lint

tests/test_logger.py

@@ -2,6 +2,7 @@
 import logging
 from trolo.utils.logging.glob_logger import platform_safe_emojis, configure_logger, add_separator_method
 
+
 @pytest.fixture
 def test_logger():
     """Fixture to create a test logger with separator support."""

trolo/__init__.py

@@ -7,4 +7,4 @@
 
 from .loaders.registry import GLOBAL_CONFIG
 from .inference import DetectionPredictor
-from .utils.box_ops import to_sv
+from .utils.box_ops import to_sv

trolo/inference/base.py

@@ -12,6 +12,7 @@
 from trolo.utils.draw_utils import draw_predictions
 from trolo.utils.logging import LOGGER
 
+
 class BasePredictor(ABC):
     def __init__(self, model_path: str, device: Optional[str] = None):
         self.device = torch.device(infer_device(device))

trolo/inference/detection.py

@@ -17,6 +17,7 @@
 
 from ..utils.logging import LOGGER
 
+
 class DetectionPredictor(BasePredictor):
     def __init__(
         self,
@@ -111,7 +112,9 @@ def preprocess(self, inputs: Union[str, List[str], Image.Image, List[Image.Image
 
         return torch.stack(images).to(self.device)
 
-    def postprocess(self, outputs: torch.Tensor, letterbox_sizes: List[Tuple[int, int]], original_sizes: List[Tuple[int, int]]) -> List[Dict[str, Any]]:
+    def postprocess(
+        self, outputs: torch.Tensor, letterbox_sizes: List[Tuple[int, int]], original_sizes: List[Tuple[int, int]]
+    ) -> List[Dict[str, Any]]:
         """Convert model outputs to boxes, scores, labels
 
         Returns:

trolo/loaders/_config.py

@@ -9,7 +9,7 @@
 from pathlib import Path
 from typing import Callable, List, Dict
 
-from ..utils.logging  import LOGGER
+from ..utils.logging import LOGGER
 
 
 __all__ = [

trolo/loaders/yaml_config.py

@@ -11,7 +11,7 @@
 from .registry import create_from_config
 from .yaml_utils import load_config, merge_config, merge_dict
 
-from ..utils.logging  import LOGGER
+from ..utils.logging import LOGGER
 
 
 class YAMLConfig(BaseConfig):

trolo/train.py

@@ -47,6 +47,7 @@ def init_distributed_mode(device="cpu"):
         logger.warning(f"Distributed training initialization failed: {e}")
         logger.info("Running in non-distributed mode.")
 
+
 def train_model(
     config: str,
     resume: str = None,

trolo/trainers/base.py

@@ -287,8 +287,12 @@ def _load_separate_configs(self, model, dataset, **overrides) -> YAMLConfig:
             raise TypeError(f"Unsupported dataset type: {type(dataset)}")
 
         # Print configs before merge for debugging
-        LOGGER.info(f"Model config transforms: {model_config.get('train_dataloader', {}).get('dataset', {}).get('transforms')}")
-        LOGGER.info(f"Dataset config transforms: {dataset_config.get('train_dataloader', {}).get('dataset', {}).get('transforms')}")
+        LOGGER.info(
+            f"Model config transforms: {model_config.get('train_dataloader', {}).get('dataset', {}).get('transforms')}"
+        )
+        LOGGER.info(
+            f"Dataset config transforms: {dataset_config.get('train_dataloader', {}).get('dataset', {}).get('transforms')}"
+        )
 
