healnet/sweep.yaml at main · konst-int-i/healnet · GitHub

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method: bayes
metric:
  goal: minimize
  name: train_loss
parameters:
  clf.n_classes:
    value: 4
  data.level:
    value: 3
  data_path:
    value: /net/archive/export/tcga
  gdc_client:
    value: /home/kh701/gdc-client
  log_path:
    value: /home/kh701/pycharm/x-perceiver/logs
  model.output_dims:
    value: 4
  model_params.class_weights:
    values:
      - "True"
      - "False"
  model_params.output_dims:
    value: 4
  model_params.weight_decay:
    distribution: uniform
    min: 0
    max: 0.001
  model_params.num_freq_bands:
    distribution: int_uniform
    min: 2
    max: 8
  model_params.depth:
    distribution: int_uniform
    min: 1
    max: 4
  model_params.max_freq:
    distribution: int_uniform
    min: 2.
    max: 8.
  model_params.num_latents:
    values:
      - 4
      - 16
      - 32
      - 64
  model_params.latent_dim:
    values:
      - 4
      - 16
      - 32
      - 64
  model_params.attn_dropout:
    distribution: uniform
    min: 0
    max: 0.9
  model_params.ff_dropout:
    distribution: uniform
    min: 0
    max: 0.9
  optimizer.lr:
    distribution: uniform
    max: 0.002
    min: 0.0005
  optimizer.max_lr:
    value: 0.002
  optimizer.momentum:
    distribution: uniform
    max: 0.9
    min: 0.0
  seed:
    value: 42
  survival.loss:
    value: nll
  task:
    value: classification
  tcga_path:
    value: /net/archive/export/tcga/tcga
  train_loop.batch_size:
    value: 4
  train_loop.checkpoint_interval:
    value: 20
  train_loop.epochs:
    value: 20
  train_loop.eval_interval:
    value: 10
  wandb:
    value: "True"
program: x_perceiver/main.py