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Pengqian Lu
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update cifar100
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-9
lines changed

3 files changed

+202
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‎.gitignore

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# don't upload cache file
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__pycache__/
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.vscode/
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/log/
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/database/
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generate_bash.ipynb
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.ipynb
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*.sh
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/results/

‎config/cifar100.json

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[
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{
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"dataset": "cifar100",
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"noise_type": "ILN",
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"noise_rate": 30,
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"loss": "rtcatoni",
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"settings": {
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"pretrain": 30,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "ILN",
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"noise_rate": 30,
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"loss": "rtlogsum",
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"settings": {
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"pretrain": 20,
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"relax": 3
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "ILN",
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"noise_rate": 30,
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"loss": "rtwelschp",
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"settings": {
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"pretrain": 40,
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"relax": 3
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "ILN",
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"noise_rate": 50,
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"loss": "rtcatoni",
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"settings": {
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"pretrain": 40,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "ILN",
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"noise_rate": 50,
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"loss": "rtlogsum",
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"settings": {
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"pretrain": 20,
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"relax": 3
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "ILN",
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"noise_rate": 50,
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"loss": "rtwelschp",
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"settings": {
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"pretrain": 20,
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"relax": 4
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "pairflip",
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"noise_rate": 30,
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"loss": "rtcatoni",
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"settings": {
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"pretrain": 30,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "pairflip",
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"noise_rate": 30,
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"loss": "rtlogsum",
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"settings": {
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"pretrain": 40,
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"relax": 3
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "pairflip",
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"noise_rate": 30,
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"loss": "rtwelschp",
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"settings": {
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"pretrain": 40,
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"relax": 3
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "pairflip",
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"noise_rate": 45,
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"loss": "rtcatoni",
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"settings": {
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"pretrain": 20,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "pairflip",
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"noise_rate": 45,
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"loss": "rtlogsum",
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"settings": {
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"pretrain": 20,
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"relax": 3
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "pairflip",
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"noise_rate": 45,
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"loss": "rtwelschp",
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"settings": {
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"pretrain": 40,
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"relax": 3
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "symmetric",
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"noise_rate": 30,
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"loss": "rtcatoni",
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"settings": {
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"pretrain": 10,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "symmetric",
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"noise_rate": 30,
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"loss": "rtlogsum",
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"settings": {
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"pretrain": 10,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "symmetric",
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"noise_rate": 30,
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"loss": "rtwelschp",
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"settings": {
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"pretrain": 50,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "symmetric",
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"noise_rate": 50,
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"loss": "rtcatoni",
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"settings": {
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"pretrain": 10,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "symmetric",
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"noise_rate": 50,
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"loss": "rtlogsum",
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"settings": {
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"pretrain": 15,
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"relax": 2
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}
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},
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{
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"dataset": "cifar100",
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"noise_type": "symmetric",
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"noise_rate": 50,
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"loss": "rtwelschp",
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"settings": {
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"pretrain": 50,
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"relax": 2
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}
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}
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]

‎option.py

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elif args.dataset == 'news':
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args.model = 'newsnet'
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args.data_path = "./database/news/"
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elif args.dataset == 'cifar100':
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args.model = 'resnet50'
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args.data_path = "./database/cifar100"
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import json
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file_path = f"./config/{args.dataset}.json"
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with open(file_path, 'r') as f:
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config = json.load(f)
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for item in config['configurations']:
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if item['loss'] == args.loss and item['noise_rate'] == args.noise_rate and item['noise_type'] == args.noise_type:
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if 'pretrain' in item['settings']:
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args.pretrain = item['settings']['pretrain']
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if 'relax' in item['settings']:
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args.relax = item['settings']['relax']
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break
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import os
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if os.path.exists(file_path):
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with open(file_path, 'r') as f:
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config = json.load(f)
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for item in config['configurations']:
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if item['loss'] == args.loss and item['noise_rate'] == args.noise_rate and item['noise_type'] == args.noise_type:
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if 'pretrain' in item['settings']:
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args.pretrain = item['settings']['pretrain']
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if 'relax' in item['settings']:
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args.relax = item['settings']['relax']
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break

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