Comments (4)
You can remove the install of Tensorflow in the last line, as this is only required for computing FID values.
That is, remove this line:
Line 24 in de30f54
Thanks, that in combination with using the most recent torchvision
version worked for me.
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I believe this was an error with pytorch, could you try to replace the base docker image such that the first line in the docker image is the following:
FROM nvcr.io/nvidia/pytorch:20.12-py3
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Hello World,
I tried the git version and failed to get it running - details will follow. I also failed with the docker image:
Created wheel for wrapt: filename=wrapt-1.12.1-cp36-cp36m-linux_x86_64.whl size=69696 sha256=bc8b02eb0456bbc2988e59f5ded83f5dea050fa6b382093be8af7e8809f3d18e
Stored in directory: /root/.cache/pip/wheels/32/42/7f/23cae9ff6ef66798d00dc5d659088e57dbba01566f6c60db63
Successfully built gast wrapt
Installing collected packages: google-pasta, tensorboard, keras-applications, keras-preprocessing, gast, tensorflow-estimator, astor, wrapt, opt-einsum, tensorflow
ERROR: thinc 6.12.1 has requirement msgpack<0.6.0,>=0.5.6, but you'll have msgpack 0.6.1 which is incompatible.
ERROR: thinc 6.12.1 has requirement wrapt<1.11.0,>=1.10.0, but you'll have wrapt 1.12.1 which is incompatible.
Attempting uninstall: tensorboard
Found existing installation: tensorboard 2.1.0
Uninstalling tensorboard-2.1.0:
Successfully uninstalled tensorboard-2.1.0
Attempting uninstall: wrapt
Found existing installation: wrapt 1.10.11
ERROR: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
The command '/bin/sh -c pip install tensorflow==1.15' returned a non-zero code: 1
I assume that the docker image does not specify the required version numbers for some of the packages.
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You can remove the install of Tensorflow in the last line, as this is only required for computing FID values.
That is, remove this line:
Line 24 in de30f54
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Related Issues (20)
- Reproducing GCPR results HOT 5
- Train model from scratch with different facial keypoints HOT 10
- image resolution
- output image resolution HOT 1
- Different results on same input HOT 1
- Training on custom dataset with custom mask for Inpainting HOT 1
- ImportError: cannot import name 'compare_ssim' from 'skimage.measure' HOT 2
- Problem with command line HOT 2
- docker build fails 401 Unauthorized HOT 1
- Docker build fails: missing cuda HOT 8
- how to train HOT 1
- The result of the face swap is scary HOT 1
- Cannot load GCPR checkpoint for config E, pretrained on Places2. HOT 1
- Partial bounding boxes HOT 2
- Train from scratch with FDF dataset HOT 16
- Anonymization failed HOT 1
- Face Detector in Config HOT 1
- something wrong with interactive demo HOT 2
- video output problems HOT 1
- face demo problem
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