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Some issues with installing the package #12
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Thanks for reporting this! It appears that my last commit on master broke the build indeed.
To be clear, isn't it a common practice for projects that are not supposed to be used as dependencies themselves to include a Manifest file so as to pin all dependencies to specific versions?
I will do this and fix the master branch later today. Thanks again! |
Deleting the Manifest (and resolving some old versions of packages I had) was sufficient to get I noticed that Flux support is commented out. Would be nice to avoid installing unnecessary packages in the Project.toml. |
Actually I had to add CuArrays.jl to make it work. I seem to have a bad state of dependencies, but I do have it running, and I had to add CuArrays for it. You're right that Manifests are good for reproducibility, but the Manifest right now has a hardcoded path causing things to fail. Especially for folks in the community who want to poke around the package, the ability to add it and dev it is nice. |
The tests did not run successfully:
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Wiped out
If I wipe the Manifest.toml, it then goes through. I do however think that the Project.toml may not need to have CUDAapi and CuArrays - that CUDA.jl should be sufficient going forward so long as it is lower bounded correctly. |
Another thing I noticed is - does the package need both JSON2 and JSON3 as direct dependencies? |
I think I use JSON2 for its pretty printing function, which did not exist in JSON3 last time I checked. |
Are the tests are failing because I don't have Knet set up correctly for GPUs? Is a GPU a must for running the code?
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AlphaZero.jl is supposed to work in the absence of a GPU. |
Yes, I am using master. If the package has a registered version in the General repo, I should use that, but I just started with the suggestion in the README. I do have a GPU with CUDA libraries, but haven't compiled the Knet for CUDA just yet - if that is required. I thought it would be good to try out the package without GPU first, get its tests working, and then try the CUDA version. |
As you said, your version of Knet is not compiled for CUDA. |
Fixed. |
Thanks for fixing so quickly! The tests are now passing on mac and linux for me. On to the GPU next. Is this expected that there are different numbers of tests? Perhaps I have some optional packages installed on one system and not the other? Anyways, I just thought I would mention it since I saw it. On Linux:
On Mac:
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Yes, the number of tests is nondeterministic right now as it depends on the length of a random simulated game. :-) |
Trying to get GPU support in Knet working, but running into some issues, which I have filed upstream: denizyuret/Knet.jl#568 Just mentioning it here for anyone who might run into it in the future. |
I first tried the instructions in the README, but they fail due to the hardcoded paths in the Manifest.
The package ships a Manifest as well as a Project.toml. I think it would be sufficient to ship just the Project.toml. In fact I had to delete the Manifest to get it to correctly
dev
. The Manifest has some hardcoded paths on the author's computer.The text was updated successfully, but these errors were encountered: