Replace attr with attrs

9 files changed, 52 insertions, 49 deletions

diff --git a/text_recognizer/data/base_data_module.py b/text_recognizer/data/base_data_module.py
index 15c286a..a0c8416 100644
--- a/text_recognizer/data/base_data_module.py
+++ b/text_recognizer/data/base_data_module.py
@@ -2,7 +2,7 @@
 from pathlib import Path
 from typing import Callable, Dict, Optional, Tuple, Type, TypeVar
 
-import attr
+from attrs import define, field
 from pytorch_lightning import LightningDataModule
 from torch.utils.data import DataLoader
 
@@ -20,29 +20,29 @@ def load_and_print_info(data_module_class: type) -> None:
     print(dataset)
 
 
-@attr.s(repr=False)
+@define(repr=False)
 class BaseDataModule(LightningDataModule):
     """Base PyTorch Lightning DataModule."""
 
-    def __attrs_pre_init__(self) -> None:
+    def __attrs_post_init__(self) -> None:
         """Pre init constructor."""
         super().__init__()
 
-    mapping: Type[AbstractMapping] = attr.ib()
-    transform: Optional[Callable] = attr.ib(default=None)
-    test_transform: Optional[Callable] = attr.ib(default=None)
-    target_transform: Optional[Callable] = attr.ib(default=None)
-    train_fraction: float = attr.ib(default=0.8)
-    batch_size: int = attr.ib(default=16)
-    num_workers: int = attr.ib(default=0)
-    pin_memory: bool = attr.ib(default=True)
+    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 = attr.ib(init=False, default=None)
-    data_val: BaseDataset = attr.ib(init=False, default=None)
-    data_test: BaseDataset = attr.ib(init=False, default=None)
-    dims: Tuple[int, ...] = attr.ib(init=False, default=None)
-    output_dims: Tuple[int, ...] = attr.ib(init=False, default=None)
+    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)
 
     @classmethod
     def data_dirname(cls: T) -> Path:
diff --git a/text_recognizer/data/base_dataset.py b/text_recognizer/data/base_dataset.py
index b9567c7..c57cbcc 100644
--- a/text_recognizer/data/base_dataset.py
+++ b/text_recognizer/data/base_dataset.py
@@ -1,7 +1,7 @@
 """Base PyTorch Dataset class."""
 from typing import Callable, Dict, Optional, Sequence, Tuple, Union
 
-import attr
+from attrs import define, field
 import torch
 from torch import Tensor
 from torch.utils.data import Dataset
@@ -9,7 +9,7 @@ from torch.utils.data import Dataset
 from text_recognizer.data.transforms.load_transform import load_transform_from_file
 
 
-@attr.s
+@define
 class BaseDataset(Dataset):
     r"""Base Dataset class that processes data and targets through optional transfroms.
 
@@ -21,10 +21,10 @@ class BaseDataset(Dataset):
             target transforms.
     """
 
-    data: Union[Sequence, Tensor] = attr.ib()
-    targets: Union[Sequence, Tensor] = attr.ib()
-    transform: Union[Optional[Callable], str] = attr.ib(default=None)
-    target_transform: Union[Optional[Callable], str] = attr.ib(default=None)
+    data: Union[Sequence, Tensor] = field()
+    targets: Union[Sequence, Tensor] = field()
+    transform: Union[Optional[Callable], str] = field(default=None)
+    target_transform: Union[Optional[Callable], str] = field(default=None)
 
     def __attrs_pre_init__(self) -> None:
         """Pre init constructor."""
diff --git a/text_recognizer/data/emnist.py b/text_recognizer/data/emnist.py
index dc8d31a..94882bf 100644
--- a/text_recognizer/data/emnist.py
+++ b/text_recognizer/data/emnist.py
@@ -6,7 +6,7 @@ import shutil
 from typing import Dict, List, Optional, Sequence, Set, Tuple
 import zipfile
 
-import attr
+from attrs import define
 import h5py
 from loguru import logger as log
 import numpy as np
@@ -35,7 +35,7 @@ ESSENTIALS_FILENAME = (
 )
 
