Source code for libai.data.datasets.imagenet

# coding=utf-8
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import os
from typing import Callable, Optional

import oneflow as flow
from flowvision import datasets

from libai.data.structures import DistTensorData, Instance


[docs]class ImageNetDataset(datasets.ImageFolder): r"""`ImageNet <http://image-net.org/>`_ 2012 Classification Dataset in LiBai. Args: root (string): Root directory of the ImageNet Dataset. train (bool, optional): If True, creates dataset from training set, otherwise creates from test set. transform (callable, optional): A function/transform that takes in a PIL image and returns a transformed version. E.g, ``transforms.RandomCrop`` """ def __init__( self, root: str, train: bool = True, transform: Optional[Callable] = None, **kwargs ): prefix = "train" if train else "val" root = os.path.join(root, prefix) super(ImageNetDataset, self).__init__(root=root, transform=transform, **kwargs) def __getitem__(self, index: int): sample, target = super().__getitem__(index) data_sample = Instance( images=DistTensorData(sample, placement_idx=0), labels=DistTensorData(flow.tensor(target, dtype=flow.long), placement_idx=-1), ) return data_sample