Simplified example

configs/resnet_model.yaml

@@ -10,10 +10,6 @@ model:
       inputs:
         - ResNet
 
-    - name: SegmentationHead
-      inputs:
-        - ResNet
-
   losses:
     - name: CrossEntropyLoss
       attached_to: ClassificationHead
@@ -23,100 +19,30 @@ model:
       is_main_metric: true
       attached_to: ClassificationHead
 
-tracker:
-  project_name: coco_test
-  save_directory: output
-  is_tensorboard: True
-  is_wandb: False
-  wandb_entity: luxonis
-  is_mlflow: False
-
 dataset:
   name: coco_test
-  train_view: train
-  val_view: val
-  test_view: test
 
 trainer:
-  accelerator: auto
-  devices: auto
-  strategy: auto
-
-  num_sanity_val_steps: 1
-  profiler: null
-  verbose: True
   batch_size: 4
-  accumulate_grad_batches: 1
-  epochs: &epochs 1
-  num_workers: 8
-  train_metrics_interval: -1
-  validation_interval: 1
+  epochs: &epochs 200
+  num_workers: 4
+  validation_interval: 10
   num_log_images: 8
-  skip_last_batch: True
-  main_head_index: 0
-  log_sub_losses: True
-  save_top_k: 3
 
   preprocessing:
-    train_image_size: [&height 256, &width 320]
+    train_image_size: [&height 224, &width 224]
     keep_aspect_ratio: False
-    train_rgb: True
     normalize:
       active: True
-    augmentations:
-      - name: Defocus
-        params:
-          p: 0.1
-      - name: Sharpen
-        params:
-          p: 0.1
-      - name: Flip
-      - name: RandomRotate90
-      - name: Mosaic4
-        params:
-          out_width: *width
-          out_height: *height
 
   callbacks:
-    - name: LearningRateMonitor
-      params:
-        logging_interval: step
-    - name: MetadataLogger
-      params:
-        hyperparams: ["trainer.epochs", trainer.batch_size]
-    - name: EarlyStopping
-      params:
-        patience: 3
-        monitor: val/loss
-        mode: min
-        verbose: true
-    - name: DeviceStatsMonitor
     - name: ExportOnTrainEnd
     - name: TestOnTrainEnd
 
   optimizer:
     name: SGD
     params:
       lr: 0.02
-      momentum: 0.937
-      nesterov: True
-      weight_decay: 0.0005
 
   scheduler:
-    name: CosineAnnealingLR
-    params:
-      T_max: *epochs
-      eta_min: 0
-
-exporter:
-  onnx:
-    opset_version: 11
-  blobconverter:
-    active: True
-    shaves: 8
-
-tuner:
-  params:
-    trainer.optimizer.name_categorical: ["Adam", "SGD"]
-    trainer.optimizer.params.lr_float: [0.0001, 0.001]
-    trainer.batch_size_int: [4, 16, 4]
+    name: ConstantLR