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ultralytics 8.0.37 add TFLite metadata in AutoBackend (#953)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com>
Co-authored-by: Aarni Koskela <akx@iki.fi>
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Glenn Jocher 2023-02-14 14:28:23 +04:00 • committed by GitHub
parent 20fe708f31
commit bdc6cd4d8b
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18 changed files with 86 additions and 46 deletions
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6
ultralytics/yolo/engine/model.py
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@ -108,8 +108,8 @@ class YOLO:
Raises TypeError is model is not a PyTorch model
"""
if not isinstance(self.model, nn.Module):
raise TypeError(f"model='{self.model}' must be a PyTorch model, but is a different type. PyTorch models "
f"can be used to train, val, predict and export, i.e. "
raise TypeError(f"model='{self.model}' must be a *.pt PyTorch model, but is a different type. "
f"PyTorch models can be used to train, val, predict and export, i.e. "
f"'yolo export model=yolov8n.pt', but exported formats like ONNX, TensorRT etc. only "
f"support 'predict' and 'val' modes, i.e. 'yolo predict model=yolov8n.onnx'.")
@ -240,7 +240,7 @@ class YOLO:
if RANK in {0, -1}:
self.model, _ = attempt_load_one_weight(str(self.trainer.best))
self.overrides = self.model.args
self.metrics_data = self.trainer.validator.metrics
self.metrics_data = self.trainer.validator.metrics
def to(self, device):
"""