Pip debug fixes (#139)

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

ultralytics/yolo/engine/exporter.py

@@ -156,7 +156,7 @@ class Exporter:
         jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs, paddle = flags  # export booleans
 
         # Load PyTorch model
-        self.device = select_device(self.args.device)
+        self.device = select_device(self.args.device or 'cpu')
         if self.args.half:
             if self.device.type == 'cpu' or not coreml:
                 LOGGER.info('half=True only compatible with GPU or CoreML export, i.e. use device=0 or format=coreml')
@@ -172,7 +172,9 @@ class Exporter:
 
         # Input
         im = torch.zeros(self.args.batch_size, 3, *self.imgsz).to(self.device)
-        file = Path(getattr(model, 'yaml_file', None) or Path(model.yaml['yaml_file']).name)
+        file = Path(getattr(model, 'pt_path', None) or model.yaml['yaml_file'])
+        if file.suffix == '.yaml':
+            file = Path(file.name)
 
         # Update model
         model = deepcopy(model)

ultralytics/yolo/engine/model.py

@@ -213,9 +213,8 @@ class YOLO:
 
     @smart_inference_mode()
     def __call__(self, imgs):
-        if not self.model:
-            LOGGER.info("model not initialized!")
-        return self.model(imgs)
+        device = next(self.model.parameters()).device  # get model device
+        return self.model(imgs.to(device))
 
     def forward(self, imgs):
         return self.__call__(imgs)

ultralytics/yolo/engine/trainer.py

@@ -81,12 +81,11 @@ class BaseTrainer:
             overrides = {}
         self.args = get_config(config, overrides)
         self.check_resume()
-        init_seeds(self.args.seed + 1 + RANK, deterministic=self.args.deterministic)
-
         self.console = LOGGER
         self.validator = None
         self.model = None
         self.callbacks = defaultdict(list)
+        init_seeds(self.args.seed + 1 + RANK, deterministic=self.args.deterministic)
 
         # Dirs
         project = self.args.project or f"runs/{self.args.task}"