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baszalmstra avatar baszalmstra commented on August 17, 2024 1

Yeah I think its actually still a bug. It looks like mkl 2023.*.* is parsed as mkl[version="2023.*", build=".*"]. I think it should become mkl[version="2023.*"].

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baszalmstra avatar baszalmstra commented on August 17, 2024 1

You're welcome, I appreciate the thorough tests! I just set in motion the release of py-rattler 0.6.1 which should include these fixes.

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wolfv avatar wolfv commented on August 17, 2024

Just did a little test, and this line also fails:

asyncio.run(rattler.solve([rattler.Channel("main")], ["binutils_impl_linux-64=2.38.0.*"], platforms=["linux-64", "noarch"], virtual_packages=virtual_packages))

I'll do some more testing.

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wolfv avatar wolfv commented on August 17, 2024

So it seems like you might have found a bug 🎉 ! - micromamba (and probably conda?) do select 2.38 when asking for 2.38.0 which makes sense.

We should fix that in rattler.

Thanks!

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baszalmstra avatar baszalmstra commented on August 17, 2024

Thanks for the thorough tests!

I think I have a fix for this in #686

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JeanChristopheMorinPerso avatar JeanChristopheMorinPerso commented on August 17, 2024

I'm having a similar problem with pytorch, more precisely

  • pytorch=2.2.0=cpu_py38hdc00b08_0
  • pytorch=2.2.0=cpu_py312hb9e5694_0
  • pytorch=2.2.0=cpu_py310hdc00b08_0
  • pytorch=2.2.0=cpu_py311h6d93b4c_0
  • pytorch=2.2.0=cpu_py39hdc00b08_0

where I get

Failed to resolve pytorch=2.2.0=cpu_py38hdc00b08_0 (0.0691 secs): Cannot solve the request because of: pytorch ==2.2.0 cpu_py38hdc00b08_0 cannot be installed because there are no viable options:
└─ pytorch 2.2.0 would require
   └─ mkl 2023.* .*, for which no candidates were found.

Could this be the same problem?

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wolfv avatar wolfv commented on August 17, 2024

For the MKL issue I found the line. It says: mkl 2023.*.* in the dependencies.

I think that's not really valid - if you would want to express the constraint like that, IMO it should be a regex.

Maybe we should strip everything after the first starts_with operator.

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wolfv avatar wolfv commented on August 17, 2024
Screenshot 2024-05-28 at 07 35 23 Excerpt from the repodata.

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baszalmstra avatar baszalmstra commented on August 17, 2024

#688 should fix the issue with mkl

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baszalmstra avatar baszalmstra commented on August 17, 2024
cargo run -- create --dry-run --platform linux-64 pytorch=2.2.0=cpu_py38hdc00b08_0 -c main --virtual-package __glibc=2.17=0 --virtual-package __archspec=1=x86_64 --virtual-package __unix=0=0 --virtual-package __linux=0=0

Shows that this is indeed solvable with #688

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JeanChristopheMorinPerso avatar JeanChristopheMorinPerso commented on August 17, 2024

Thank you for the fixes!

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JeanChristopheMorinPerso avatar JeanChristopheMorinPerso commented on August 17, 2024

Just tested and it seems to be working for both cases! Thanks again!

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