# 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