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Right now the first time a user needs to run torchserve they need to
python install_dependencies.py
pip install torchserve or pip install .
This is confusing to users mostly used to the python ecosystem so how can we fix this? Especially as we move towards a python client like with the recent PR #2751 how can we make it easier to install torchserve within something like a notebook
Our install_dependencies.py is primarily used to install java, nodejs (for dev builds) and wget
We can't completely get rid of the script but we can recommend more users use conda if we think the below is more convenient
Motivation, pitch
The issue is torchserve is not a pure python library and at least within the pip ecosystem there is no way around this, you can't package non python dependencies easily
But you can in conda!
And I have a proof of concept, given this file binaries/conda/torchserve/meta.yaml where all we need to do is add our dependencies under run in the meta.yaml
🚀 The feature
Right now the first time a user needs to run torchserve they need to
This is confusing to users mostly used to the python ecosystem so how can we fix this? Especially as we move towards a python client like with the recent PR #2751 how can we make it easier to install torchserve within something like a notebook
Our
install_dependencies.py
is primarily used to install java, nodejs (for dev builds) and wgetWe can't completely get rid of the script but we can recommend more users use conda if we think the below is more convenient
Motivation, pitch
The issue is torchserve is not a pure python library and at least within the pip ecosystem there is no way around this, you can't package non python dependencies easily
But you can in conda!
And I have a proof of concept, given this file
binaries/conda/torchserve/meta.yaml
where all we need to do is add our dependencies underrun
in themeta.yaml
Build it
Test it
You can see that nodejs, java and wget are all installed
Alternatives
No response
Additional context
No response
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