style: Bumps ruff to 0.1.14 (#290)

* chore: Bumps ruff to 0.1.14 * ci: Updates CI version of ruff * style: Fixes lint & format
frgfm · Jan 28, 2024 · 6af1a7f · 6af1a7f
1 parent d2158e6
commit 6af1a7f
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diff --git a/.github/collect_env.py b/.github/collect_env.py
@@ -14,7 +14,7 @@
 import locale
 import os
 import re
-import subprocess
+import subprocess  # noqa S404
 import sys
 from pathlib import Path
 from typing import NamedTuple

diff --git a/.github/workflows/style.yml b/.github/workflows/style.yml
@@ -21,7 +21,7 @@ jobs:
           architecture: x64
       - name: Run ruff
         run: |
-          pip install ruff==0.1.11
+          pip install ruff==0.1.14
           ruff --version
           ruff check --diff .
 
@@ -65,7 +65,7 @@ jobs:
           architecture: x64
       - name: Run ruff
         run: |
-          pip install ruff==0.1.11
+          pip install ruff==0.1.14
           ruff --version
           ruff format --check --diff .
 

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -21,7 +21,7 @@ repos:
         args: ['--branch', 'main']
       - id: trailing-whitespace
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: 'v0.1.11'
+    rev: 'v0.1.14'
     hooks:
       - id: ruff
         args:

diff --git a/api/app/vision.py b/api/app/vision.py
@@ -15,7 +15,7 @@
 
 from app.config import settings
 
-__all__ = ["decode_image", "classify_image"]
+__all__ = ["classify_image", "decode_image"]
 
 logger = logging.getLogger("uvicorn.warning")
 

diff --git a/holocron/models/checkpoints.py b/holocron/models/checkpoints.py
@@ -12,12 +12,12 @@
 
 __all__ = [
     "Checkpoint",
-    "TrainingRecipe",
-    "Metric",
     "Dataset",
     "Evaluation",
     "LoadingMeta",
+    "Metric",
     "PreProcessing",
+    "TrainingRecipe",
 ]
 
 

diff --git a/holocron/models/classification/convnext.py b/holocron/models/classification/convnext.py
@@ -23,13 +23,13 @@
     "ConvNeXt",
     "ConvNeXt_Atto_Checkpoint",
     "convnext_atto",
+    "convnext_base",
     "convnext_femto",
-    "convnext_pico",
+    "convnext_large",
     "convnext_nano",
-    "convnext_tiny",
+    "convnext_pico",
     "convnext_small",
-    "convnext_base",
-    "convnext_large",
+    "convnext_tiny",
     "convnext_xl",
 ]
 

diff --git a/holocron/models/classification/darknetv2.py b/holocron/models/classification/darknetv2.py
@@ -17,7 +17,7 @@
 from ..presets import IMAGENETTE
 from ..utils import _checkpoint, _configure_model, conv_sequence
 
-__all__ = ["DarknetV2", "Darknet19_Checkpoint", "darknet19"]
+__all__ = ["Darknet19_Checkpoint", "DarknetV2", "darknet19"]
 
 
 default_cfgs: Dict[str, Dict[str, Any]] = {

diff --git a/holocron/models/classification/darknetv3.py b/holocron/models/classification/darknetv3.py
@@ -17,7 +17,7 @@
 from ..utils import _checkpoint, _configure_model, conv_sequence
 from .resnet import _ResBlock
 
-__all__ = ["DarknetV3", "Darknet53_Checkpoint", "darknet53"]
+__all__ = ["Darknet53_Checkpoint", "DarknetV3", "darknet53"]
 
 
 class ResBlock(_ResBlock):

diff --git a/holocron/models/classification/darknetv4.py b/holocron/models/classification/darknetv4.py
@@ -18,7 +18,7 @@
 from ..utils import _checkpoint, _configure_model, conv_sequence
 from .darknetv3 import ResBlock
 
