Module data_preprocess.fl_datasets.cifar100

Expand source code
import os
from PIL import Image
from ..h5_tff_dataset import H5TFFDataset


class FLCifar100(H5TFFDataset):
    """
    CIFAR100 Dataset.
    500 clients that were allocated data_preprocess using LDA.
    """
    def __init__(self, h5_path, transform, client_id=None, train=True):
        if train:
            h5_path = os.path.join(h5_path, 'cifar100_fl/fed_cifar100_train.h5')
        else:
            h5_path = os.path.join(h5_path, 'cifar100_fl/fed_cifar100_test.h5')

        super(FLCifar100, self).__init__(h5_path, client_id, 'cifar100_fl', 'image')
        self.transform = transform

    def __getitem__(self, index):
        """
        Args:
            index (int): Index of item that is fetched on behalf on current setup client

        Returns:
            tuple: (image, target) where target is index of the target class.
        """
        client, i = self._get_item_preprocess(index)
        img = Image.fromarray(self.dataset[client]['image'][i])
        x = self.transform(img)
        y = self.dataset[client]['label'][i]
        return x, y

Classes

class FLCifar100 (h5_path, transform, client_id=None, train=True)

CIFAR100 Dataset. 500 clients that were allocated data_preprocess using LDA.

Ctor.

Args

h5_path : str
path to HDF5 file with dataset. Not native for systems like TensorFlow
client_id : int
switch dataset to work view of client client_id

data_key(str): if h5_path is not in the filesystem and download is True then it will an attempt to download dataset from TFF_DATASETS[data_key] URL download(bool): allow to download dataset

Expand source code
class FLCifar100(H5TFFDataset):
    """
    CIFAR100 Dataset.
    500 clients that were allocated data_preprocess using LDA.
    """
    def __init__(self, h5_path, transform, client_id=None, train=True):
        if train:
            h5_path = os.path.join(h5_path, 'cifar100_fl/fed_cifar100_train.h5')
        else:
            h5_path = os.path.join(h5_path, 'cifar100_fl/fed_cifar100_test.h5')

        super(FLCifar100, self).__init__(h5_path, client_id, 'cifar100_fl', 'image')
        self.transform = transform

    def __getitem__(self, index):
        """
        Args:
            index (int): Index of item that is fetched on behalf on current setup client

        Returns:
            tuple: (image, target) where target is index of the target class.
        """
        client, i = self._get_item_preprocess(index)
        img = Image.fromarray(self.dataset[client]['image'][i])
        x = self.transform(img)
        y = self.dataset[client]['label'][i]
        return x, y

Ancestors

  • data_preprocess.h5_tff_dataset.H5TFFDataset
  • data_preprocess.fl_dataset.FLDataset
  • torch.utils.data.dataset.Dataset
  • typing.Generic