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| author | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2021-04-11 21:48:34 +0200 |
|---|---|---|
| committer | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2021-04-11 21:48:34 +0200 |
| commit | 0ab820d3595e4f17d4f1f3c310e186692f65cc67 (patch) | |
| tree | 21891ab98c10e64ef9261c69b2d494f42cda66f1 /text_recognizer/models | |
| parent | a548e421314908771ce9e413d9fa4e205943cceb (diff) | |
Working on mapping
Diffstat (limited to 'text_recognizer/models')
| -rw-r--r-- | text_recognizer/models/base.py | 1 | ||||
| -rw-r--r-- | text_recognizer/models/transformer.py | 5 |
2 files changed, 3 insertions, 3 deletions
diff --git a/text_recognizer/models/base.py b/text_recognizer/models/base.py index 0928e6c..c6d5d73 100644 --- a/text_recognizer/models/base.py +++ b/text_recognizer/models/base.py @@ -60,6 +60,7 @@ class LitBaseModel(pl.LightningModule): scheduler["scheduler"] = getattr( torch.optim.lr_scheduler, self._lr_scheduler.type )(optimizer, **args) + return scheduler def configure_optimizers(self) -> Tuple[List[type], List[Dict[str, Any]]]: diff --git a/text_recognizer/models/transformer.py b/text_recognizer/models/transformer.py index b23685b..7dc1352 100644 --- a/text_recognizer/models/transformer.py +++ b/text_recognizer/models/transformer.py @@ -1,5 +1,5 @@ """PyTorch Lightning model for base Transformers.""" -from typing import Dict, List, Optional, Union, Tuple +from typing import Dict, List, Optional, Union, Tuple, Type from omegaconf import DictConfig, OmegaConf import pytorch_lightning as pl @@ -19,7 +19,7 @@ class LitTransformerModel(LitBaseModel): def __init__( self, - network: Type[nn, Module], + network: Type[nn.Module], optimizer: Union[DictConfig, Dict], lr_scheduler: Union[DictConfig, Dict], criterion: Union[DictConfig, Dict], @@ -27,7 +27,6 @@ class LitTransformerModel(LitBaseModel): mapping: Optional[List[str]] = None, ) -> None: super().__init__(network, optimizer, lr_scheduler, criterion, monitor) - self.mapping, ignore_tokens = self.configure_mapping(mapping) self.val_cer = CharacterErrorRate(ignore_tokens) self.test_cer = CharacterErrorRate(ignore_tokens) |