But the generated config file shows that these parameters are still default values, such as
{  image_size: null
  train_batch_size: 32
  eval_batch_size: 32
 backbone: resnet18}


# anomalib==1.1.0dev
seed_everything: true
trainer:
  accelerator: auto
  strategy: auto
  devices: 1
  num_nodes: 1
  precision: null
  logger: null
  callbacks: null
  fast_dev_run: false
  max_epochs: null
  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: null
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: null
  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: 0
normalization:
  normalization_method: MIN_MAX
task: SEGMENTATION
metrics:
  image:
  - F1Score
  - AUROC
  pixel: null
  threshold:
    class_path: anomalib.metrics.F1AdaptiveThreshold
    init_args:
      default_value: 0.5
      thresholds: null
      ignore_index: null
      validate_args: true
      compute_on_cpu: false
      dist_sync_on_step: false
      sync_on_compute: true
      compute_with_cache: true
logging:
  log_graph: false
default_root_dir: results
ckpt_path: null
model:
  class_path: anomalib.models.Padim
  init_args:
    backbone: resnet18
    layers:
    - layer1
    - layer2
    - layer3
    pre_trained: true
    n_features: null
data:
  class_path: anomalib.data.MVTec
  init_args:
    root: datasets\MVTec
    category: bottle
    train_batch_size: 32
    eval_batch_size: 32
    num_workers: 8
    image_size: null
    transform: null
    train_transform: null
    eval_transform: null
    test_split_mode: FROM_DIR
    test_split_ratio: 0.2
    val_split_mode: SAME_AS_TEST
    val_split_ratio: 0.5
    seed: null