 
-@attr.s(auto_attribs=True)
+@define(auto_attribs=True)
 class EMNIST(BaseDataModule):
     """Lightning DataModule class for loading EMNIST dataset.
 
diff --git a/text_recognizer/data/emnist_lines.py b/text_recognizer/data/emnist_lines.py
index c267286..43d55b9 100644
--- a/text_recognizer/data/emnist_lines.py
+++ b/text_recognizer/data/emnist_lines.py
@@ -3,7 +3,7 @@ from collections import defaultdict
 from pathlib import Path
 from typing import DefaultDict, List, Tuple
 
-import attr
+from attrs import define, field
 import h5py
 from loguru import logger as log
 import numpy as np
@@ -33,17 +33,17 @@ IMAGE_X_PADDING = 28
 MAX_OUTPUT_LENGTH = 89  # Same as IAMLines
 
 
-@attr.s(auto_attribs=True, repr=False)
+@define(auto_attribs=True, repr=False)
 class EMNISTLines(BaseDataModule):
     """EMNIST Lines dataset: synthetic handwritten lines dataset made from EMNIST."""
 
-    max_length: int = attr.ib(default=128)
-    min_overlap: float = attr.ib(default=0.0)
-    max_overlap: float = attr.ib(default=0.33)
-    num_train: int = attr.ib(default=10_000)
-    num_val: int = attr.ib(default=2_000)
-    num_test: int = attr.ib(default=2_000)
-    emnist: EMNIST = attr.ib(init=False, default=None)
+    max_length: int = field(default=128)
+    min_overlap: float = field(default=0.0)
+    max_overlap: float = field(default=0.33)
+    num_train: int = field(default=10_000)
+    num_val: int = field(default=2_000)
+    num_test: int = field(default=2_000)
+    emnist: EMNIST = field(init=False, default=None)
 
     def __attrs_post_init__(self) -> None:
         """Post init constructor."""
diff --git a/text_recognizer/data/iam.py b/text_recognizer/data/iam.py
index 766f3e0..8166863 100644
--- a/text_recognizer/data/iam.py
+++ b/text_recognizer/data/iam.py
@@ -9,7 +9,7 @@ from typing import Any, Dict, List
 import xml.etree.ElementTree as ElementTree
 import zipfile
 
-import attr
+from attrs import define, field
 from boltons.cacheutils import cachedproperty
 from loguru import logger as log
 import toml
@@ -27,7 +27,7 @@ DOWNSAMPLE_FACTOR = 2  # If images were downsampled, the regions must also be.
 LINE_REGION_PADDING = 16  # Add this many pixels around the exact coordinates.
 
 
-@attr.s(auto_attribs=True)
+@define(auto_attribs=True)
 class IAM(BaseDataModule):
     r"""The IAM Lines dataset.
 
@@ -44,7 +44,7 @@ class IAM(BaseDataModule):
         contributed to one set only.
     """
 
-    metadata: Dict = attr.ib(init=False, default=toml.load(METADATA_FILENAME))
+    metadata: Dict = field(init=False, default=toml.load(METADATA_FILENAME))
 
     def prepare_data(self) -> None:
         """Prepares the IAM dataset."""
diff --git a/text_recognizer/data/iam_extended_paragraphs.py b/text_recognizer/data/iam_extended_paragraphs.py
index 22d00f1..52c10c3 100644
--- a/text_recognizer/data/iam_extended_paragraphs.py
+++ b/text_recognizer/data/iam_extended_paragraphs.py
@@ -1,5 +1,5 @@
 """IAM original and sythetic dataset class."""
-import attr
+from attrs import define, field
 from torch.utils.data import ConcatDataset
 
 from text_recognizer.data.base_data_module import BaseDataModule, load_and_print_info
@@ -8,7 +8,7 @@ from text_recognizer.data.iam_synthetic_paragraphs import IAMSyntheticParagraphs
 from text_recognizer.data.transforms.load_transform import load_transform_from_file
 
 
-@attr.s(auto_attribs=True, repr=False)
+@define(auto_attribs=True, repr=False)
 class IAMExtendedParagraphs(BaseDataModule):
     """A dataset with synthetic and real handwritten paragraph."""
 
