added checkpoint_type setting to yaml configs

kaiko-ai · Dec 5, 2024 · bfd5cd1 · bfd5cd1
1 parent 30287c3
commit bfd5cd1
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Showing 27 changed files with 58 additions and 28 deletions.
diff --git a/configs/vision/pathology/offline/classification/bach.yaml b/configs/vision/pathology/offline/classification/bach.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/bach}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -23,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 400
+          patience: ${oc.env:PATIENCE, 400}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.ClassificationEmbeddingsWriter

diff --git a/configs/vision/pathology/offline/classification/camelyon16.yaml b/configs/vision/pathology/offline/classification/camelyon16.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/camelyon16}
     max_epochs: &MAX_EPOCHS ${oc.env:MAX_EPOCHS, 100}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar

diff --git a/configs/vision/pathology/offline/classification/camelyon16_small.yaml b/configs/vision/pathology/offline/classification/camelyon16_small.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/camelyon16}
     max_epochs: &MAX_EPOCHS ${oc.env:MAX_EPOCHS, 100}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar

diff --git a/configs/vision/pathology/offline/classification/crc.yaml b/configs/vision/pathology/offline/classification/crc.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/crc}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -23,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 24
+          patience: ${oc.env:PATIENCE, 24}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.ClassificationEmbeddingsWriter

diff --git a/configs/vision/pathology/offline/classification/mhist.yaml b/configs/vision/pathology/offline/classification/mhist.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/mhist}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -23,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 70
+          patience: ${oc.env:PATIENCE, 70}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.ClassificationEmbeddingsWriter

diff --git a/configs/vision/pathology/offline/classification/panda.yaml b/configs/vision/pathology/offline/classification/panda.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/panda}
     max_epochs: &MAX_EPOCHS ${oc.env:MAX_EPOCHS, 49}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar

diff --git a/configs/vision/pathology/offline/classification/panda_small.yaml b/configs/vision/pathology/offline/classification/panda_small.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/panda}
     max_epochs: &MAX_EPOCHS ${oc.env:MAX_EPOCHS, 49}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar

diff --git a/configs/vision/pathology/offline/classification/patch_camelyon.yaml b/configs/vision/pathology/offline/classification/patch_camelyon.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/offline/patch_camelyon}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -23,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 9
+          patience: ${oc.env:PATIENCE, 9}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.ClassificationEmbeddingsWriter

diff --git a/configs/vision/pathology/offline/segmentation/bcss.yaml b/configs/vision/pathology/offline/segmentation/bcss.yaml
@@ -2,10 +2,11 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224}/bcss}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 2000}
     log_every_n_steps: 6
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -25,7 +26,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 8
+          patience: ${oc.env:PATIENCE, 8}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.SegmentationEmbeddingsWriter

diff --git a/configs/vision/pathology/offline/segmentation/consep.yaml b/configs/vision/pathology/offline/segmentation/consep.yaml
@@ -2,10 +2,11 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/consep}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 2000}
     log_every_n_steps: 6
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -25,7 +26,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 34
+          patience: ${oc.env:PATIENCE, 34}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.SegmentationEmbeddingsWriter

diff --git a/configs/vision/pathology/offline/segmentation/monusac.yaml b/configs/vision/pathology/offline/segmentation/monusac.yaml
@@ -6,6 +6,7 @@ trainer:
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/monusac}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 2000}
     log_every_n_steps: 6
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -28,7 +29,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 50
+          patience: ${oc.env:PATIENCE, 50}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.SegmentationEmbeddingsWriter

diff --git a/configs/vision/pathology/offline/segmentation/total_segmentator_2d.yaml b/configs/vision/pathology/offline/segmentation/total_segmentator_2d.yaml
@@ -5,6 +5,7 @@ trainer:
     n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/total_segmentator_2d}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 20000}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -25,7 +26,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 5
+          patience: ${oc.env:PATIENCE, 5}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.SegmentationEmbeddingsWriter

