covalent-oci-plugin 0.3.0

Covalent OCI Plugin

Covalent is a Pythonic workflow tool used to execute tasks on advanced computing hardware.

This executor plugin interfaces Covalent with Oracle Cloud Infrastructure (OCI). Valid OCI credentials are therefore required for use.

1. Installation

⚠️ If you are just getting started with Covalent, check out the quickstart. We recommend using a virtual environment such as venv or conda to minimize dependency conflicts.

To use this plugin with Covalent, install it using pip:

pip install covalent covalent-oci-plugin

2. Usage Example

The small workflow below demonstrates task execution with the OCI Executor.

In the example, we train a Support Vector Machine (SVM) and use an instance of the executor to execute the train_svm electron on an OCI compute instance. Note that we also use pip dependencies which will pre-install packages required to execute the electrons.

⚠️ Ensure the Covalent server is started before using this script by running covalent start on the command line.

import covalent as ct
from numpy.random import permutation
from sklearn import svm, datasets

deps_pip = ["numpy==1.22.4", "scikit-learn==1.1.2"]

executor = ct.executor.OCIExecutor(
    availability_domain="giLp:US-ASHBURN-AD-1",
    shape="VM.Standard.E2.1",
    compartment_id="ocid1.compartment.oc1..unique-id",
    image_id="ocid1.image.oc1.iad.unique-id",
    subnet_id="ocid1.subnet.oc1.iad.unique-id",
    # ssh_key_file="~/.oci/id_rsa",
)

# Use executor plugin to train our SVM model
@ct.electron(
    executor=executor,
    deps_pip=deps_pip
)
def train_svm(data, C, gamma):
    X, y = data
    clf = svm.SVC(C=C, gamma=gamma)
    clf.fit(X[90:], y[90:])
    return clf

# When no executor is attached, the task runs locally
@ct.electron
def load_data():
    iris = datasets.load_iris()
    perm = permutation(iris.target.size)
    iris.data = iris.data[perm]
    iris.target = iris.target[perm]
    return iris.data, iris.target

@ct.electron
def score_svm(data, clf):
    X_test, y_test = data
    return clf.score(
    	X_test[:90],y_test[:90]
    )

@ct.lattice
def run_experiment(C=1.0, gamma=0.7):
    data = load_data()
    clf = train_svm(
    	data=data,
	    C=C,
	    gamma=gamma
    )
    score = score_svm(
    	data=data,
	    clf=clf
    )
    return score

# Dispatch the workflow.
dispatch_id = ct.dispatch(run_experiment)(
    C=1.0,
    gamma=0.7
)

# Wait for our result and get result value
result = ct.get_result(dispatch_id, wait=True).result

print(result)

During the execution of the workflow, one can navigate to the UI to see the status of the workflow. Once completed, the above script should also output a value with the score of our model.

0.8666666666666667

Note that some cloud infrastructure must already exists to run the above workflow, as noted in Required OCI Resources.

3. Configuration

There are many configuration options that can be passed in to the class ct.executor.OCIExecutor or by modifying the covalent config file under the section [executors.oci].

For more information about all of the possible configuration values visit our documentation page for this plugin.

4. Required OCI Resources

The required OCI resources must first be provisioned before using this plugin:

1. Virtual cloud network (VCN)
2. Internet gateway
3. Route table
4. Public subnet
5. SSH key
6. API signing key

Covalent's resource deployment feature is very convenient for auto-creating these resources:

covalent deploy up oci --compartment_ocid=<your-compartment-ocid>

For this plugin the compartment ocid is a required parameter. This can be found and chosen from in the OCI console.

For more information, see our documentation page for this plugin.

Getting Started with Covalent

For more information on how to get started with Covalent, check out the project homepage and the official documentation.

Release Notes

Release notes are available in the Changelog.

Citation

Please use the following citation in any publications:

https://doi.org/10.5281/zenodo.5903364

License

Covalent is licensed under the Apache License 2.0. See the LICENSE file or contact the support team for more details.