model_type: null
device: cuda:0
save_dir: null # directory
model_name: null # if none, name will default to model_type. otherwise, will be used to name the folder to save results
seed: 1234
max_threads: 4
load_from_checkpoint: null
# eval_n_seeds: 5

model_args:
  shared_f_init: false # f_init and f_sys are shared
  
data_args:
  path: data/har/processed
  mode: subseq # fullts or subseq
  input_dims: 6
  subseq_size: 128

  # the following data_kwargs are used to downsample and select channels 
  downsample_factor: 1 # downsample factor across time.
  include_channels: all # "all" or list of channels indices (i.e. [0, 1]). useful for testing subset of channels
  p_train: 1 # proportion of train set to use
  p_val: 1 # proportion of val set to use.
  train_stride: 128 # when wrapping fullts into subseqs, how many samples to skip between subseqs
  val_stride: 128 # when wrapping fullts into subseqs, how many samples to skip between subseqs

training_args:
  epochs: 100
  lr: 0.001
  batch_size: 32
  clip_grad_norm: 1
  eval_batch_size: 32 
  standardize_batch: false
  eval_every_n: 2
  log_every_n: 2
  checkpoint_every_n: 25
  save_every_n: 500

encoder_args: # fixed across all models
  norm_last_layer: true
  num_layers: 10
  emb_dim: 320
  hidden_dim: 64
  pool_across_time_mode: max

transfer: false
eval_args:
  do_eval: true
  eval_n_seeds: 5
  plot_tsne_alpha: 0.1
  