a  dM @s2dZddlZddlmZmZmZmZmZmZzddlm Z dZ Wne yVdZ Yn0zddlm Z dZ Wne ydZ Yn0zddlmZdZWne ydZYn0zdd lmZdZWne ydZYn0d d lmZmZeeeeeed Zeddd ZeddddddZddZdddZdS)zE Dataset Factory Hacked together by / Copyright 2021, Ross Wightman N)CIFAR100CIFAR10MNISTKMNIST FashionMNIST ImageFolder) Places365TF) INaturalist)QMNIST)ImageNet)IterableImageDataset ImageDataset)Zcifar10Zcifar100ZmnistZkmnistZ fashion_mnist)trainZtraining)valZvalid validationevalZ evaluationcs^|dd}tj|}tj|r,|Sfdd}|tvrJ|tn|tvrZ|tS)N[rcs0|D]&}tj|}tj|r|SqS)N)ospathjoinexists)Zsynstry_rootrootb/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/timm/data/dataset_factory.py_try1s   z_search_split.._try)splitrrrr_TRAIN_SYNONYM _EVAL_SYNONYM)rrZ split_namerrrrr _search_split*s   r"r*c  Ks|}|dr |ddd}tf||d| } |tvrft|} |tv}| fd|i| }q|dksv|dkrtsJd d }|d}t|d kr|d d }t|d kr|d }|d}|tvrd}n |tvrd}t f||d| }q|dkrBt sJd|tvr d}n|tvr.d}t fd|i| }n|dkrvt sZJd|tv}t fd|i| }n|dkrtsJd|tvrd}tfd|i| }nX|dks|dkr|rtj|rt||}t|fi| }ndsJd|n|dr0t|f|||d| }n|d r`t|f||||||| | d!| }nd|d"rt|f|||||| | d#| }n6|rtj|rt||}t|f|||d$| }|S)%a Dataset factory method In parenthesis after each arg are the type of dataset supported for each arg, one of: * folder - default, timm folder (or tar) based ImageDataset * torch - torchvision based datasets * HFDS - Hugging Face Datasets * TFDS - Tensorflow-datasets wrapper in IterabeDataset interface via IterableImageDataset * WDS - Webdataset * all - any of the above Args: name: dataset name, empty is okay for folder based datasets root: root folder of dataset (all) split: dataset split (all) search_split: search for split specific child fold from root so one can specify `imagenet/` instead of `/imagenet/val`, etc on cmd line / config. (folder, torch/folder) class_map: specify class -> index mapping via text file or dict (folder) load_bytes: load data, return images as undecoded bytes (folder) download: download dataset if not present and supported (HFDS, TFDS, torch) is_training: create dataset in train mode, this is different from the split. For Iterable / TDFS it enables shuffle, ignored for other datasets. (TFDS, WDS) batch_size: batch size hint for (TFDS, WDS) seed: seed for iterable datasets (TFDS, WDS) repeats: dataset repeats per iteration i.e. epoch (TFDS, WDS) **kwargs: other args to pass to dataset Returns: Dataset object ztorch//)rdownloadrZ inaturalistZinatz@Please update to PyTorch 1.10, torchvision 0.11+ for Inaturalistfullr r_Z 2021_trainZ 2021_valid)version target_typeZ places365zGPlease update to a newer PyTorch and torchvision for Places365 dataset.ztrain-standardrrZqmnistzDPlease update to a newer PyTorch and torchvision for QMNIST dataset.ZimagenetzFPlease update to a newer PyTorch and torchvision for ImageNet dataset.Z image_folderfolderFzUnknown torchvision dataset zhfds/)readerr class_mapztfds/)r-rr. is_trainingr' batch_sizerepeatsseedzwds/)r-rr.r/r0r1r2)r-r. load_bytes)lower startswithrdict_TORCH_BASIC_DSr has_inaturalistlenr!r has_places365r has_qmnistr has_imagenetr rrisdirr"rrr )namerrZ search_splitr.r3r/r'r0r2r1kwargsZ torch_kwargsZds_classZ use_trainZdsr+Z split_splitrrrcreate_dataset>s+                   r@) rTNFFFNr#r)__doc__rZtorchvision.datasetsrrrrrrrr: ImportErrorr r8r r;r r<Zdatasetr rr6r7r r!r"r@rrrrsV