Functions — github.com/AshwinRJ/Federated-Learning-PyTorch

CodeHub MCPcopy Create free account

hub / github.com/AshwinRJ/Federated-Learning-PyTorch / functions

Functions27 in github.com/AshwinRJ/Federated-Learning-PyTorch

⨍ Functions 27 ◇ Types & classes 7

↓ 4 callersMethod__init__

(self, dim_in, dim_hidden, dim_out)

src/models.py:10

↓ 2 callersFunctionargs_parser

src/options.py:8

↓ 2 callersFunctionget_dataset

Returns train and test datasets and a user group which is a dict where the keys are the user index and the values are the corresponding data for

src/utils.py:12

↓ 2 callersFunctionmnist_noniid

Sample non-I.I.D client data from MNIST dataset :param dataset: :param num_users: :return:

src/sampling.py:26

↓ 2 callersFunctiontest_inference

Returns the test accuracy and loss.

src/update.py:114

↓ 1 callersFunctionaverage_weights

Returns the average of the weights.

src/utils.py:75

↓ 1 callersFunctioncifar_iid

Sample I.I.D. client data from CIFAR10 dataset :param dataset: :param num_users: :return: dict of image index

src/sampling.py:145

↓ 1 callersFunctioncifar_noniid

Sample non-I.I.D client data from CIFAR10 dataset :param dataset: :param num_users: :return:

src/sampling.py:161

↓ 1 callersFunctionexp_details

src/utils.py:87

↓ 1 callersMethodinference

Returns the inference accuracy and loss.

src/update.py:89

↓ 1 callersFunctionmnist_iid

Sample I.I.D. client data from MNIST dataset :param dataset: :param num_users: :return: dict of image index

src/sampling.py:10

↓ 1 callersFunctionmnist_noniid_unequal

Sample non-I.I.D client data from MNIST dataset s.t clients have unequal amount of data :param dataset: :param num_users: :return

src/sampling.py:55

↓ 1 callersMethodtrain_val_test

Returns train, validation and test dataloaders for a given dataset and user indexes.

src/update.py:36

↓ 1 callersMethodupdate_weights

(self, model, global_round)

src/update.py:54

Method__getitem__

src/update.py:21

src/models.py:28

src/models.py:47

src/models.py:70

(self, input_size, n_classes=10, **kwargs)

src/models.py:89

(self, dataset, idxs)

src/update.py:14

(self, args, dataset, idxs, logger)

src/update.py:27

src/update.py:18

src/models.py:18

src/models.py:36

src/models.py:61

src/models.py:79

src/models.py:103