hyp_sweep.yaml

program: train_mmnist.py
method: random
name: general_search_mmnist_slot_rim
metric:
  name: Loss.train loss
  goal: minimize
early_terminate:
  type: hyperband 
  min_iter: 5 # how many times called wandb.log // (iter-15)*test_frequency = epochs
  eta: 1 # check if training exploded every 20 epochs (if test_freq=10)
parameters:
  experiment_name:
    value: "MMNIST_slotrim_sweep"
  cfg_json: 
    value: "configs/rim/rim_slot.json"
  core: 
    value: "RIM"
  epochs:
    value: 200
  save_frequency: 
    value: 50
  batch_size:
    value: 32
  lr:
    distribution: "log_uniform"
    min: -9.57 # log(0.00007)
    max: -4.962 # log(0.007)
  input_size: 
    distribution: "q_log_uniform"
    min: 3.46 # log(32)
    max: 4.86 # log(128)
  hidden_size:
    values: [50, 100, 150]
  num_hidden:
    values: [3, 6, 10]
  k:
    values: [2, 4, 6]
  num_input_heads:
    values: [1, 2]
  input_value_size:
    values: [100, 200, 400]
  num_comm_heads:
    values: [1, 2, 4]
  slot_size:
    values: [64, 100, 256]
  num_slots:
    values: [3, 6]
  num_iterations_slot:
    values: [3, 5]