API driven Machine Learning suite
Project description
enzyme
X-1 ML System anywhwere
Install
OS - Rocky Linux 9. Docker should be installed.
git clone -b x1 https://github.com/aregm/enzyme.git
cd enzyme
./scripts/deploy/kind.sh
What's in Package?
Out of the box X1 will provide an integrated set of Intel-optimized data science libraries:
- Pandas/Modin
- Scikit-Learn/Intel SciKit-Learn Extensions
- XGBoost
- Intel PyTorch Extensions/Intel Tensorflow Extensions
- Ray
- MatplotLib
Quick start
The cluster's endpoints are accessible only from localhost:
- http://dashboard.localtest.me
- http://jupyter.localtest.me
- http://minio.localtest.me
- http://prefect.localtest.me
In your browser, navigate to http://jupyter.localtest.me.
Define a flow
Currently, ICL uses Prefect for defining basic workflow building blocks: flow and tasks.
Create a Python file my_flow.py
that defines a single flow my_flow
:
from prefect import flow
@flow
def my_flow():
print('Hello from my_flow')
Note this is a regular Python file, so it can be developed, tested, and executed locally.
Deploy and run a flow
The following code deploys and runs flow my_flow
in the default infrastructure:
import x1
program = await x1.deploy('my_flow.py')
await program.run()
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