%T[[%9F$UYY%5%5fENF%N'+{{ ! #J ! A']]$++D]Q )nnDKKdnS ']]4>>:?? JOOPTPXPXY &&2!%!4!4Z!@J  AVm#!<<JJ--T[[-AMMfU[[II,,DKK,@LLVTE F+ !.Vm+ A As CH>B%H2B.H>2H; 7H>c,t|jSN)rrBr[s r.__len__zPrefetchLoader.__len__s4;;r;c.|jjSro)rBsamplerrps r.rszPrefetchLoader.sampler{{"""r;c.|jjSro)rBdatasetrps r.rvzPrefetchLoader.datasetrtr;ct|jjtr |jjjSy)NFrrB collate_fnr mixup_enabledrps r.rzzPrefetchLoader.mixup_enableds0 dkk,,.> ?;;))77 7r;ct|jjtr||jj_yyrorx)r[r7s r.rzzPrefetchLoader.mixup_enableds/ dkk,,.> ?34DKK " " 0 @r;)__name__ __module__ __qualname__r r rrEutilsdata DataLoaderrfloatintrrboolstrr]rmrqpropertyrsrvrzsetterr;r.r=r=Ps; '<%9#/5<<#7/3"!"'HKK$$//'Hs #'Hucz" 'H  'H LL 'H  ,'H'H'H'H'H'HR#J #### 55r;r=allctjjj}|j|k(sJt |t rU||}tj|tj|tjj|dzy|dvsJ|dk(r-tjj|jdzyy)Nl)rpartr) rrrget_worker_infoidrrrandomseed manual_seedr) worker_idworker_seeding worker_infors r. _worker_initrs++""224K >>Y && &.(+k* D $ t{+,000 U " IINN;++{; < #r;Fr@rAg?g?bilinearr?Trv input_sizer& is_trainingno_augrHrIrJre_splittrain_crop_modescaleratiohflipvflip color_jittercolor_jitter_probgrayscale_probgaussian_blur_prob auto_augmentnum_aug_repeatsnum_aug_splits interpolationr3.rC num_workers distributedcrop_pct crop_modecrop_border_pixelsry pin_memoryrGrFrEuse_prefetcheruse_multi_epochs_loaderpersistent_workersrtf_preprocessingc' nd}'|r|xsd}'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|dkD|_t|tr|j |d}(|rt|t j jjsR|rD|rt||}(nLt j jjj|}(nt|}(n |dk(sJd|6|"rtn-t j jjj}t j jj })|#rt"})t%|t|t j jj xr|(duxr|||(|||t't(|% |$! }* |)|fi|*}+|"r!|r|s|nd#}-t/|+|||d|!|| |-|||'$ }+|+S#t*$r$},|*j-d"|)|fi|*}+Yd},~,Md},~,wwxYw)%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 rrrrrrrrrrrrrrr3rCrrrrHrIrJrKrrseparate)rN) num_repeatszORepeatAugment not currently supported in non-distributed or IterableDataset use)r) r&shufflerrsryr drop_lastworker_init_fnrrr@) r3rCrDrErGrFrHrIrJrK)r transformrr set_loader_cfgrrrIterableDatasetrrDistributedSamplerrr/ dataloaderdefault_collaterMultiEpochsDataLoaderdictrr TypeErrorpopr=).rvrr&rrrHrIrJrrrrrrrrrrrrrrr3rCrrrrrryrrGrFrErrrrrrKrs loader_class loader_argsrBeprefetch_re_probs. r. create_loaderrsnM&+! ((     ",&."$ !"#$%&.'()*+,-.$/0*12&34 !#5G:'/0 ;7G:gu{{/?/?/O/OP *7P++**66II'R08G!#v%vv#%3\9I9I9T9T9d9d ;;##..L, w (8(8(H(HIImgY]ombm|NK- K6g55&1&7b ]$'   M' 6,-g556s H H4H//H4c*eZdZfdZdZdZxZS)rct||i|d|_|jt |j |_nt |j|_d|_t||_y)NFT)superr]_DataLoader__initialized batch_sampler_RepeatSamplerrsrmiterator)r[argskwargs __class__s r.r]zMultiEpochsDataLoader.__init__sc $)&)(-%    %)$,,7DL!/0B0B!CD (,%(* r;c|jt|jSt|jjSro)rrrsrps r.rqzMultiEpochsDataLoader.__len__s2$($6$6$>s4<< cCHZHZHbHbDccr;c#lKtt|D]}t|jywro)r rnextr)r[r+s r.rmzMultiEpochsDataLoader.__iter__s-s4y! &At}}% % &s24)r|r}r~r]rqrm __classcell__)rs@r.rr}s+d&r;rceZdZdZdZdZy)rzH Sampler that repeats forever. Args: sampler (Sampler) c||_yro)rs)r[rss r.r]z_RepeatSampler.__init__s  r;c#LK t|jEd{7wro)iterrsrps r.rmz_RepeatSampler.__iter__s#DLL) ) ) )s $"$N)r|r}r~__doc__r]rmrr;r.rrs *r;r)r)6rloggingr contextlibr functoolsr itertoolsrtypingrrrr rtorch.utils.datanumpyr constantsr r rvr rdistributed_samplerrrrVrmixuprtransforms_factoryr getLoggerr|r5r/r:r=rrTrErrrrrrrrrrobjectrrr;r.rsN 33 B7L)#0 '  H %$N  e5e5P =(")-/3/3!-1 "$&&* '"7!5!$(#',0)- !&+u||F3#(-#'#!&Or|%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!KrLMrNOrj&EKK,,77&( *V *r;