# coding=utf-8
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from typing import Callable, Optional
import oneflow as flow
from flowvision import datasets
from libai.data.structures import DistTensorData, Instance
[docs]class CIFAR10Dataset(datasets.CIFAR10):
r"""`CIFAR10 <https://www.cs.toronto.edu/~kriz/cifar.html>`_ Dataset in LiBai.
Args:
root (string): Root directory of dataset where directory
``cifar-10-batches-py`` exists or will be saved to if download is set to True.
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``
download (bool, optional): If true, downloads the dataset from the internet and
puts it in root directory. If the dataset is already downloaded, it will not be
downloaded again.
"""
def __init__(
self,
root: str,
train: bool = True,
transform: Optional[Callable] = None,
download: bool = False,
**kwargs
):
super(CIFAR10Dataset, self).__init__(
root=root, train=train, transform=transform, download=download, **kwargs
)
def __getitem__(self, index: int):
img, target = super().__getitem__(index)
data_sample = Instance(
images=DistTensorData(img, placement_idx=0),
labels=DistTensorData(flow.tensor(target, dtype=flow.long), placement_idx=-1),
)
return data_sample
[docs]class CIFAR100Dataset(datasets.CIFAR100):
r"""`CIFAR100 <https://www.cs.toronto.edu/~kriz/cifar.html>`_ Dataset in LiBai.
Args:
root (string): Root directory of dataset where directory
``cifar-10-batches-py`` exists or will be saved to if download is set to True.
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``
download (bool, optional): If true, downloads the dataset from the internet and
puts it in root directory. If the dataset is already downloaded, it will not be
downloaded again.
dataset_name (str, optional): Name for the dataset as an identifier. E.g, ``cifar100``
"""
def __init__(
self,
root: str,
train: bool = True,
transform: Optional[Callable] = None,
download: bool = False,
**kwargs
):
super(CIFAR100Dataset, self).__init__(
root=root, train=train, transform=transform, download=download, **kwargs
)
def __getitem__(self, index: int):
img, target = super().__getitem__(index)
data_sample = Instance(
images=DistTensorData(img, placement_idx=0),
labels=DistTensorData(flow.tensor(target, dtype=flow.long), placement_idx=-1),
)
return data_sample