config_deep.yaml

# pytorch_lightning==2.0.2
seed_everything: true
trainer:
  accelerator: cuda
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: 32-true
  logger: null
  callbacks: null
  fast_dev_run: false
  max_epochs: 100
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 18
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: 1
  enable_checkpointing: null
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: null
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: true
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins: null
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 1
  default_root_dir: null
  logger: 
    class_path: CSVLogger
    init_args:
      save_dir: "lightning_logs"
      name: "lightning_logs"
      flush_logs_every_n_steps: 1
model:
  layers:
  - 784
  - 256
  - 10
  tau_mem: 20.0
  tau_stdp: 10.0
  controller_rate: 0.1
  max_val_steps: 10
  max_train_steps: 100
  positive_control: 0.1
  alpha_stdp: 1.0
  batch_size: 1000
data:
  data_dir: data/
  batch_size: 1000
ckpt_path: null
optimizer:
  class_path: torch.optim.Adam
  init_args:
    betas:
      - 0.9
      - 0.9
    lr: 1e-3
    maximize: false
    foreach: null
    differentiable: false