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@Ben Kaiser "The versions were actually installed", are those installed on the system or part of the output on the bento's requirements.txt? I think with your latest change on the

pip_packages

option, bentoml will just use the versions that's available on your system. Can you set the packages to

torch=1.6.0 and torchvision=0.7.0

and see ?

if I do not pin the versions in the python file then bentoml will output

bentoml==0.13.1
imageio
torch==1.10.0
botocore==1.23.20
torchvision==0.11.0

and docker build will fail with the dependency conflicts if I pin the versions via

@bentoml.env(pip_packages=["torch==1.6.0", "torchvision==0.7.0"])

then I get some dependency conflict again (I don’t have the exact error at the moment but this case doesn’t convey anything about the issue I am describing either) if I pin the versions via

@bentoml.env(pip_packages=["torch>=1.6.0", "torchvision>=0.7.0"])

then bentoml will output

bentoml==0.13.1
imageio
torch>=1.6.0
botocore==1.23.20
torchvision>=0.7.0

and docker will successfully build the image with the following versions installed

torch==1.10.0
torchvision==0.11.1

----- I am fine pinning the version but I feel it is a bug that if I leave the dependency version selection up to bentoml it will select incompatible/conflicting versions

@Ben Kaiser Yeah I think this is something we should improve on a lot. With the 1.0 version it will be more straight forward and remove the guessing game like this from the current version.