-__all__ = ["DarknetV4", "CSPDarknet53_Checkpoint", "cspdarknet53", "CSPDarknet53_Mish_Checkpoint", "cspdarknet53_mish"]
+__all__ = ["CSPDarknet53_Checkpoint", "CSPDarknet53_Mish_Checkpoint", "DarknetV4", "cspdarknet53", "cspdarknet53_mish"]
 
 
 default_cfgs: Dict[str, Dict[str, Any]] = {

diff --git a/holocron/models/classification/mobileone.py b/holocron/models/classification/mobileone.py
@@ -18,12 +18,12 @@
 
 __all__ = [
     "MobileOne_S0_Checkpoint",
-    "mobileone_s0",
     "MobileOne_S1_Checkpoint",
-    "mobileone_s1",
     "MobileOne_S2_Checkpoint",
-    "mobileone_s2",
     "MobileOne_S3_Checkpoint",
+    "mobileone_s0",
+    "mobileone_s1",
+    "mobileone_s2",
     "mobileone_s3",
 ]
 

diff --git a/holocron/models/classification/repvgg.py b/holocron/models/classification/repvgg.py
@@ -16,20 +16,20 @@
 from ..utils import _checkpoint, _configure_model, conv_sequence, fuse_conv_bn
 
 __all__ = [
-    "RepVGG",
     "RepBlock",
     "RepVGG",
+    "RepVGG",
     "RepVGG_A0_Checkpoint",
-    "repvgg_a0",
     "RepVGG_A1_Checkpoint",
-    "repvgg_a1",
     "RepVGG_A2_Checkpoint",
-    "repvgg_a2",
     "RepVGG_B0_Checkpoint",
-    "repvgg_b0",
     "RepVGG_B1_Checkpoint",
-    "repvgg_b1",
     "RepVGG_B2_Checkpoint",
+    "repvgg_a0",
+    "repvgg_a1",
+    "repvgg_a2",
+    "repvgg_b0",
+    "repvgg_b1",
     "repvgg_b2",
     "repvgg_b3",
 ]

diff --git a/holocron/models/classification/resnet.py b/holocron/models/classification/resnet.py
@@ -19,20 +19,20 @@
 __all__ = [
     "BasicBlock",
     "Bottleneck",
+    "ResNeXt50_32x4d_Checkpoint",
     "ResNet",
     "ResNet18_Checkpoint",
-    "resnet18",
     "ResNet34_Checkpoint",
-    "resnet34",
+    "ResNet50D_Checkpoint",
     "ResNet50_Checkpoint",
+    "resnet18",
+    "resnet34",
     "resnet50",
+    "resnet50d",
     "resnet101",
     "resnet152",
-    "ResNeXt50_32x4d_Checkpoint",
     "resnext50_32x4d",
     "resnext101_32x8d",
-    "ResNet50D_Checkpoint",
-    "resnet50d",
 ]
 
 

diff --git a/holocron/models/classification/rexnet.py b/holocron/models/classification/rexnet.py
@@ -19,18 +19,18 @@
 from ..utils import _checkpoint, _configure_model, conv_sequence
 
 __all__ = [
-    "SEBlock",
     "ReXBlock",
     "ReXNet",
     "ReXNet1_0x_Checkpoint",
-    "rexnet1_0x",
     "ReXNet1_3x_Checkpoint",
-    "rexnet1_3x",
     "ReXNet1_5x_Checkpoint",
-    "rexnet1_5x",
     "ReXNet2_0x_Checkpoint",
-    "rexnet2_0x",
     "ReXNet2_2x_Checkpoint",
+    "SEBlock",
+    "rexnet1_0x",
+    "rexnet1_3x",
+    "rexnet1_5x",
+    "rexnet2_0x",
     "rexnet2_2x",
 ]
 

diff --git a/holocron/models/classification/sknet.py b/holocron/models/classification/sknet.py
@@ -16,7 +16,7 @@
 from ..utils import _checkpoint, _configure_model, conv_sequence
 from .resnet import ResNet, _ResBlock
 
-__all__ = ["SoftAttentionLayer", "SKConv2d", "SKBottleneck", "SKNet50_Checkpoint", "sknet50", "sknet101", "sknet152"]
+__all__ = ["SKBottleneck", "SKConv2d", "SKNet50_Checkpoint", "SoftAttentionLayer", "sknet50", "sknet101", "sknet152"]
 
 
 default_cfgs: Dict[str, Dict[str, Any]] = {

diff --git a/holocron/models/detection/yolov4.py b/holocron/models/detection/yolov4.py
@@ -20,7 +20,7 @@
 from ..classification.darknetv4 import default_cfgs as dark_cfgs
 from ..utils import conv_sequence, load_pretrained_params
 
-__all__ = ["YOLOv4", "yolov4", "PAN"]
+__all__ = ["PAN", "YOLOv4", "yolov4"]
 
 
 default_cfgs = {

diff --git a/holocron/models/presets.py b/holocron/models/presets.py
@@ -3,7 +3,7 @@
 # This program is licensed under the Apache License 2.0.
 # See LICENSE or go to <https://www.apache.org/licenses/LICENSE-2.0> for full license details.
 
-__all__ = ["IMAGENET", "IMAGENETTE", "CIFAR10"]
+__all__ = ["CIFAR10", "IMAGENET", "IMAGENETTE"]
 
 from dataclasses import dataclass
 from typing import List, Tuple

diff --git a/holocron/models/segmentation/unet.py b/holocron/models/segmentation/unet.py
@@ -18,7 +18,7 @@
 from ..classification.rexnet import rexnet1_3x
 from ..utils import conv_sequence, load_pretrained_params
 
-__all__ = ["UNet", "unet", "DynamicUNet", "unet_tvvgg11", "unet_tvresnet34", "unet_rexnet13", "unet2"]
+__all__ = ["DynamicUNet", "UNet", "unet", "unet2", "unet_rexnet13", "unet_tvresnet34", "unet_tvvgg11"]
 
 
 default_cfgs: Dict[str, Dict[str, Any]] = {

diff --git a/holocron/models/segmentation/unetpp.py b/holocron/models/segmentation/unetpp.py
@@ -13,7 +13,7 @@
 from ..utils import conv_sequence, load_pretrained_params
 from .unet import UpPath, down_path
 
-__all__ = ["UNetp", "unetp", "UNetpp", "unetpp"]
+__all__ = ["UNetp", "UNetpp", "unetp", "unetpp"]
 
 
 default_cfgs: Dict[str, Dict[str, Any]] = {

diff --git a/holocron/models/utils.py b/holocron/models/utils.py
@@ -19,7 +19,7 @@
 from .checkpoints import Checkpoint, Dataset, Evaluation, LoadingMeta, Metric, PreProcessing, TrainingRecipe
 from .presets import IMAGENET, IMAGENETTE
 
-__all__ = ["conv_sequence", "load_pretrained_params", "fuse_conv_bn", "model_from_hf_hub"]
+__all__ = ["conv_sequence", "fuse_conv_bn", "load_pretrained_params", "model_from_hf_hub"]
 
 M = TypeVar("M", bound=nn.Module)
 

diff --git a/holocron/nn/functional.py b/holocron/nn/functional.py
@@ -11,19 +11,19 @@
 from torch import Tensor
 
 __all__ = [
-    "hard_mish",
-    "nl_relu",
+    "add2d",
+    "complement_cross_entropy",
+    "concat_downsample2d",
+    "dice_loss",
+    "dropblock2d",
     "focal_loss",
+    "hard_mish",
     "multilabel_cross_entropy",
-    "complement_cross_entropy",
     "mutual_channel_loss",
+    "nl_relu",
     "norm_conv2d",
-    "add2d",
-    "dropblock2d",
-    "z_pool",
-    "concat_downsample2d",
-    "dice_loss",
     "poly_loss",
+    "z_pool",
 ]
 
