Comet updates (#11818)

* update colab link

* fix path check for datasets

* apply yapf

* run precommit hooks

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

utils/loggers/comet/README.md

@@ -59,7 +59,7 @@ Check out an example of a [completed run here](https://www.comet.com/examples/co
 
 Or better yet, try it out yourself in this Colab Notebook
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1RG0WOQyxlDlo5Km8GogJpIEJlg_5lyYO?usp=sharing)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/comet-ml/comet-examples/blob/master/integrations/model-training/yolov5/notebooks/Comet_and_YOLOv5.ipynb)
 
 # Log automatically
 

utils/loggers/comet/__init__.py

@@ -42,7 +42,7 @@
 COMET_UPLOAD_DATASET = os.getenv('COMET_UPLOAD_DATASET', 'false').lower() == 'true'
 
 # Evaluation Settings
-COMET_LOG_CONFUSION_MATRIX = os.getenv('COMET_LOG_CONFUSION_MATRIX', 'true').lower() == 'true'
+COMET_LOG_CONFUSION_MATRIX = (os.getenv('COMET_LOG_CONFUSION_MATRIX', 'true').lower() == 'true')
 COMET_LOG_PREDICTIONS = os.getenv('COMET_LOG_PREDICTIONS', 'true').lower() == 'true'
 COMET_MAX_IMAGE_UPLOADS = int(os.getenv('COMET_MAX_IMAGE_UPLOADS', 100))
 
@@ -51,10 +51,10 @@
 IOU_THRES = float(os.getenv('IOU_THRES', 0.6))
 
 # Batch Logging Settings
-COMET_LOG_BATCH_METRICS = os.getenv('COMET_LOG_BATCH_METRICS', 'false').lower() == 'true'
+COMET_LOG_BATCH_METRICS = (os.getenv('COMET_LOG_BATCH_METRICS', 'false').lower() == 'true')
 COMET_BATCH_LOGGING_INTERVAL = os.getenv('COMET_BATCH_LOGGING_INTERVAL', 1)
 COMET_PREDICTION_LOGGING_INTERVAL = os.getenv('COMET_PREDICTION_LOGGING_INTERVAL', 1)
-COMET_LOG_PER_CLASS_METRICS = os.getenv('COMET_LOG_PER_CLASS_METRICS', 'false').lower() == 'true'
+COMET_LOG_PER_CLASS_METRICS = (os.getenv('COMET_LOG_PER_CLASS_METRICS', 'false').lower() == 'true')
 
 RANK = int(os.getenv('RANK', -1))
 
@@ -137,7 +137,7 @@ def __init__(self, opt, hyp, run_id=None, job_type='Training', **experiment_kwar
 
         self.comet_log_predictions = COMET_LOG_PREDICTIONS
         if self.opt.bbox_interval == -1:
-            self.comet_log_prediction_interval = 1 if self.opt.epochs < 10 else self.opt.epochs // 10
+            self.comet_log_prediction_interval = (1 if self.opt.epochs < 10 else self.opt.epochs // 10)
         else:
             self.comet_log_prediction_interval = self.opt.bbox_interval
 
@@ -232,7 +232,8 @@ def check_dataset(self, data_file):
         with open(data_file) as f:
             data_config = yaml.safe_load(f)
 
-        if data_config['path'].startswith(COMET_PREFIX):
+        path = data_config.get('path')
+        if path and path.startswith(COMET_PREFIX):
             path = data_config['path'].replace(COMET_PREFIX, '')
             data_dict = self.download_dataset_artifact(path)
 
@@ -313,8 +314,16 @@ def add_assets_to_artifact(self, artifact, path, asset_path, split):
             image_logical_path, label_logical_path = map(lambda x: os.path.relpath(x, path), [image_file, label_file])
 
             try:
-                artifact.add(image_file, logical_path=image_logical_path, metadata={'split': split})
-                artifact.add(label_file, logical_path=label_logical_path, metadata={'split': split})
+                artifact.add(
+                    image_file,
+                    logical_path=image_logical_path,
+                    metadata={'split': split},
+                )
+                artifact.add(
+                    label_file,
+                    logical_path=label_logical_path,
+                    metadata={'split': split},
+                )
             except ValueError as e:
                 logger.error('COMET ERROR: Error adding file to Artifact. Skipping file.')
                 logger.error(f'COMET ERROR: {e}')
@@ -476,8 +485,9 @@ def on_val_end(self, nt, tp, fp, p, r, f1, ap, ap50, ap_class, confusion_matrix)
                             'f1': f1[i],
                             'true_positives': tp[i],
                             'false_positives': fp[i],
-                            'support': nt[c]},
-                        prefix=class_name)
+                            'support': nt[c], },
+                        prefix=class_name,
+                    )
 
         if self.comet_log_confusion_matrix:
             epoch = self.experiment.curr_epoch