program: metalearn/train_caml.py
method: grid
metric:
  goal: maximize
  name: "best_Mean Val rate @ 0.998_value"

parameters:
  max_train_drugs:
    values: [1] ## add 4
    
  meta_batch_size:
    values: [1]

  num_como_layers:
    values: [2]

  num_covariates_layer:
    values: [2]

  num_propensity_layers:
    values: [2]

  num_treatment_layer:
    values: [6]

  pro_dropout:
    values: [0.1]

  l1_reg:
    values: [1e-7]

  dim_output:
    values: [256]

  dim_hidden_treatment:
    values: [256]

  dim_hidden_covariates:
    values: [128]

  dim_hidden_como:
    values: [256]

  dim_hidden_propensity:
    values: [32]

  learning_rate:
    values: [0.0001]

  lr:
    values: [0.003]

  pro_lr:
    values: [0.001]

  sin_weight_decay:
    values: [0]

  pro_weight_decay:
    values: [0.005]

  gnn_weight_decay:
    values: [0.005]

  caml_k:
    values: [1]

  deterministic_sample:
    values: ["false"]

  all_tasks_baseline:
    values: ["false"]

  task_sample_weighting:
    values: ["enable"]

  sin_learner:
    values: ["true"]

  task_embedding_config:
    values: ["early_concat"]

  use_task_embeddings:
    values: ["true"]

  step:
    values: ["y0"]

  n_iterations:
    values: [10000]

  val_interval:
    values: [50]

  sin_learner_stage1_loc:
    values: ['/home/anon/ehr-drug-sides/model_outputs/ehr_sin_stage1_model/model_500.pt']

  dummy_repetition:
    values: [0,1,2,3,4,5,6,7]

