Comments (6)
hongzimao
commented on July 27, 2024
Those are deprecation warnings for some variable naming. Should still be fine running the code. IIRC we used tensorflow 1.12 at the time.
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RuifMaxx
commented on July 27, 2024
Thank you very much
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jahidhasanlinix
commented on July 27, 2024
I was trying to run this code after installing all the pkgs correctly, but I am getting this while running train.py, any suggestions on how to resolve it. Thank you.
$ python3 train.py
Using backend: pytorch
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hongzimao
commented on July 27, 2024
This is weird. This repo is built on top of tensorflow. Don't know how pytorch is triggered. Do you have any more output information when running the code?
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jahidhasanlinix
commented on July 27, 2024
No, I did not get any output. I am not sure why, I am just having trouble with running this code so far. Just working on it to make it run. will update you once it is working. Apart from that if you have any suggestions please let me know so I can work on it. And thank you for your response too.
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wwww6555
commented on July 27, 2024
你好，我想问一下代码要求的tensorflow版本是什么呢
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Related Issues (20)
- some questions of your code HOT 9
- The model training issue with reward function optimizing makespan HOT 14
- Updating Tensorflow 1.14 to 2 HOT 3
- About nodes information HOT 1
- A question about the result HOT 5
- some question about the main idea
- Some questions about Decima's GNN HOT 2
- A question about actor_network HOT 2
- Questions about the input vector HOT 2
- Question about multi resource training. HOT 1
- when calculating the reward whether the locality of the data to the core is taken into account? in other word,the data transfer between different nodes may significant affect the reward calculation.
- How to integrate Decima in Spark
- About the model of generation HOT 1
- Question about .npy files
- Some questions about executor
- Code for Learning State Representation
- Could u plz tell me the piplist of this code? HOT 2
- Bug in determining `done` in `env.step`?
- PyTorch Implementation of Decima Available!
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