Closed samuela closed 2 years ago
numba
is not declared as a dependency, but is necessary.Good catch @samuela. Some should definitely be removed. However:
numba
to be in the python dependencies as we recommend using it with conda. It includes packages that improve performance over the pip
version.Do you want to make a PR ?
I don't have bandwidth to submit a PR atm, but hopefully recording these things here will be useful for someone in the future.
Another one:
Having the packages required for to run examples was to make it easier for newcomers to just try the library by running the examples and not having to figure out what else they need to install. Do you think it's a bad idea.
I would propose having separate dependency lists for the core library, benchmarks, and tests. For example, check out how flax does it here: https://github.com/google/flax/blob/main/setup.py.
The thing here is that we want to make it as easy for people to run the experiments. If we add an extra step it will already put a lot of people off using it :/
I improved the list in the next release. Reopen if you have another suggestion :)
sklearn
is declared as a dependency here. But this should likely bescikit-learn
. Also it does not appear to be used anywhere in the actual ffcv source.matplotlib
is declared as a dependency here but does not appear to be used anywhere in the actual ffcv source.fastargs
is declared as a dependency here but is only used in the cifar example code.imgcat
is declared as a dependency here but is not used in the actual ffcv source.assertpy
is declared as a dependency here but is only used in the tests and benchmarks.psutil
is declared as a dependency here but is only used in the tests.webdataset
is declared as a dependency here, but is identified as optional in the code.