Error when trying to train yolov8 model

[vrathi101]

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Question

I followed the Ultralytics documentation online for using YoloV8 for training an object detection model but keep experiencing the following issue. This is the code I ran:

os.chdir('/kaggle/working')
!pip uninstall -y ultralytics
!pip cache purge
!pip install -U ultralytics
from ultralytics import YOLO
model = YOLO("yolov8s.pt")
results = model.train(
data="/kaggle/working/data.yaml", epochs=20,
imgsz=640, batch=-1, save=True
)

I previously installed ultralytics so here I just uninstalled and reinstalled it. the model loads properly but whenever I try training it I get the following error:

---

FileNotFoundError Traceback (most recent call last)
Cell In[27], line 1
----> 1 results = model.train(
2 data="/kaggle/working/data.yaml", epochs=20,
3 imgsz=640, batch=-1, save=True
4 )

File /opt/conda/lib/python3.10/site-packages/ultralytics/yolo/engine/model.py:189, in YOLO.train(self, **kwargs)
186 if overrides.get("resume"):
187 overrides["resume"] = self.ckpt_path
--> 189 self.trainer = self.TrainerClass(overrides=overrides)
190 if not overrides.get("resume"): # manually set model only if not resuming
191 self.trainer.model = self.trainer.get_model(weights=self.model if self.ckpt else None, cfg=self.model.yaml)

File /opt/conda/lib/python3.10/site-packages/ultralytics/yolo/engine/trainer.py:86, in init(self, config, overrides)

File /opt/conda/lib/python3.10/site-packages/ultralytics/yolo/configs/init.py:25, in get_config(config, overrides)

File /opt/conda/lib/python3.10/site-packages/omegaconf/omegaconf.py:189, in OmegaConf.load(file_)
186 from .utils import get_yaml_loader
188 if isinstance(file, (str, pathlib.Path)):
--> 189 with io.open(os.path.abspath(file_), "r", encoding="utf-8") as f:
190 obj = yaml.load(f, Loader=get_yaml_loader())
191 elif getattr(file_, "read", None):

FileNotFoundError: [Errno 2] No such file or directory: '/opt/conda/lib/python3.10/site-packages/ultralytics/yolo/configs/default.yaml'

[github-actions]

👋 Hello @vrathi101, thank you for your interest in Ultralytics YOLOv8 🚀! We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.

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Install

Pip install the ultralytics package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.

pip install ultralytics

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[Y-T-G]

Just restart the notebook kernel

[vrathi101]

I tried that but now am getting this error:
AttributeError: module 'torch.amp' has no attribute 'GradScaler'

---

AttributeError Traceback (most recent call last)
Cell In[5], line 1
----> 1 results = model.train(
2 data="/kaggle/working/data.yaml", epochs=20,
3 imgsz=640, batch=-1, save=True
4 )

File /opt/conda/lib/python3.10/site-packages/ultralytics/engine/model.py:810, in Model.train(self, trainer, **kwargs)
807 self.model = self.trainer.model
809 self.trainer.hub_session = self.session # attach optional HUB session
--> 810 self.trainer.train()
811 # Update model and cfg after training
812 if RANK in {-1, 0}:

File /opt/conda/lib/python3.10/site-packages/ultralytics/engine/trainer.py:206, in BaseTrainer.train(self)
203 ddp_cleanup(self, str(file))
205 else:
--> 206 self._do_train(world_size)

File /opt/conda/lib/python3.10/site-packages/ultralytics/engine/trainer.py:329, in BaseTrainer._do_train(self, world_size)
327 if world_size > 1:
328 self._setup_ddp(world_size)
--> 329 self._setup_train(world_size)
331 nb = len(self.train_loader) # number of batches
332 nw = max(round(self.args.warmup_epochs * nb), 100) if self.args.warmup_epochs > 0 else -1 # warmup iterations

File /opt/conda/lib/python3.10/site-packages/ultralytics/engine/trainer.py:270, in BaseTrainer._setup_train(self, world_size)
267 dist.broadcast(self.amp, src=0) # broadcast the tensor from rank 0 to all other ranks (returns None)
268 self.amp = bool(self.amp) # as boolean
269 self.scaler = (
--> 270 torch.amp.GradScaler("cuda", enabled=self.amp)
271 if TORCH_1_13
272 else torch.cuda.amp.GradScaler(enabled=self.amp)
273 )
274 if world_size > 1:
275 self.model = nn.parallel.DistributedDataParallel(self.model, device_ids=[RANK], find_unused_parameters=True)

AttributeError: module 'torch.amp' has no attribute 'GradScaler'

[vrathi101]

yes that worked, thank you!

[Laughing-q]

@vrathi101 closing the issue as it's resolved, please feel free to reopen it if you encounter any related issues. :)