diff --git a/text_recognizer/data/iam_lines.py b/text_recognizer/data/iam_lines.py
index a79c202..34cf605 100644
--- a/text_recognizer/data/iam_lines.py
+++ b/text_recognizer/data/iam_lines.py
@@ -7,7 +7,7 @@ import json
 from pathlib import Path
 from typing import List, Sequence, Tuple
 
-import attr
+from attrs import define, field
 from loguru import logger as log
 import numpy as np
 from PIL import Image, ImageFile, ImageOps
@@ -35,14 +35,14 @@ MAX_LABEL_LENGTH = 89
 MAX_WORD_PIECE_LENGTH = 72
 
 
-@attr.s(auto_attribs=True, repr=False)
+@define(auto_attribs=True, repr=False)
 class IAMLines(BaseDataModule):
     """IAM handwritten lines dataset."""
 
-    dims: Tuple[int, int, int] = attr.ib(
+    dims: Tuple[int, int, int] = field(
         init=False, default=(1, IMAGE_HEIGHT, IMAGE_WIDTH)
     )
-    output_dims: Tuple[int, int] = attr.ib(init=False, default=(MAX_LABEL_LENGTH, 1))
+    output_dims: Tuple[int, int] = field(init=False, default=(MAX_LABEL_LENGTH, 1))
 
     def prepare_data(self) -> None:
         """Creates the IAM lines dataset if not existing."""
diff --git a/text_recognizer/data/iam_paragraphs.py b/text_recognizer/data/iam_paragraphs.py
index 033b93e..b605bbc 100644
--- a/text_recognizer/data/iam_paragraphs.py
+++ b/text_recognizer/data/iam_paragraphs.py
@@ -3,7 +3,7 @@ import json
 from pathlib import Path
 from typing import Dict, List, Optional, Sequence, Tuple
 
-import attr
+from attrs import define, field
 from loguru import logger as log
 import numpy as np
 from PIL import Image, ImageOps
@@ -33,15 +33,15 @@ MAX_LABEL_LENGTH = 682
 MAX_WORD_PIECE_LENGTH = 451
 
 
-@attr.s(auto_attribs=True, repr=False)
+@define(auto_attribs=True, repr=False)
 class IAMParagraphs(BaseDataModule):
     """IAM handwriting database paragraphs."""
 
     # Placeholders
-    dims: Tuple[int, int, int] = attr.ib(
+    dims: Tuple[int, int, int] = field(
         init=False, default=(1, IMAGE_HEIGHT, IMAGE_WIDTH)
     )
-    output_dims: Tuple[int, int] = attr.ib(init=False, default=(MAX_LABEL_LENGTH, 1))
+    output_dims: Tuple[int, int] = field(init=False, default=(MAX_LABEL_LENGTH, 1))
 
     def prepare_data(self) -> None:
         """Create data for training/testing."""
@@ -86,7 +86,10 @@ class IAMParagraphs(BaseDataModule):
                 length=self.output_dims[0],
             )
             return BaseDataset(
-                data, targets, transform=transform, target_transform=target_transform,
+                data,
+                targets,
+                transform=transform,
+                target_transform=target_transform,
             )
 
         log.info(f"Loading IAM paragraph regions and lines for {stage}...")
diff --git a/text_recognizer/data/iam_synthetic_paragraphs.py b/text_recognizer/data/iam_synthetic_paragraphs.py
index ea59098..7143951 100644
--- a/text_recognizer/data/iam_synthetic_paragraphs.py
+++ b/text_recognizer/data/iam_synthetic_paragraphs.py
@@ -2,7 +2,7 @@
 import random
 from typing import Any, List, Sequence, Tuple
 
-import attr
+from attrs import define
 from loguru import logger as log
 import numpy as np
 from PIL import Image
@@ -34,7 +34,7 @@ PROCESSED_DATA_DIRNAME = (
 )
 
 
-@attr.s(auto_attribs=True, repr=False)
+@define(auto_attribs=True, repr=False)
 class IAMSyntheticParagraphs(IAMParagraphs):
     """IAM Handwriting database of synthetic paragraphs."""