pathological_mnist

Module Contents

PathologicalMNIST

The partition stratigy in FedAvg. See http://proceedings.mlr.press/v54/mcmahan17a?ref=https://githubhelp.com

class PathologicalMNIST(root, path, num_clients=100, shards=200, download=True, preprocess=False)

Bases: fedlab.contrib.dataset.basic_dataset.FedDataset

The partition stratigy in FedAvg. See http://proceedings.mlr.press/v54/mcmahan17a?ref=https://githubhelp.com

Parameters:

• root (str) – Path to download raw dataset.

• path (str) – Path to save partitioned subdataset.

• num_clients (int) – Number of clients.

• shards (int, optional) – Sort the dataset by the label, and uniformly partition them into shards. Then

• download (bool, optional) – Download. Defaults to True.

preprocess(download=True)

Define the dataset partition process

get_dataset(id, type='train')

Load subdataset for client with client ID cid from local file.

Parameters:

• cid (int) – client id

• type (str, optional) – Dataset type, can be "train", "val" or "test". Default as "train".

Returns:

Dataset

get_dataloader(id, batch_size=None, type='train')

Return dataload for client with client ID cid.

Parameters:

• cid (int) – client id

• batch_size (int, optional) – batch size in DataLoader.

• type (str, optional) – Dataset type, can be "train", "val" or "test". Default as "train".