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I do not see immediately see an issue. Locking may just take a while. You may find some useful information in #6409. In Poetry 2.0, you will have the following option: https://python-poetry.org/docs/main/dependency-specification/#extra-environment-marker |
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@radoering : After waiting for a longer time, it locked, but the additional nvidia-packages necessary for the gpu-version are still installed (and therefore blow up the image significantly). The additional environmental markers might be an option, but have to be tested after poetry 2.0 has been released. |
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I have a poetry-based project I'd like to pack into a docker image. For that, I use the following docker script:
However, as my project contains
pytorch
with CUDA, the resulting image has a size of > 8 GByte, much larger than what is supported by my repository. Therefore, I want to switch out my CUDA-based torch with a CPU-basedtorch
build, but only in the docker-image. As my current implementation oftorch
inpyproject.toml
is defined asthe idea was to replace the package names and -url with the cpu-based url before creating the docker image, using
However, this then results in a stuck
poetry
-loop while building the image. Is this the right way of switching, or is there another way I could solve my issue of the image being too large?Beta Was this translation helpful? Give feedback.
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