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Add warning when cache_ram works with classify (#14650)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Laughing 2024-07-24 18:07:38 +08:00 • committed by GitHub
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ultralytics/data/dataset.py
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@ -431,6 +431,12 @@ class ClassificationDataset:
self.samples = self.samples[: round(len(self.samples) * args.fraction)] self.samples = self.samples[: round(len(self.samples) * args.fraction)]
self.prefix = colorstr(f"{prefix}: ") if prefix else "" self.prefix = colorstr(f"{prefix}: ") if prefix else ""
self.cache_ram = args.cache is True or str(args.cache).lower() == "ram" # cache images into RAM self.cache_ram = args.cache is True or str(args.cache).lower() == "ram" # cache images into RAM
if self.cache_ram:
LOGGER.warning(
"WARNING ⚠️ Classification `cache_ram` training has known memory leak in "
"https://github.com/ultralytics/ultralytics/issues/9824, setting `cache_ram=False`."
)
self.cache_ram = False
self.cache_disk = str(args.cache).lower() == "disk" # cache images on hard drive as uncompressed *.npy files self.cache_disk = str(args.cache).lower() == "disk" # cache images on hard drive as uncompressed *.npy files
self.samples = self.verify_images() # filter out bad images self.samples = self.verify_images() # filter out bad images
self.samples = [list(x) + [Path(x[0]).with_suffix(".npy"), None] for x in self.samples] # file, index, npy, im self.samples = [list(x) + [Path(x[0]).with_suffix(".npy"), None] for x in self.samples] # file, index, npy, im