Remove attrs

1 files changed, 26 insertions, 20 deletions

diff --git a/text_recognizer/data/base_data_module.py b/text_recognizer/data/base_data_module.py
index a0c8416..6306cf8 100644
--- a/text_recognizer/data/base_data_module.py
+++ b/text_recognizer/data/base_data_module.py
@@ -2,7 +2,6 @@
 from pathlib import Path
 from typing import Callable, Dict, Optional, Tuple, Type, TypeVar
 
-from attrs import define, field
 from pytorch_lightning import LightningDataModule
 from torch.utils.data import DataLoader
 
@@ -20,29 +19,36 @@ def load_and_print_info(data_module_class: type) -> None:
     print(dataset)
 
 
-@define(repr=False)
 class BaseDataModule(LightningDataModule):
     """Base PyTorch Lightning DataModule."""
 
-    def __attrs_post_init__(self) -> None:
-        """Pre init constructor."""
+    def __init__(
+        self,
+        mapping: Type[AbstractMapping],
+        transform: Optional[Callable] = None,
+        test_transform: Optional[Callable] = None,
+        target_transform: Optional[Callable] = None,
+        train_fraction: float = 0.8,
+        batch_size: int = 16,
+        num_workers: int = 0,
+        pin_memory: bool = True,
+    ) -> None:
         super().__init__()
-
-    mapping: Type[AbstractMapping] = field()
-    transform: Optional[Callable] = field(default=None)
-    test_transform: Optional[Callable] = field(default=None)
-    target_transform: Optional[Callable] = field(default=None)
-    train_fraction: float = field(default=0.8)
-    batch_size: int = field(default=16)
-    num_workers: int = field(default=0)
-    pin_memory: bool = field(default=True)
-
-    # Placeholders
-    data_train: BaseDataset = field(init=False, default=None)
-    data_val: BaseDataset = field(init=False, default=None)
-    data_test: BaseDataset = field(init=False, default=None)
-    dims: Tuple[int, ...] = field(init=False, default=None)
-    output_dims: Tuple[int, ...] = field(init=False, default=None)
+        self.mapping = mapping
+        self.transform = transform
+        self.test_transform = test_transform
+        self.target_transform = target_transform
+        self.train_fraction = train_fraction
+        self.batch_size = batch_size
+        self.num_workers = num_workers
+        self.pin_memory = pin_memory
+
+        # Placeholders
+        self.data_train: BaseDataset
+        self.data_val: BaseDataset
+        self.data_test: BaseDataset
+        self.dims: Tuple[int, ...]
+        self.output_dims: Tuple[int, ...]
 
     @classmethod
     def data_dirname(cls: T) -> Path: