Comments (1)
I'm not sure whether it's related to the Issue11 mentioned here. TORCH_USE_CUDA_DSA occurs when the code is attempting to run on a GPU, but the installed PyTorch version, CUDA toolkit, or GPU driver is incompatible with the device's architecture. Here's the environments we've tested on:
Operating System: Ubuntu 22.04 Conda Version: 23.7.4 Python Version: 3.12.4
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Related Issues (20)
- Dataset Format for the Training Task HOT 1
- How to predict? HOT 1
- 请问如何在python3.10下编译运行train_3d.py HOT 1
- installing requirements in kaggle HOT 2
- Is there any available code for inference? HOT 2
- training error HOT 3
- inference error HOT 9
- Details about Experiment on STARE Vessel Dataset HOT 2
- one-shot inference HOT 1
- About video_length? HOT 1
- Question about the 3D segmentation of organs HOT 3
- 是否支持无标签预测? HOT 1
- Is there code for segmentation visualization? HOT 1
- Implementation of weighted pick up strategy and 'confidence-first' HOT 1
- MaskDecoder resolution HOT 4
- Support for One-Prompt segmentation HOT 1
- RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead. HOT 1
- The results that I produced using REFUGE_disc is worse than REFUGE_cup
- 3D训练时loss的梯度更新和参数更新 HOT 1
- predict HOT 1
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