update

fgssl/__init__.py

@@ -0,0 +1,18 @@
+from __future__ import absolute_import, division, print_function
+
+__version__ = '0.2.1'
+
+
+def _setup_logger():
+    import logging
+
+    logging_fmt = "%(asctime)s (%(module)s:%(lineno)d)" \
+                  "%(levelname)s: %(message)s"
+    logger = logging.getLogger("federatedscope")
+    handler = logging.StreamHandler()
+    handler.setFormatter(logging.Formatter(logging_fmt))
+    logger.addHandler(handler)
+    logger.propagate = False
+
+
+_setup_logger()

fgssl/attack/auxiliary/MIA_get_target_data.py

@@ -0,0 +1,32 @@
+import torch
+from federatedscope.attack.auxiliary.utils import get_data_info
+
+
+def get_target_data(dataset_name, pth=None):
+    '''
+
+    Args:
+        dataset_name (str): the dataset name
+        pth (str): the path storing the target data
+
+    Returns:
+
+    '''
+    # JUST FOR SHOWCASE
+    if pth is not None:
+        pass
+    else:
+        # generate the synthetic data
+        if dataset_name == 'femnist':
+            data_feature_dim, num_class, is_one_hot_label = get_data_info(
+                dataset_name)
+
+            # generate random data
+            num_syn_data = 20
+            data_dim = [num_syn_data]
+            data_dim.extend(data_feature_dim)
+            syn_data = torch.randn(data_dim)
+            syn_label = torch.randint(low=0,
+                                      high=num_class,
+                                      size=(num_syn_data, ))
+            return [syn_data, syn_label]

fgssl/attack/auxiliary/__init__.py

@@ -0,0 +1,16 @@
+from federatedscope.attack.auxiliary.utils import *
+from federatedscope.attack.auxiliary.attack_trainer_builder \
+    import wrap_attacker_trainer
+from federatedscope.attack.auxiliary.backdoor_utils import *
+from federatedscope.attack.auxiliary.poisoning_data import *
+from federatedscope.attack.auxiliary.create_edgeset import *
+
+__all__ = [
+    'get_passive_PIA_auxiliary_dataset', 'iDLG_trick', 'cos_sim',
+    'get_classifier', 'get_data_info', 'get_data_sav_fn', 'get_info_diff_loss',
+    'sav_femnist_image', 'get_reconstructor', 'get_generator',
+    'get_data_property', 'get_passive_PIA_auxiliary_dataset',
+    'load_poisoned_dataset_edgeset', 'load_poisoned_dataset_pixel',
+    'selectTrigger', 'poisoning', 'create_ardis_poisoned_dataset',
+    'create_ardis_poisoned_dataset', 'create_ardis_test_dataset'
+]

fgssl/attack/auxiliary/attack_trainer_builder.py

@@ -0,0 +1,23 @@
+def wrap_attacker_trainer(base_trainer, config):
+    '''Wrap the trainer for attack client.
+    Args:
+        base_trainer (core.trainers.GeneralTorchTrainer): the trainer that
+        will be wrapped;
+        config (federatedscope.core.configs.config.CN): the configure;
+
+    :returns:
+        The wrapped trainer; Type: core.trainers.GeneralTorchTrainer
+
+    '''
+    if config.attack.attack_method.lower() == 'gan_attack':
+        from federatedscope.attack.trainer import wrap_GANTrainer
+        return wrap_GANTrainer(base_trainer)
+    elif config.attack.attack_method.lower() == 'gradascent':
+        from federatedscope.attack.trainer import wrap_GradientAscentTrainer
+        return wrap_GradientAscentTrainer(base_trainer)
+    elif config.attack.attack_method.lower() == 'backdoor':
+        from federatedscope.attack.trainer import wrap_backdoorTrainer
+        return wrap_backdoorTrainer(base_trainer)
+    else:
+        raise ValueError('Trainer {} is not provided'.format(
+            config.attack.attack_method))