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Fixes #8697 GPU memory leak by checking both image and label tensors for CUDA device #8708

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Fixes #8697 GPU memory leak by checking both image and label tensors for CUDA device #8708

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Fixes #8697 GPU memory leak by checking both image and label tensors …
benediktjohannes Jan 17, 2026
f8cc9ff
Forgot to define variables, thanks coderabbitai for the information
benediktjohannes Jan 17, 2026
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13 changes: 6 additions & 7 deletions monai/auto3dseg/analyzer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -468,21 +468,20 @@ def __call__(self, data: Mapping[Hashable, MetaTensor]) -> dict[Hashable, MetaTe
"""
d: dict[Hashable, MetaTensor] = dict(data)
start = time.time()
if isinstance(d[self.image_key], (torch.Tensor, MetaTensor)) and d[self.image_key].device.type == "cuda":
using_cuda = True
else:
using_cuda = False
image_tensor = d[self.image_key]
label_tensor = d[self.label_key]
using_cuda = any(isinstance(t, torch.Tensor) and t.device.type == "cuda" for t in (image_tensor, label_tensor))
restore_grad_state = torch.is_grad_enabled()
torch.set_grad_enabled(False)

ndas: list[MetaTensor] = [d[self.image_key][i] for i in range(d[self.image_key].shape[0])] # type: ignore
ndas_label: MetaTensor = d[self.label_key].astype(torch.int16) # (H,W,D)
ndas: list[MetaTensor] = [image_tensor[i] for i in range(image_tensor.shape[0])] # type: ignore
ndas_label: MetaTensor = label_tensor.astype(torch.int16) # (H,W,D)

if ndas_label.shape != ndas[0].shape:
raise ValueError(f"Label shape {ndas_label.shape} is different from image shape {ndas[0].shape}")

nda_foregrounds: list[torch.Tensor] = [get_foreground_label(nda, ndas_label) for nda in ndas]
nda_foregrounds = [nda if nda.numel() > 0 else torch.Tensor([0]) for nda in nda_foregrounds]
nda_foregrounds = [nda if nda.numel() > 0 else MetaTensor([0.0]) for nda in nda_foregrounds]

unique_label = unique(ndas_label)
if isinstance(ndas_label, (MetaTensor, torch.Tensor)):
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