Package: covalent-awslambda-plugin
Covalent AWS Lambda PluginCovalent is a Pythonic workflow tool used to execute tasks on advanced computing hardware. This executor plugin interfaces Covalent withAWS Lambdafor dispatching computational tasks.1. InstallationTo use this plugin with Covalent, install it usingpip:pipinstallcovalent-awslambda-plugin2. Usage ExampleThis is an example of how a workflow can be constructed to use the AWS Lambda executor.
In the example, we train a Support Vector Machine (SVM) and use an instance of the executor
to execute thetrain_svmelectron. Note that we also requireDepsPipwhich will be required to execute the electrons.TheAWSLambdaExecutorrequires a container based AWS lambda function to already have been created in the user's AWS account with itsContainer image URIconfigured properly. Users can use Covalent's public Lambda executor registry i.e.public.ecr.aws/covalent/covalent-lambda-executor:stablewhen creating their Lambda functions.
This public ECR registry holds the base container image the lambda function can use to execute tasks from a workflow.User's can pass in the name of their Lambda function to the constructor using thefunction_nameargument. See ourdocumentationfor more details.fromnumpy.randomimportpermutationfromsklearnimportsvm,datasetsimportcovalentasctdeps_pip=ct.DepsPip(packages=["numpy==1.23.2","scikit-learn==1.1.2"])executor=ct.executor.AWSLambdaExecutor(function_name="my-lambda-function",s3_bucket_name="covalent-lambda-job-resources",)# Use executor plugin to train our SVM model.@ct.electron(executor=executor,deps_pip=deps_pip)deftrain_svm(data,C,gamma):X,y=dataclf=svm.SVC(C=C,gamma=gamma)clf.fit(X[90:],y[90:])returnclf@ct.electrondefload_data():iris=datasets.load_iris()perm=permutation(iris.target.size)iris.data=iris.data[perm]iris.target=iris.target[perm]returniris.data,iris.target@ct.electrondefscore_svm(data,clf):X_test,y_test=datareturnclf.score(X_test[:90],y_test[:90])@ct.latticedefrun_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)returnscore# Dispatch the workflow.dispatch_id=ct.dispatch(run_experiment)(C=1.0,gamma=0.7)# Wait for our result and get result valueresult=ct.get_result(dispatch_id,wait=True).resultprint(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.0.8666666666666667In order for the above workflow to run successfully, one has to provision the required cloud resources as mentioned in the sectionRequired AWS Resources.3. ConfigurationThere are many configuration options that can be passed into thect.executor.AWSLambdaExecutorclass or by modifying thecovalent config fileunder the section[executors.awslambda]For more information about all of the possible configuration values, visit ourread the docs (RTD) guidefor this plugin.4. Required AWS ResourcesIn order for workflows to leverage this executor, users must ensure that all the necessary IAM permissions are properly setup and configured. This executor uses theS3andAWS Lambdaservices to execute an electron, thus the required IAM roles and policies must be configured correctly. Precisely, the following resources are needed for the executor to run any dispatched electrons properly.ResourceConfig NameDescriptionIAM Rolelambda_role_nameThe IAM role this lambda will assume during execution of your tasksS3 Buckets3_bucket_nameThe name of the S3 bucket that the executor can use to store temporary filesAWS Lambdafunction_nameName of the pre-configured AWS Lambda function use to run tasksFor exact details on how the above resources can be provisioned, visit ourread the docs (RTD) guidefor this plugin.Getting Started with CovalentFor more information on how to get started with Covalent, check out the projecthomepageand the officialdocumentation.Release NotesRelease notes are available in theChangelog.CitationPlease use the following citation in any publications:W. J. Cunningham, S. K. Radha, F. Hasan, J. Kanem, S. W. Neagle, and S. Sanand.Covalent.Zenodo, 2022.https://doi.org/10.5281/zenodo.5903364LicenseCovalent is licensed under the GNU Affero GPL 3.0 License. Covalent may be distributed under other licenses upon request. See theLICENSEfile or contact thesupport teamfor more details.