[distributed_dp] Including package versions into the requirements file #57
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Hi @fraboeni, Thanks for your interest! I just tried locally cloning the repo and starting a new conda environment, and I was able to get it running using the following commands: The specific versions of the related packages: It seems that nightly builds are not needed but you would need |
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Thank you so much for your help with that @kenziyuliu. Now, I am running into different errors: I ran The issue did not occur when specifying the flags as in your example: This started very promising, then I got a different error: Tried fixing that with disabling GPU execution by inserting the following lines here: federated/distributed_dp/fl_run.py Line 33 in ed50f1e and simply re-ran the command. However, the error stayed the same. Would I have to do some re-build, or can you recommend me another way to get rid of the error resulting from tff? Thank you very much! |
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@fraboeni Can you see what happens if you try toggling this line: federated/distributed_dp/fl_run.py Line 251 in ed50f1e For context, the client training that is part of |
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Also for context @kenziyuliu I believe the nightly TFF packages are currently broken. I believe that using the latest version is the recommended way to proceed (as in your comment above). |
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Thanks for your prompt answer @zcharles8! Unfortunately, no matter if I set the indicated line to True or False, I still get the same error. |
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@fraboeni Is that true if you don't add the call to For context, I just ran the command you posted above (purely on CPU) and it worked fine using the default executor. |
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Oh wait, I see the potential problem. @fraboeni It sounds like you are using a multi-GPU environment based on the error. If that is the case then you would need to alter this line: https://github.com/google-research/federated/blob/master/distributed_dp/fl_run.py#L266 In particular, set |
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Thank you very much @zcharles8. Unfortunately, passing the parameter in the line you indicated also does not solve the issue: I also tried switching off GPUs by Or only using one GPU by that command. Unfortunately, nothing seems to change the error. |
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Hi @zcharles8, are there any news from your side on how we could make the code here run? |
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Hi @fraboeni, I tried following #57 (comment) on a single-GPU machine, and by default things seem to work fine. Specifically, I followed #57 (comment), fixed the error in #58, and checked that TF sees the GPU as Running the example script from here seems to work ( |
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Can anyone help me solve the same issue while using |
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Could you please expand more on where exactly you are doing? Are you creating a custom iterative process or using one that we are providing in the repo? Could you also please provide a snippet for the error you are seeing? |
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Hi everyone,
First on all, thank you very much for providing the very nice distributed_dp package.
I was trying to get it to work, and installed the packages referenced in https://github.com/google-research/federated/blob/master/distributed_dp/requirements.txt. Unfortunately, even though I installed the nightly build versions of all the packages as indicated in the README, there seem to be compatibility issues.
I've tried a couple of different combinations of versions for tf, tf-federated, tf-privacy, tf-estimator, but the code was running in none of them.
My current setup is
In this setup, I get the error
when running
bazel run :fl_runMy question now is the following: could you share version numbers in your requirement.txt file for which the code is successfully running?
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