 

diff --git a/holocron/nn/modules/activation.py b/holocron/nn/modules/activation.py
@@ -11,7 +11,7 @@
 
 from .. import functional as F
 
-__all__ = ["HardMish", "NLReLU", "FReLU"]
+__all__ = ["FReLU", "HardMish", "NLReLU"]
 
 
 class _Activation(nn.Module):

diff --git a/holocron/nn/modules/conv.py b/holocron/nn/modules/conv.py
@@ -15,7 +15,7 @@
 
 from .. import functional as F
 
-__all__ = ["NormConv2d", "Add2d", "SlimConv2d", "PyConv2d", "Involution2d"]
+__all__ = ["Add2d", "Involution2d", "NormConv2d", "PyConv2d", "SlimConv2d"]
 
 
 class _NormConvNd(_ConvNd):

diff --git a/holocron/nn/modules/downsample.py b/holocron/nn/modules/downsample.py
@@ -13,12 +13,12 @@
 from .. import functional as F
 
 __all__ = [
+    "SPP",
+    "BlurPool2d",
     "ConcatDownsample2d",
     "ConcatDownsample2dJit",
     "GlobalAvgPool2d",
     "GlobalMaxPool2d",
-    "BlurPool2d",
-    "SPP",
     "ZPool",
 ]
 

diff --git a/holocron/nn/modules/loss.py b/holocron/nn/modules/loss.py
@@ -12,12 +12,12 @@
 from .. import functional as F
 
 __all__ = [
+    "ClassBalancedWrapper",
+    "ComplementCrossEntropy",
+    "DiceLoss",
     "FocalLoss",
     "MultiLabelCrossEntropy",
-    "ComplementCrossEntropy",
-    "ClassBalancedWrapper",
     "MutualChannelLoss",
-    "DiceLoss",
     "PolyLoss",
 ]
 

diff --git a/holocron/ops/boxes.py b/holocron/ops/boxes.py
@@ -10,7 +10,7 @@
 from torch import Tensor
 from torchvision.ops.boxes import box_area, box_iou
 
-__all__ = ["box_giou", "diou_loss", "ciou_loss"]
+__all__ = ["box_giou", "ciou_loss", "diou_loss"]
 
 
 def _box_iou(boxes1: Tensor, boxes2: Tensor) -> Tuple[Tensor, Tensor]:

diff --git a/holocron/trainer/classification.py b/holocron/trainer/classification.py
@@ -15,7 +15,7 @@
 
 from .core import Trainer
 
-__all__ = ["ClassificationTrainer", "BinaryClassificationTrainer"]
+__all__ = ["BinaryClassificationTrainer", "ClassificationTrainer"]
 
 
 class ClassificationTrainer(Trainer):
@@ -142,8 +142,7 @@ def plot_top_losses(
         num_cols = 4
         num_rows = int(math.ceil(num_samples / num_cols))
         _, axes = plt.subplots(num_rows, num_cols, figsize=(20, 5))
-        idx = 0
-        for img, pred, prob, target, loss in zip(images, preds, probs, targets, losses):
+        for idx, (img, pred, prob, target, loss) in enumerate(zip(images, preds, probs, targets, losses)):
             _row = int(idx / num_cols)
             _col = idx - num_cols * _row
             axes[_row][_col].imshow(img)
@@ -156,7 +155,6 @@ def plot_top_losses(
                     f"{loss:.3} / {classes[pred]} ({prob:.1%}) / {classes[target]}"  # type: ignore[index]
                 )
             axes[_row][_col].axis("off")
-            idx += 1
 
         plt.show(**kwargs)
 

diff --git a/holocron/transforms/interpolation.py b/holocron/transforms/interpolation.py
@@ -13,7 +13,7 @@
 from torchvision.transforms import transforms as T
 from torchvision.transforms.functional import pad, resize
 
-__all__ = ["Resize", "RandomZoomOut"]
+__all__ = ["RandomZoomOut", "Resize"]
 
 
 class ResizeMethod(str, Enum):

diff --git a/holocron/utils/misc.py b/holocron/utils/misc.py
@@ -17,7 +17,7 @@
 Out = TypeVar("Out")
 
 
-__all__ = ["parallel", "find_image_size"]
+__all__ = ["find_image_size", "parallel"]
 
 
 def parallel(