config.py
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config = {
"debug" : False,
"seed" : 0,
"wandb.use" : False,
"wandb.run_id" : None,
"project" : "brain-age",
"result_folder" : "result",
"mode" : ["test", "train"],
"data.name" : "brain_age",
"data.root_path" : "/content/drive/MyDrive/2d-slice-set-networks-for-brain-age-master/data",
"data.train_csv" : "data/train0609.csv",
"data.test_csv" : "data/test0609.csv",
"data.valid_csv" : "data/valid0609.csv",
"data.train_num_sample" : -1,
"data.frame_keep_style" : "random",
"data.frame_keep_fraction" : 1,
"data.frame_dim" : 1,
"data.impute" : "drop",
"model.name" : "regression",
"model.arch.file" : "src/arch/brain_age_3d.py",
"model.arch.lstm_feat_dim" : 2,
"model.arch.lstm_latent_dim" : 128,
"model.arch.attn_dim" : 32,
"model.arch.attn_num_heads" : 1,
"model.arch.attn_drop" : False,
"model.arch.agg_fn" : "attention",
"train.batch_size" : 8,
"train.patience" : 100,
"train.max_epoch" : 100,
"train.optimizer" : "adam",
"train.lr" : 1e-4,
"train.weight_decay" : 1e-4,
"train.save_strategy" : ["best", "last"],
"train.log_every" : 100,
"train.stopping_criteria" : "loss",
"train.stopping_criteria_direction": "lower",
"train.gradient_norm_clip" : -1,
"test.batch_size" : 8,
"test.eval_model" : "best",
}