68 lines
2.5 KiB
Python
68 lines
2.5 KiB
Python
'''The implementation of ASAM and SAM are borrowed from
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https://github.com/debcaldarola/fedsam
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Caldarola, D., Caputo, B., & Ciccone, M.
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Improving Generalization in Federated Learning by Seeking Flat Minima,
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European Conference on Computer Vision (ECCV) 2022.
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'''
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import re
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import json
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import numpy as np
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from federatedscope.register import register_splitter
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from federatedscope.core.splitters import BaseSplitter
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class FedSAM_CIFAR10_Splitter(BaseSplitter):
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"""
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This splitter split according to what FedSAM provides
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Args:
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client_num: the dataset will be split into ``client_num`` pieces
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alpha (float): Partition hyperparameter in LDA, smaller alpha \
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generates more extreme heterogeneous scenario see \
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``np.random.dirichlet``
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"""
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def __init__(self, client_num, alpha=0.5):
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self.alpha = alpha
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super(FedSAM_CIFAR10_Splitter, self).__init__(client_num)
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def __call__(self, dataset, prior=None, **kwargs):
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dataset = [ds for ds in dataset]
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label = np.array([y for x, y in dataset])
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alpha_str = f'{self.alpha:.2f}'
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if len(label) == 50000:
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filename = \
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'data/fedsam_cifar10/data/{}/federated_{}_alpha_{' \
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'}.json'.format('train', 'train', alpha_str)
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elif len(label) == 10000:
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filename = 'data/fedsam_cifar10/data/test/test.json'
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with open(filename, 'r') as ips:
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content = json.load(ips)
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idx_slice = []
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def get_idx(name_list):
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return [
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int(re.findall('img_\d+_label', fn)[0][4:-6])
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for fn in name_list
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]
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if len(label) == 50000:
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for uid in range(self.client_num):
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idx_slice.append(
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get_idx(content['user_data'][str(uid)]['x']))
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elif len(label) == 10000:
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idx_slice.append(get_idx(content['user_data'][str(100)]['x']))
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idx_slice = np.array_split(np.array(idx_slice[0]),
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self.client_num)
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data_list = [[dataset[idx] for idx in idxs] for idxs in idx_slice]
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return data_list
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def call_fedsam_cifar10_splitter(splitter_type, client_num, **kwargs):
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if splitter_type == 'fedsam_cifar10_splitter':
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splitter = FedSAM_CIFAR10_Splitter(client_num, **kwargs)
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return splitter
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register_splitter('fedsam_cifar10_splitter', call_fedsam_cifar10_splitter)
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