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Use inference_mode for evaluation methods #18

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Merged
JeremieGince merged 2 commits into from
Feb 13, 2026
Merged

Use inference_mode for evaluation methods #18

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ce5e357
Use inference_mode for evaluation methods
JeremieGince Feb 13, 2026
4f9df9f
Reorder imports in lightning_pipeline.py
JeremieGince Feb 13, 2026
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4 changes: 4 additions & 0 deletions src/matchcake_opt/tr_pipeline/lightning_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
from lightning.pytorch.callbacks.callback import Callback
from lightning.pytorch.loggers import TensorBoardLogger
from lightning.pytorch.profilers import SimpleProfiler
from torch.autograd import inference_mode

from ..datamodules.datamodule import DataModule
from ..modules.base_model import BaseModel
Expand Down Expand Up @@ -124,6 +125,7 @@ def run(self) -> Dict[str, Any]:
val_metrics: Dict[str, Any] = self.run_validation()
return {**train_metrics, **val_metrics}

@inference_mode()
def run_train_validation(self, **additional_metrics) -> Dict[str, Any]:
start_time = time.perf_counter()
try:
Expand All @@ -150,6 +152,7 @@ def run_train_validation(self, **additional_metrics) -> Dict[str, Any]:
self.save_metrics_to_checkpoint_folder(metrics_0, name="train_metrics")
return metrics_0

@inference_mode()
def run_validation(self) -> Dict[str, Any]:
start_time = time.perf_counter()
try:
Expand All @@ -174,6 +177,7 @@ def run_validation(self) -> Dict[str, Any]:
self.save_metrics_to_checkpoint_folder(metrics_0, name="validation_metrics")
return metrics_0

@inference_mode()
def run_test(self, ckpt_path="best") -> Dict[str, Any]:
start_time = time.perf_counter()
metrics: Dict[str, Any] = self.trainer.test( # type: ignore
Expand Down