🎨 [Update] pre-commit module, add isort

.pre-commit-config.yaml

@@ -6,3 +6,9 @@ repos:
         language_version: python3  # Specify the Python version
         exclude: '.*\.yaml$'  # Regex pattern to exclude all YAML files
         args: ["--line-length", "120"]  # Set max line length to 100 characters
+        
+  - repo: https://github.com/pre-commit/mirrors-isort
+    rev: v5.10.1  # Use the appropriate version or "stable" for the latest stable release
+    hooks:
+      - id: isort
+        args: ["--profile", "black", "--verbose"]

config/config.py

@@ -1,5 +1,5 @@
 from dataclasses import dataclass
-from typing import List, Dict, Union
+from typing import Dict, List, Union
 
 
 @dataclass

model/module.py

@@ -48,10 +48,12 @@ class Conv(nn.Module):
 # RepVGG
 class RepConv(nn.Module):
     # https://github.com/DingXiaoH/RepVGG
-    def __init__(self, in_channels, out_channels, kernel_size=3, padding=None, stride=1, groups=1, act=nn.SiLU(), deploy=False):
+    def __init__(
+        self, in_channels, out_channels, kernel_size=3, padding=None, stride=1, groups=1, act=nn.SiLU(), deploy=False
+    ):
 
         super().__init__()
-        self.deploy = deploy 
+        self.deploy = deploy
         self.conv1 = Conv(in_channels, out_channels, kernel_size, stride, groups=groups, act=False)
         self.conv2 = Conv(in_channels, out_channels, 1, stride, groups=groups, act=False)
         self.act = act if isinstance(act, nn.Module) else nn.Identity()
@@ -73,15 +75,17 @@ class RepConv(nn.Module):
         weights = conv.weight * t
 
         bn = nn.Identity()
-        conv = nn.Conv2d(in_channels = conv.in_channels,
-                              out_channels = conv.out_channels,
-                              kernel_size = conv.kernel_size,
-                              stride=conv.stride,
-                              padding = conv.padding,
-                              dilation = conv.dilation,
-                              groups = conv.groups,
-                              bias = True,
-                              padding_mode = conv.padding_mode)
+        conv = nn.Conv2d(
+            in_channels=conv.in_channels,
+            out_channels=conv.out_channels,
+            kernel_size=conv.kernel_size,
+            stride=conv.stride,
+            padding=conv.padding,
+            dilation=conv.dilation,
+            groups=conv.groups,
+            bias=True,
+            padding_mode=conv.padding_mode,
+        )
 
         conv.weight = torch.nn.Parameter(weights)
         conv.bias = torch.nn.Parameter(bias)

model/yolo.py

@@ -4,6 +4,7 @@ import torch
 import torch.nn as nn
 from loguru import logger
 from omegaconf import OmegaConf
+
 from tools.layer_helper import get_layer_map
 
 

tests/test_model/test_yolo.py

@@ -1,11 +1,11 @@
+import sys
+
 import pytest
 import torch
-from hydra import initialize, compose
+from hydra import compose, initialize
 from hydra.core.global_hydra import GlobalHydra
 from omegaconf import DictConfig, OmegaConf
 
-import sys
-
 sys.path.append("./")
 from model.yolo import YOLO, get_model
 

tests/test_utils/test_dataaugment.py

@@ -1,11 +1,12 @@
+import sys
+
 import pytest
 import torch
 from PIL import Image
 from torchvision.transforms import functional as TF
-import sys
 
 sys.path.append("./")
-from utils.dataargument import RandomHorizontalFlip, Compose, Mosaic
+from utils.dataargument import Compose, Mosaic, RandomHorizontalFlip
 
 
 def test_random_horizontal_flip():

tools/layer_helper.py

@@ -1,5 +1,7 @@
 import inspect
+
 import torch.nn as nn
+
 from model import module
 
 

tools/log_helper.py

@@ -12,6 +12,7 @@ Example:
 """
 
 import sys
+
 from loguru import logger
 
 

train.py

@@ -1,9 +1,10 @@
+import hydra
 from loguru import logger
+
+from config.config import Config
 from model.yolo import get_model
 from tools.log_helper import custom_logger
 from utils.get_dataset import prepare_dataset
-import hydra
-from config.config import Config
 
 
 @hydra.main(config_path="config", config_name="config", version_base=None)

utils/dataargument.py

@@ -1,6 +1,6 @@
-from PIL import Image
 import numpy as np
 import torch
+from PIL import Image
 from torchvision.transforms import functional as TF
 
 

utils/dataloader.py

@@ -1,16 +1,16 @@
-from PIL import Image
-from os import path, listdir
+from os import listdir, path
+from typing import Union
 
+import diskcache as dc
 import hydra
 import numpy as np
 import torch
-from torch.utils.data import Dataset
+from dataargument import Compose, Mosaic, RandomHorizontalFlip
+from drawer import draw_bboxes
 from loguru import logger
+from PIL import Image
+from torch.utils.data import Dataset
 from tqdm.rich import tqdm
-import diskcache as dc
-from typing import Union
-from drawer import draw_bboxes
-from dataargument import Compose, RandomHorizontalFlip, Mosaic
 
 
 class YoloDataset(Dataset):

utils/get_dataset.py

@@ -2,8 +2,8 @@ import os
 import zipfile
 
 import hydra
-from loguru import logger
 import requests
+from loguru import logger
 from tqdm.rich import tqdm