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run_pipeline.py
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from omegaconf import OmegaConf
import eval_linear, eval_knn
import pretrain
import utils
if __name__ == "__main__":
# load pretrain config
cfg = OmegaConf.load('pretrain.yaml')
# init distributed
utils.distributed.init_distributed_mode(cfg)
utils.fix_random_seeds(cfg.seed)
print('*************STARTING PRETRAINING*************')
pretrain.main(cfg)
################## LINEAR EVALUATION ##################
print('*************STARTING LINEAR EVAL EVALUATION: ImageNet*************')
eval_linear_cfg = OmegaConf.load("eval_linear.yaml")
# copy dist parameters
eval_linear_cfg.gpu = cfg.gpu
eval_linear_cfg.rank = cfg.rank
eval_linear_cfg.world_size = cfg.world_size
eval_linear_cfg.dist_url = cfg.dist_url
eval_linear.main(eval_linear_cfg)
print('STARTING k-NN EVALUATION')
eval_knn_cfg = OmegaConf.load("eval_knn.yaml")
# copy dist parameters
eval_knn_cfg.gpu = cfg.gpu
eval_knn_cfg.rank = cfg.rank
eval_knn_cfg.world_size = cfg.world_size
eval_knn_cfg.dist_url = cfg.dist_url
eval_knn_cfg.timeout = 1800*20
eval_knn.main(eval_knn_cfg)
print('*************STARTING LINEAR EVALUATION: CIFAR10*************')
eval_linear_cfg.dataset = "CIFAR10"
# eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = False
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING LINEAR EVALUATION: CIFAR100*************')
eval_linear_cfg.dataset = "CIFAR100"
# eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = False
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING LINEAR EVALUATION: FOOD101*************')
eval_linear_cfg.dataset = "Food101"
# eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = False
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING LINEAR EVALUATION: Flowers102*************')
eval_linear_cfg.dataset = "Flowers102"
# eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = False
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING LINEAR EVALUATION: Places365*************')
eval_linear_cfg.dataset = "Places365"
# eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = False
eval_linear_cfg.data_path = "/work/dlclarge1/ferreira-simsiam/minsim_experiments/datasets/places365"
eval_linear.main(eval_linear_cfg)
print('*************STARTING LINEAR EVALUATION: iNaturalist (using train_mini)*************')
eval_linear_cfg.dataset = "inat21"
# eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = False
eval_linear_cfg.data_path = "/work/dlclarge1/ferreira-simsiam/minsim_experiments/datasets"
eval_linear.main(eval_linear_cfg)
################## FINE-TUNING ##################
print('*************STARTING FINETUNING: CIFAR10*************')
eval_linear_cfg.dataset = "CIFAR10"
eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = True
eval_linear_cfg.lr = 7.5e-6
eval_linear_cfg.weight_decay = 0.05
eval_linear_cfg.optimizer = "adamw"
eval_linear_cfg.epochs = 300
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING FINETUNING: CIFAR100*************')
eval_linear_cfg.dataset = "CIFAR100"
eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = True
eval_linear_cfg.lr = 5e-6
eval_linear_cfg.weight_decay = 0.05
eval_linear_cfg.optimizer = "adamw"
eval_linear_cfg.epochs = 300
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING FINETUNING: FOOD101*************')
eval_linear_cfg.dataset = "Food101"
eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = True
eval_linear_cfg.lr = 5e-6
eval_linear_cfg.weight_decay = 0.05
eval_linear_cfg.optimizer = "adamw"
eval_linear_cfg.epochs = 300
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING FINETUNING: Flowers102*************')
eval_linear_cfg.dataset = "Flowers102"
eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = True
eval_linear_cfg.lr = 5e-4
eval_linear_cfg.weight_decay = 0.05
eval_linear_cfg.optimizer = "adamw"
eval_linear_cfg.epochs = 300
eval_linear_cfg.data_path = "../datasets"
eval_linear.main(eval_linear_cfg)
print('*************STARTING FINETUNING: Places365*************')
eval_linear_cfg.dataset = "Places365"
eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = True
eval_linear_cfg.lr = 5e-5
eval_linear_cfg.weight_decay = 0.05
eval_linear_cfg.optimizer = "adamw"
eval_linear_cfg.epochs = 100
eval_linear_cfg.data_path = "/work/dlclarge1/ferreira-simsiam/minsim_experiments/datasets/places365"
eval_linear.main(eval_linear_cfg)
print('*************STARTING LINEAR EVAL EVALUATION: iNaturalist (using train_mini)*************')
eval_linear_cfg.dataset = "inat21"
eval_linear_cfg.batch_size = 512
eval_linear_cfg.finetune = True
eval_linear_cfg.lr = 7.5e-5
eval_linear_cfg.weight_decay = 0.05
eval_linear_cfg.epochs = 100
eval_linear_cfg.optimizer = "adamw"
eval_linear_cfg.data_path = "/work/dlclarge1/ferreira-simsiam/minsim_experiments/datasets"
eval_linear.main(eval_linear_cfg)