configs/configs.py

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
  }