File size: 2,773 Bytes
abd2a81 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
{
"run_name": "mapping_dataset.fcn50",
"data_dir_candidates": [
"/local/shared/data", // try cluster local node first
"/data/titane/user/nigirard/data", // Try cluster /data directory
"~/data", // In home directory (docker)
"/data" // In landsat's /data volume (docker)
],
"data_root_partial_dirpath": "mapping_challenge_dataset",
"dataset_params": {
"small": false
},
"num_workers": 10,
"data_split_params": {
"seed": 0, // Change this to change the random splitting of data in train/val/test
"train_fraction": 0.75,
"val_fraction": 0.25 // test_fraction is the rest
},
"data_aug_params": {
"enable": true,
"vflip": true,
"rotate": true,
"color_jitter": true,
"device": "cuda"
},
"device": "cuda", // Only has effects when mode is val or test. When mode is train, always use CUDA
"use_amp": true, // Automatic Mixed Precision switch
"backbone_params": {
"name": "fcn50",
"input_features": 3,
"features": 256,
"pretrained": false
},
"compute_seg": true,
"compute_crossfield": true,
"seg_params": {
"compute_interior": true,
"compute_edge": true,
"compute_vertex": false
},
"loss_params": {
"multiloss": {
"normalization_params": {
"min_samples": 10, // Per GPU
"max_samples": 1000 // Per GPU
},
"coefs": {
"seg_interior": 1,
"seg_edge": 1,
"seg_vertex": 0,
"crossfield_align": 1,
"crossfield_align90": 0.2,
"crossfield_smooth": 0.2,
"seg_interior_crossfield": 0.2,
"seg_edge_crossfield": 0.2,
"seg_edge_interior": 0.2
}
},
"seg_loss_params": { // https://github.com/neptune-ai/open-solution-mapping-challenge/blob/master/neptune.yaml
"bce_coef": 1.0,
"dice_coef": 0.2,
"w0": 50, // From original U-Net paper: distance weight to increase loss between objects
"sigma": 10 // From original U-Net paper: distance weight to increase loss between objects
}
},
"batch_size": 16, // Batch size per GPU. The effective batch size is effective_batch_size=world_size*batch_size
"base_lr": 1e-4, // Will be multiplied by the effective_batch_size=world_size*batch_size.
"max_lr": 1e-2, // Maximum learning rate
"warmup_epochs": 1, // Number of epochs for warmup (learning rate starts at lr*warmup_factor and gradually increases to lr)
"warmup_factor": 1e-3,
"weight_decay": 0,
"dropout_keep_prob": 1.0, // Not used for now
"max_epoch": 25,
"log_steps": 50,
"checkpoint_epoch": 1,
"checkpoints_to_keep": 10, // outputs
"logs_dirname": "logs",
"save_input_output": false,
"log_input_output": false,
"checkpoints_dirname": "checkpoints",
"eval_dirname": "eval"
}
|