85 lines
2.8 KiB
Python
85 lines
2.8 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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from federatedscope.core.auxiliaries.data_builder import get_data
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from federatedscope.core.auxiliaries.utils import setup_seed
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from federatedscope.core.auxiliaries.logging import update_logger
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from federatedscope.core.configs.config import global_cfg
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from federatedscope.core.fed_runner import FedRunner
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from federatedscope.core.auxiliaries.worker_builder import get_server_cls, get_client_cls
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SAMPLE_CLIENT_NUM = 5
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class SimCLR_CIFAR10Test(unittest.TestCase):
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def setUp(self):
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print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
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def set_config_simclr_cifar10(self, cfg):
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backup_cfg = cfg.clone()
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import torch
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cfg.use_gpu = torch.cuda.is_available()
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cfg.eval.freq = 5
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cfg.eval.metrics = ['loss']
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cfg.eval.split = ['val', 'test']
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cfg.federate.mode = 'standalone'
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cfg.train.local_update_steps = 5
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cfg.train.batch_or_epoch = 'batch'
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cfg.federate.total_round_num = 20
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cfg.federate.client_num = 5
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cfg.federate.sample_client_num = 5
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cfg.data.root = 'test_data/'
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cfg.data.type = 'Cifar4CL'
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cfg.data.splits = [0.8, 0.1, 0.1]
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cfg.data.batch_size = 256
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cfg.data.splitter = 'lda'
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cfg.data.splitter_args = [{'alpha': 0.1}]
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cfg.data.consistent_label_distribution = True
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cfg.data.num_workers = 4
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cfg.data.subsample = 1.0
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cfg.model.type = 'SimCLR'
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cfg.model.hidden = 256
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cfg.model.out_channels = 1
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cfg.train.optimizer.lr = 0.01
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cfg.train.optimizer.weight_decay = 0.0001
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cfg.train.optimizer.momentum = 0.9
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cfg.criterion.type = 'NT_xentloss'
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cfg.trainer.type = 'cltrainer'
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cfg.seed = 1
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return backup_cfg
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def test_simclr_cifar10_standalone(self):
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init_cfg = global_cfg.clone()
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backup_cfg = self.set_config_simclr_cifar10(init_cfg)
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setup_seed(init_cfg.seed)
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update_logger(init_cfg, True)
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data, modified_cfg = get_data(init_cfg.clone())
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init_cfg.merge_from_other_cfg(modified_cfg)
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self.assertIsNotNone(data)
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self.assertEqual(init_cfg.federate.sample_client_num,
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SAMPLE_CLIENT_NUM)
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Fed_runner = FedRunner(data=data,
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server_class=get_server_cls(init_cfg),
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client_class=get_client_cls(init_cfg),
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config=init_cfg.clone())
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self.assertIsNotNone(Fed_runner)
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test_best_results = Fed_runner.run()
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print(test_best_results)
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init_cfg.merge_from_other_cfg(backup_cfg)
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self.assertLess(
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test_best_results["client_summarized_weighted_avg"]['test_loss'],
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10000)
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if __name__ == '__main__':
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unittest.main()
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