diff --git a/configs/vision/pathology/online/classification/bach.yaml b/configs/vision/pathology/online/classification/bach.yaml
@@ -2,8 +2,10 @@
 trainer:
   class_path: eva.Trainer
   init_args:
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/online/bach}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -22,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 400
+          patience: ${oc.env:PATIENCE, 400}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/pathology/online/classification/crc.yaml b/configs/vision/pathology/online/classification/crc.yaml
@@ -2,8 +2,10 @@
 trainer:
   class_path: eva.Trainer
   init_args:
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/online/crc}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -22,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 24
+          patience: ${oc.env:PATIENCE, 24}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/pathology/online/classification/mhist.yaml b/configs/vision/pathology/online/classification/mhist.yaml
@@ -2,8 +2,10 @@
 trainer:
   class_path: eva.Trainer
   init_args:
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &LIGHTNING_ROOT ${oc.env:LIGHTNING_ROOT, logs/dino_vits16/online/mhist}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -22,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 70
+          patience: ${oc.env:PATIENCE, 70}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/pathology/online/classification/patch_camelyon.yaml b/configs/vision/pathology/online/classification/patch_camelyon.yaml
@@ -2,8 +2,10 @@
 trainer:
   class_path: eva.Trainer
   init_args:
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, dino_vits16}/online/patch_camelyon}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -22,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 9
+          patience: ${oc.env:PATIENCE, 9}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/pathology/online/segmentation/bcss.yaml b/configs/vision/pathology/online/segmentation/bcss.yaml
@@ -2,10 +2,11 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224}/bcss}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 513}
     log_every_n_steps: 6
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -26,7 +27,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 100
+          patience: ${oc.env:PATIENCE, 100}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/pathology/online/segmentation/consep.yaml b/configs/vision/pathology/online/segmentation/consep.yaml
@@ -2,10 +2,11 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/consep}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 2000}
     log_every_n_steps: 6
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -26,7 +27,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 34
+          patience: ${oc.env:PATIENCE, 34}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/pathology/online/segmentation/monusac.yaml b/configs/vision/pathology/online/segmentation/monusac.yaml
@@ -2,10 +2,11 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/monusac}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 2000}
     log_every_n_steps: 6
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -26,7 +27,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 50
+          patience: ${oc.env:PATIENCE, 50}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/pathology/online/segmentation/total_segmentator_2d.yaml b/configs/vision/pathology/online/segmentation/total_segmentator_2d.yaml
@@ -2,9 +2,10 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/total_segmentator_2d}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 20000}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -25,7 +26,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 5
+          patience: ${oc.env:PATIENCE, 5}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
     logger:

diff --git a/configs/vision/radiology/offline/segmentation/lits.yaml b/configs/vision/radiology/offline/segmentation/lits.yaml
@@ -2,7 +2,7 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/lits}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 500000}
     callbacks:
@@ -24,7 +24,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 100
+          patience: ${oc.env:PATIENCE, 100}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.SegmentationEmbeddingsWriter

diff --git a/configs/vision/radiology/offline/segmentation/lits_balanced.yaml b/configs/vision/radiology/offline/segmentation/lits_balanced.yaml
@@ -2,9 +2,10 @@
 trainer:
   class_path: eva.Trainer
   init_args:
-    n_runs: &N_RUNS ${oc.env:N_RUNS, 1}
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
     default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, vit_small_patch16_224_dino}/lits_balanced}
     max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 500000}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
     callbacks:
       - class_path: eva.callbacks.ConfigurationLogger
       - class_path: lightning.pytorch.callbacks.TQDMProgressBar
@@ -24,7 +25,7 @@ trainer:
       - class_path: lightning.pytorch.callbacks.EarlyStopping
         init_args:
           min_delta: 0
-          patience: 100
+          patience: ${oc.env:PATIENCE, 100}
           monitor: *MONITOR_METRIC
           mode: *MONITOR_METRIC_MODE
       - class_path: eva.callbacks.SegmentationEmbeddingsWriter