config.yaml

defaults:
  - hydra/job_logging: colorlog
  - hydra/hydra_logging: colorlog
  - experiment: imagenet_split_1
  - simulation: amt_structured_noise
  - learner_method: efficient_annotation # lean, improved_lean, efficient_annotation, online_ds


hydra:
  run:
    dir: ./outputs/${now:%Y-%m-%d}-${now:%H-%M-%S}

exp_name: test
seed: 123
n_jobs: 2
early_stop: false

aggregator: 
  algo: bayes # mj bayes


optimizer:
  max_em_steps: 10
  likelihood_epsilon: 0.001


learner:
  features: byol_r50-e3b0c442.pth_feat1.npy
  risk_thres: 0.1
  n_hidden_layer: 1
  hidden_size: 64
  batch_size: 1024
  max_epochs: 300
  lr_ratio: 0.0001
  weight_decay: 0.001

  algo: dummy
  calibrate: temperature
  semi_supervised: none
  early_stop_scope: local
  prototype_as_val: true

  mixmatch:
    mu: 5
    alpha: 0.75
    mixmatch_w: 75
  

sampler:
  algo: random # random, greedy_task_assignment
  max_annotation_per_example: 3
  max_annotation_per_worker: 2000