New log folder structure

configs/config.yaml

@@ -6,8 +6,6 @@ defaults:
     - experiment: development_baby_unet_cb55_10.yaml
     - hparams_search: null
 
-    - hydra: default.yaml
-
     # enable color logging
     - override hydra/job_logging: colorlog
     - override hydra/hydra_logging: colorlog

configs/experiment/cb55_full_run_unet.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_HisDB_cropped.yaml
     - /loss: crossentropyloss.yaml
@@ -23,6 +24,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "semantic_segmentation_cb55_full_unet"
+
 train: True
 test: True
 predict: False
@@ -34,6 +37,7 @@ trainer:
     min_epochs: 1
     max_epochs: 50
     precision: 16
+    check_val_every_n_epoch: 4
 
 task:
     confusion_matrix_log_every_n_epoch: 10
@@ -62,6 +66,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'cb55-full-unet'
+        name: ${name}
         tags: ["best_model", "USL", "baseline"]
         group: 'baseline'

configs/experiment/cb55_full_run_unet_loss_no_weights.yaml

@@ -0,0 +1,71 @@
+# @package _global_
+
+# to execute this experiment run:
+# python run.py +experiment=exp_example_full
+
+defaults:
+    - /mode: experiment.yaml
+    - /plugins: default.yaml
+    - /task: semantic_segmentation_HisDB_cropped.yaml
+    - /loss: crossentropyloss_no_weight.yaml
+    - /metric: hisdbiou.yaml
+    - /model/backbone: unet_model.yaml
+    - /model/header: identity.yaml
+    - /optimizer: adam.yaml
+    - /callbacks:
+          - check_compatibility.yaml
+          - model_checkpoint.yaml
+    - /logger:
+          - wandb.yaml # set logger here or use command line (e.g. `python run.py logger=wandb`)
+          - csv.yaml
+    - _self_
+
+# we override default configurations with nulls to prevent them from loading at all
+# instead we define all modules and their paths directly in this config,
+# so everything is stored in one place for more readibility
+
+name: "semantic_segmentation_cb55_full_unet_loss_no_weights"
+
+train: True
+test: True
+predict: False
+
+trainer:
+    _target_: pytorch_lightning.Trainer
+    gpus: -1
+    accelerator: 'ddp'
+    min_epochs: 1
+    max_epochs: 50
+    precision: 16
+    check_val_every_n_epoch: 4
+
+task:
+    confusion_matrix_log_every_n_epoch: 10
+    confusion_matrix_val: True
+    confusion_matrix_test: True
+
+datamodule:
+    _target_: src.datamodules.DivaHisDB.datamodule_cropped.DivaHisDBDataModuleCropped
+
+    data_dir: /net/research-hisdoc/datasets/semantic_segmentation/datasets_cropped/CB55
+    crop_size: 256
+    num_workers: 4
+    batch_size: 16
+    shuffle: True
+    drop_last: True
+    data_folder_name: data
+    gt_folder_name: gt
+
+callbacks:
+    model_checkpoint:
+        monitor: "val/hisdbiou"
+        mode: "max"
+        filename: ${checkpoint_folder_name}cb55-full-unet
+#    watch_model:
+#        log_freq: 1000
+
+logger:
+    wandb:
+        name: ${name}
+        tags: ["best_model", "USL", "baseline"]
+        group: 'baseline'

configs/experiment/cb55_select_train15_unet.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_HisDB_cropped.yaml
     - /loss: crossentropyloss.yaml
@@ -23,6 +24,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "semantic_segmentation_cb55_train15_unet"
+
 train: True
 test: True
 predict: False
@@ -63,6 +66,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'cb55-select-train15-unet'
+        name: ${name}
         tags: ["best_model", "USL", "baseline"]
         group: 'baseline'

configs/experiment/cb55_select_train1_val1_unet.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_HisDB_cropped.yaml
     - /loss: crossentropyloss.yaml
@@ -23,6 +24,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "semantic_segmentation_cb55_train1_val1_unet"
+
 train: True
 test: True
 predict: False
@@ -64,6 +67,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'cb55-select-train1-val1-unet'
+        name: ${name}
         tags: ["best_model", "USL", "baseline"]
         group: 'baseline'

