Remove uploading of code to Wandb, upload config instead

1 files changed, 5 insertions, 5 deletions

diff --git a/text_recognizer/models/base.py b/text_recognizer/models/base.py
index 94dbde5..56d4ca5 100644
--- a/text_recognizer/models/base.py
+++ b/text_recognizer/models/base.py
@@ -1,5 +1,5 @@
 """Base PyTorch Lightning model."""
-from typing import Any, Dict, List, Tuple, Type
+from typing import Any, Dict, List, Optional, Tuple, Type
 
 import attr
 import hydra
@@ -25,7 +25,7 @@ class BaseLitModel(LightningModule):
     mapping: Type[AbstractMapping] = attr.ib()
     loss_fn: Type[nn.Module] = attr.ib()
     optimizer_configs: DictConfig = attr.ib()
-    lr_scheduler_configs: DictConfig = attr.ib()
+    lr_scheduler_configs: Optional[DictConfig] = attr.ib()
     train_acc: torchmetrics.Accuracy = attr.ib(
         init=False, default=torchmetrics.Accuracy()
     )
@@ -55,9 +55,7 @@ class BaseLitModel(LightningModule):
             del optimizer_config.parameters
             log.info(f"Instantiating optimizer <{optimizer_config._target_}>")
             optimizers.append(
-                hydra.utils.instantiate(
-                    optimizer_config, params=module.parameters()
-                )
+                hydra.utils.instantiate(optimizer_config, params=module.parameters())
             )
         return optimizers
 
@@ -65,6 +63,8 @@ class BaseLitModel(LightningModule):
         self, optimizers: List[Type[torch.optim.Optimizer]]
     ) -> List[Dict[str, Any]]:
         """Configures the lr scheduler."""
+        if None in self.lr_scheduler_configs:
+            return []
         schedulers = []
         for optimizer, lr_scheduler_config in zip(
             optimizers, self.lr_scheduler_configs.values()