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Add CHECKPOINT_TYPE env variable to configs #726

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merged 3 commits into from
Dec 6, 2024
Merged

Add CHECKPOINT_TYPE env variable to configs #726

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30287c3
add checkpoint_type argument to Trainer
nkaenzig Dec 5, 2024
bfd5cd1
added checkpoint_type setting to yaml configs
nkaenzig Dec 5, 2024
c603659
update docs
nkaenzig Dec 5, 2024
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3 changes: 2 additions & 1 deletion configs/vision/pathology/offline/classification/bach.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand All @@ -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
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1 change: 1 addition & 0 deletions configs/vision/pathology/offline/classification/camelyon16.yaml
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Expand Up @@ -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
Expand Down
1 change: 1 addition & 0 deletions configs/vision/pathology/offline/classification/camelyon16_small.yaml
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Expand Up @@ -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
Expand Down
3 changes: 2 additions & 1 deletion configs/vision/pathology/offline/classification/crc.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
3 changes: 2 additions & 1 deletion configs/vision/pathology/offline/classification/mhist.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
1 change: 1 addition & 0 deletions configs/vision/pathology/offline/classification/panda.yaml
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Expand Up @@ -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
Expand Down
1 change: 1 addition & 0 deletions configs/vision/pathology/offline/classification/panda_small.yaml
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Expand Up @@ -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
Expand Down
3 changes: 2 additions & 1 deletion configs/vision/pathology/offline/classification/patch_camelyon.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
5 changes: 3 additions & 2 deletions configs/vision/pathology/offline/segmentation/bcss.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
5 changes: 3 additions & 2 deletions configs/vision/pathology/offline/segmentation/consep.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
3 changes: 2 additions & 1 deletion configs/vision/pathology/offline/segmentation/monusac.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
3 changes: 2 additions & 1 deletion configs/vision/pathology/offline/segmentation/total_segmentator_2d.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
4 changes: 3 additions & 1 deletion configs/vision/pathology/online/classification/bach.yaml
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Expand Up @@ -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
Expand All @@ -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:
Expand Down
4 changes: 3 additions & 1 deletion configs/vision/pathology/online/classification/crc.yaml
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Expand Up @@ -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
Expand All @@ -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:
Expand Down
4 changes: 3 additions & 1 deletion configs/vision/pathology/online/classification/mhist.yaml
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Expand Up @@ -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
Expand All @@ -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:
Expand Down
4 changes: 3 additions & 1 deletion configs/vision/pathology/online/classification/patch_camelyon.yaml
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Expand Up @@ -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
Expand All @@ -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:
Expand Down
5 changes: 3 additions & 2 deletions configs/vision/pathology/online/segmentation/bcss.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand All @@ -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:
Expand Down
5 changes: 3 additions & 2 deletions configs/vision/pathology/online/segmentation/consep.yaml
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Expand Up @@ -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
Expand All @@ -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:
Expand Down
5 changes: 3 additions & 2 deletions configs/vision/pathology/online/segmentation/monusac.yaml
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Expand Up @@ -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
Expand All @@ -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:
Expand Down
5 changes: 3 additions & 2 deletions configs/vision/pathology/online/segmentation/total_segmentator_2d.yaml
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Expand Up @@ -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
Expand All @@ -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:
Expand Down
4 changes: 2 additions & 2 deletions configs/vision/radiology/offline/segmentation/lits.yaml
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Expand Up @@ -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:
Expand All @@ -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
Expand Down
5 changes: 3 additions & 2 deletions configs/vision/radiology/offline/segmentation/lits_balanced.yaml
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Expand Up @@ -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
Expand All @@ -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
Expand Down
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