         # Merge configs
         cfg = YAMLConfig.merge_configs(model_config, dataset_config, **overrides)

trolo/trainers/clas_engine.py

@@ -61,7 +61,7 @@ def evaluate(model, criterion, dataloader, device):
         metric_logger.update(**reduced_values)
 
     metric_logger.synchronize_between_processes()
-    logger.info(f"Averaged stats: {metric_logger}" )
+    logger.info(f"Averaged stats: {metric_logger}")
 
     stats = {k: meter.global_avg for k, meter in metric_logger.meters.items()}
     return stats

trolo/trainers/classification.py

@@ -55,7 +55,7 @@ def fit(
         args = self.cfg
 
         n_parameters = sum(p.numel() for p in self.model.parameters() if p.requires_grad)
-        logger.info(f"Number of params: {n_parameters}" )
+        logger.info(f"Number of params: {n_parameters}")
 
         output_dir = Path(args.output_dir)
         output_dir.mkdir(exist_ok=True)

trolo/trainers/det_engine.py

@@ -96,7 +96,7 @@ def train_one_epoch(
         loss_value = sum(loss_dict_reduced.values())
 
         if not math.isfinite(loss_value):
-            LOGGER.info(F"Loss is {loss_value}, stopping training")
+            LOGGER.info(f"Loss is {loss_value}, stopping training")
             LOGGER.info(f"{loss_dict_reduced}")
             sys.exit(1)
 

trolo/utils/dist_utils.py

@@ -18,6 +18,7 @@
 # from torch.utils.data.dataloader import DataLoader
 from ..data import DataLoader
 
+
 def setup_distributed(
     print_rank: int = 0,
     print_method: str = "builtin",

trolo/utils/logger.py

@@ -231,5 +231,3 @@ def log_every(self, iterable, print_freq, header=None):
         total_time = time.time() - start_time
         total_time_str = str(datetime.timedelta(seconds=int(total_time)))
         print("{} Total time: {} ({:.4f} s / it)".format(header, total_time_str, total_time / len(iterable)))
-
-

trolo/utils/logging/glob_logger.py

@@ -3,14 +3,17 @@
 import sys
 import logging
 
+
 def platform_safe_emojis(emoji_str=""):
     """Return emoji-safe version of the string."""
-    return emoji.emojize(emoji_str, language='alias')
+    return emoji.emojize(emoji_str, language="alias")
+
 
 class ColorLogger(logging.Formatter):
     """
     Custom formatter with colors & emojis for all log levels.
     """
+
     # No color for INFO
     COLORS = {
         "DEBUG": Fore.BLUE,
@@ -26,24 +29,27 @@ class ColorLogger(logging.Formatter):
         "ERROR": "❌",
         "CRITICAL": "🔥",
     }
+
     def format(self, record):
         levelname = record.levelname
         message = super().format(record)
         color = self.COLORS.get(levelname, Style.RESET_ALL)
         emoji_symbol = platform_safe_emojis(self.EMOJIS.get(levelname, ""))
         return f"{color}{emoji_symbol} {message}{Style.RESET_ALL}"
 
+
 def add_separator_method(logger):
     """
     Add a separator method to the logger.
-    
+
     :param logger: The logger instance
     :return: The logger with added separator method
     """
-    def separator(text, char='-', width=85):
+
+    def separator(text, char="-", width=85):
         """
         Create a separator line with optional text.
-        
+
         :param text: Text to display in the separator
         :param char: Character to use for separator
         :param width: Total width of the separator
@@ -52,25 +58,26 @@ def separator(text, char='-', width=85):
         total_width = width
         text_with_spaces = f" {text} "
         padding_length = (total_width - len(text_with_spaces)) // 2
-        
+
         # Create separator line
         separator_line = char * padding_length + text_with_spaces + char * padding_length
-        
+
         # Ensure exact width by trimming or padding
         separator_line = separator_line[:total_width]
         separator_line = separator_line.ljust(total_width, char)
-        
+
         # Log the separator
         logger.info(separator_line)
-    
+
     # Attach the separator method to the logger
     logger.separator = separator
     return logger
 
+
 def configure_logger(name="default_logger", verbose=True, rank=0):
     """
     Configure logger with color and emoji formatting and customizable verbosity.
-    
+
     :param name: Name of the logger
     :param verbose: Whether to set logging level to INFO
     :param rank: Rank of the process (to control logging)
@@ -91,5 +98,6 @@ def configure_logger(name="default_logger", verbose=True, rank=0):
 
     return logger
 
+
 # Lazy initialization
-LOGGER =  add_separator_method(configure_logger())
+LOGGER = add_separator_method(configure_logger())