configs/experiment/dev_rgb_full_page.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_RGB.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/dev_rgb_full_page_predict.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_RGB.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/dev_rolf_format.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode:            development.yaml
     - /plugins:         default.yaml
     - /task:            semantic_segmentation_RGB.yaml
     - /datamodule:      rolf_format_dev.yaml

configs/experiment/dev_rolf_format_prediction.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode:            development.yaml
     - /plugins:         default.yaml
     - /task:            semantic_segmentation_RGB.yaml
     - /datamodule:      rolf_format_dev_prediction.yaml

configs/experiment/dev_rotnet_cnn_basic_cb55_10.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: classification.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/dev_rotnet_pt_resnet18_cb55_10_segmentation.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_HisDB_cropped.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/dev_rotnet_resnet18_cb55_10.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: classification.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/dev_rotnet_resnet50_cb55_10.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: classification.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/development_baby_unet_cb55_10.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_HisDB_cropped.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/development_baby_unet_rgb_data.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: development.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_RGB_cropped.yaml
     - /loss: crossentropyloss.yaml

configs/experiment/rotnet_resnet18_cb55_full.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: classification.yaml
     - /loss: crossentropyloss.yaml
@@ -24,6 +25,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "rotnet_cb55_full_resnet18"
+
 train: True
 test: False
 predict: False
@@ -67,6 +70,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'rotnet-resnet18-cb55'
+        name: ${name}
         tags: [ "best_model", "USL"]
         group: 'rotnet-baseline'

configs/experiment/rotnet_resnet18_cb55_train10_last.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: classification.yaml
     - /loss: crossentropyloss.yaml
@@ -24,6 +25,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "rotnet_cb55_train10_resnet18"
+
 train: True
 test: False
 predict: False
@@ -78,6 +81,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'rotnet-resnet18-cb55-last10-train'
+        name: ${name}
         tags: [ "best_model", "USL"]
         group: 'rotnet-baseline'

configs/experiment/rotnet_resnet18_cb55_train19_last.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: classification.yaml
     - /loss: crossentropyloss.yaml
@@ -24,6 +25,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "rotnet_cb55_train19_resnet18"
+
 train: True
 test: False
 predict: False
@@ -87,6 +90,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'rotnet-resnet18-cb55-last19-train'
+        name: ${name}
         tags: [ "best_model", "USL"]
         group: 'rotnet-baseline'

configs/experiment/synthetic_baby_unet_layoutD_gtD.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_RGB_cropped.yaml
     - /loss: crossentropyloss.yaml
@@ -24,6 +25,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "semantic_segmentation_synthetic_layoutD_gtD_baby_unet"
+
 train: True
 test: True
 predict: False
@@ -64,6 +67,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'synthetic-baby-unet-layoutD-gtD'
+        name: ${name}
         tags: [ "best_model", "synthetic", "layoutD", "gtD", "Rolf" ]
         group: 'synthetic'

configs/experiment/synthetic_baby_unet_layoutD_gtD_rolf_format.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode:            experiment.yaml
     - /plugins:         default.yaml
     - /task:            semantic_segmentation_RGB.yaml
     - /datamodule:      rolf_format_layoutD_gtD.yaml
@@ -25,6 +26,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "semantic_segmentation_synthetic_fullpage_layoutD_gtD_baby_unet"
+
 train: True
 test: True
 predict: False
@@ -53,6 +56,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'synthetic-baby-unet-layoutD-gtD-rolf-format'
+        name: ${name}
         tags: [ "best_model", "synthetic", "RolfFormat" ]
         group: 'synthetic'

configs/experiment/synthetic_baby_unet_layoutR_gtD.yaml

@@ -4,6 +4,7 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
+    - /mode: experiment.yaml
     - /plugins: default.yaml
     - /task: semantic_segmentation_RGB_cropped.yaml
     - /loss: crossentropyloss.yaml
@@ -24,6 +25,8 @@ defaults:
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+name: "semantic_segmentation_synthetic_layoutR_gtD_baby_unet"
+
 train: True
 test: True
 predict: False
@@ -64,6 +67,6 @@ callbacks:
 
 logger:
     wandb:
-        name: 'synthetic-baby-unet-layoutR-gtD'
+        name: ${name}
         tags: [ "best_model", "synthetic", "layoutR", "gtD", "Rolf" ]
         group: 'synthetic'