eval.yaml

num_workers: 32
precision: float32
fine_tune: false
output_path: ./output
tlt_wf_path: ./transfer-learning/workflows/vision_anomaly_detection
dataset:
  root_dir: ./data
  category_type: all
  batch_size: 32
  image_size: 224
model:
  name: resnet50
  layer: layer3
  pool: 2
  feature_extractor: simsiam
simsiam:
  batch_size: 64
  epochs: 2
  optim: sgd
  model_path: ./output
  ckpt: true
  initial_ckpt: null
cutpaste:
  cutpaste_type: 3way
  head_layer: 2
  freeze_resnet: 20
  batch_size: 64
  epochs: 2
  optim: sgd
  model_path: ./output
  ckpt: true
pca:
  pca_thresholds: 0.99