new check_dataset functions (#43)

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

ultralytics/yolo/engine/trainer.py

@@ -24,7 +24,9 @@ from tqdm import tqdm
 
 import ultralytics.yolo.utils as utils
 import ultralytics.yolo.utils.loggers as loggers
+from ultralytics.yolo.data.utils import check_dataset, check_dataset_yaml
 from ultralytics.yolo.utils import LOGGER, ROOT
+from ultralytics.yolo.utils.checks import check_file, check_yaml
 from ultralytics.yolo.utils.files import increment_path, save_yaml
 from ultralytics.yolo.utils.modeling import get_model
 
@@ -55,9 +57,14 @@ class BaseTrainer:
         self.scaler = amp.GradScaler(enabled=self.device.type != 'cpu')
 
         # Model and Dataloaders.
-        self.trainset, self.testset = self.get_dataset(self.args.data)
+        self.data = self.args.data
+        if self.data.endswith(".yaml"):
+            self.data = check_dataset_yaml(self.data)
+        else:
+            self.data = check_dataset(self.data)
+        self.trainset, self.testset = self.get_dataset(self.data)
         if self.args.cfg is not None:
-            self.model = self.load_cfg(self.args.cfg)
+            self.model = self.load_cfg(check_file(self.args.cfg))
         if self.args.model is not None:
             self.model = self.get_model(self.args.model, self.args.pretrained).to(self.device)
 
@@ -250,10 +257,9 @@ class BaseTrainer:
 
     def get_dataset(self, data):
         """
-        Download the dataset if needed and verify it.
-        Returns train and val split datasets
+        Get train, val path from data dict if it exists. Returns None if data format is not recognized
         """
-        pass
+        return data["train"], data["val"]
 
     def get_model(self, model, pretrained):
         """