program: metalearn/train_caml_lincs.py
method: random
metric:
  goal: minimize
  name: "best_val_mse_diff_20_value"

parameters:
  meta_batch_size:
    values: [1]

  batch_size:
    values: [20] ## add 4

  num_como_layers:
    values: [2,4,6]

  num_covariates_layer:
    values: [2,4,6]

  num_propensity_layers:
    values: [2,4,6]

  num_treatment_layer:
    values: [2,4,6]

  pro_dropout:
    values: [0, 0.1]

  dropout:
    values: [0, 0.1]

  l1_reg:
    values: [0, 1e-7, 5e-7]

  dim_output:
    values: [128, 256]

  dim_hidden_treatment:
    values: [128, 256]

  dim_hidden_covariates:
    values: [128, 256]

  meta_learning_rate:
    values: [0.1,0.5,0.9]

  dim_hidden_como:
    values: [128, 256]

  dim_hidden_propensity:
    values: [16, 32, 64, 128]

  model_dim:
    values: [512, 1024]

  learning_rate:
    values: [0.003, 0.001, 0.0003, 0.0001]

  lr:
    values: [0.003, 0.001, 0.0003, 0.0001]

  pro_lr:
    values: [0.003, 0.001, 0.0003, 0.0001]

  weight_decay:
    values: [0.1]

  sin_weight_decay:
    values: [0.0, 0.005]

  pro_weight_decay:
    values: [0.0, 0.005]

  gnn_weight_decay:
    values: [0.0, 0.005]

  caml_k:
    values: [1,2,3]

  sin_learner:
    values: ["true"]

  task_embedding_config:
    values: ["early_concat"]

  use_task_embeddings:
    values: ["true"]

  step:
    values: ["tau"]

  n_iterations:
    values: [50000]

  val_interval:
    values: [50]

  sin_learner_stage1_loc:
    values: ['/dfs/user/anon/ehr-drug-sides/model_outputs/lincs/wzs34cwy/model_13900.pt']

