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import os
import torch
root = "/content/drive/MyDrive"
mae_config={
"lr":1e-4,
"warmup":5,
"weight_decay":5e-4,
"num_epochs":200,
"num_classes":14,
"zip_path":os.path.join(root,"CheXpert-v1.0-small","chexpert.zip"),
"resume":os.path.join(root,"CheXpert-v1.0-small","maecheckpoints","best_mae.pth"),
"logdir":os.path.join(root,"CheXpert-v1.0-small","maelogs"),
"checkpoints":os.path.join(root,"CheXpert-v1.0-small","maecheckpoints"),
"datadir":root,
"lmdb":os.path.join(root,"CheXpert-v1.0-small","lmdb"),
"csv":os.path.join(root,"CheXpert-v1.0-small","train.csv"),
"batch_size":96,
"device":torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu"),
"accumulation":1,
"dirsToMake":[os.path.join(root,"CheXpert-v1.0-small","maecheckpoints"),os.path.join(root,"CheXpert-v1.0-small","maelogs")],
"train_csv":os.path.join(root,"CheXpert-v1.0-small","train_ready.csv"),
"val_csv":os.path.join(root,"CheXpert-v1.0-small","val_ready.csv"),
"test_csv":os.path.join(root,"CheXpert-v1.0-small","test_ready.csv")
,"channels":1,"mask_ratio":0.75,"dropout":0.25,"img_size":384,"encoder_dim":768,
"mlp_dim":3072,"decoder_dim":512,"encoder_depth":12,"encoder_head":8,"decoder_depth":8,
"decoder_head":8,"patch_size":16
} |