Do we need all these inference dependencies?
Closed this issue · 3 comments
PorkShoulderHolder commented
- I see that the install script downloads tensorflow, keras, xgboost, and probably more.
- I imagine these are probably used in some of the examples, but are these strictly necessary? If the idea is for our library to be agnostic to what tools the user prefers, it should probably be more lightweight and not require you to download 250MB of code/data you do not need.
- IRL use-case example: I like PyTorch for DNNs, not tensorflow. If I were to deploy this the build script is gonna be slowed down significantly by the tensorflow requirement even though im not going to use it.
PorkShoulderHolder commented
We could keep the example code in the repo, but have a separate install command for the examples. Or something that you see sometimes is that the required stuff is installed at runtime if the user decides to run one of the examples.
miriamkw commented
Good points, thanks! I will not prioritize this fix atm. I'll leave the issue open until I have some time.