Comments (5)
The version of cudatoolkit is 10.1.168, while pytorch1.3 is build with cuda 10.1.243. Maybe this is the problem live in.
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I think you can easily verify that it does not take more than 1 minute on colab, so this should be an environment issue.
What looks problematic in your environment is that your version of pytorch is not built with the compute compatibility for P100. In that case when some ops are run for the first time nvidia-driver will spend some time compiling them. Running it the second time on the same machine should be faster.
Running the code you showed also needs to download 178MB of model for the first time. This is fast on colab, but may be slow on your machine.
AttributeError: 'NoneType' object has no attribute 'shape'
It is saying that opencv cannot read the input image you gave. You may need to check your input path or the opencv installation.
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Similar reports have been seen in #27 and pytorch/pytorch#537. You need to find a version of pytorch whose "NVCC architecture flags" include the compute compatibility of your GPU.
Closing as the issue is about pytorch installation.
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Has been fixed in pytorch according to #27
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Thank you very much for the help! I can confirm that the Conda version of PyTorch from last week wasn't properly compiled to support my GPU. This has been fixed and the newest PyTorch version downloaded via Conda works error-free.
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Related Issues (20)
- export_model.py crashes with keypoints HOT 1
- export_model.py crashes with keypoints HOT 9
- Very slow training on Apple M1 Pro HOT 2
- UnpicklingError: invalid load key, '\xef'. HOT 2
- export_model.py - list_of_lines[165] = " [1344, 1344], 1344 \n" HOT 1
- Please read & provide the following HOT 2
- The comits you are making are breaking the code!!! HOT 1
- @torch.compiler.disable - AttributeError: module 'torch' has no attribute 'compiler' HOT 7
- missing config key error HOT 2
- Please read & provide the following HOT 1
- Detectron2 about rotated object detection HOT 1
- AttributeError: Cannot find field 'gt_masks' in the given Instances! HOT 1
- DensePose的apply_net.py运行dump的选项时候,如何多gpu运行呢? HOT 1
- Encountered freezing during start training at iteration 0 HOT 2
- printing label name and bbox coordinates of predicted images
- Add device argument for multi-backends access & Ascend NPU support HOT 3
- How to convert densepose model to onnx? HOT 1
- 模型跑出来的效果超出预期
- Does this project support FCOS? HOT 1
- C++ and onnx HOT 2
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