method: grid
parameters:
  batch_norm:
    value: "false"
  batch_size:
    value: 8192
  dropout:
    values:
      - 0
  dry_load:
    value: "false"
  dummy_repetition:
    values:
      - 0
      - 1
      - 2
  kge:
    value: stargraph
  l1_reg:
    value: 5e-07
  layer_norm_inner_layers:
    values:
      - "false"
  learning_rate:
    value: 0.001
  max_train_drugs:
    value: 2
  meta_batch_size:
    value: 4
  meta_learning_rate:
    value: 1
  meta_learning_rate_final_ratio:
    value: 0.1
  min_pos_label:
    value: 50
  model_dim:
    value: 256
  n_iterations:
    value: 1000
  n_layers:
    values:
      - 6
  caml_k:
    value: 50
  residual:
    value: "true"
  set_task_embeddings_to_random:
    value: 0
  step:
    value: tau
  task_embedding_aggregation:
    value: sum
  task_embedding_config:
    values:
      - late_concat_layernorm
      - late_concat
      - early_concat
  task_sample_weighting:
    value: "false"
  use_lr_scheduler:
    value: "false"
  use_random_sampler:
    value: "false"
  use_task_embeddings:
    value: "true"
  val_interval:
    value: 10
  val_test_location:
    value: metalearn/splits/new_splits_final.csv
  weight_decay:
    value: 0.005
program: metalearn/train_caml.py
