Package: covalent-awsbatch-plugin
Covalent AWS Batch PluginCovalent is a Pythonic workflow tool used to execute tasks on advanced computing hardware.This executor plugin interfaces Covalent withAWS Batchwhich allows tasks in a covalent workflow to be executed as AWS batch jobs.1. InstallationTo use this plugin with Covalent, simply install it usingpip:pip install covalent-awsbatch-plugin2. Usage ExampleThis is an example of how a workflow can be adapted to utilize the AWS Batch Executor. Here we train a simple Support Vector Machine (SVM) model and use an existing AWS Batch Compute environment to run thetrain_svmelectron as a batch job. We also note we requireDepsPipto install the dependencies when creating the batch job.fromnumpy.randomimportpermutationfromsklearnimportsvm,datasetsimportcovalentasctdeps_pip=ct.DepsPip(packages=["numpy==1.23.2","scikit-learn==1.1.2"])executor=ct.executor.AWSBatchExecutor(s3_bucket_name="covalent-batch-qa-job-resources",batch_queue="covalent-batch-qa-queue",batch_execution_role_name="ecsTaskExecutionRole",batch_job_role_name="covalent-batch-qa-job-role",batch_job_log_group_name="covalent-batch-qa-log-group",vcpu=2,# Number of vCPUs to allocatememory=3.75,# Memory in GB to allocatetime_limit=300,# Time limit of job in seconds)# 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 workflowdispatch_id=ct.dispatch(run_experiment)(C=1.0,gamma=0.7)# Wait for our result and get result valueresult=ct.get_result(dispatch_id=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 however the above script should also output a value with the score of our model.0.97777777777777773. ConfigurationThere are many configuration options that can be passed in to the classct.executor.AWSBatchExecutoror by modifying thecovalent config fileunder the section[executors.awsbatch]For more information about all of the possible configuration values visit ourread the docs (RTD) guidefor this plugin.4. Required AWS ResourcesIn order to run your workflows with covalent there are a few notable AWS resources that need to be provisioned first.For more information regarding which cloud resources need to be provisioned visit ourread the docs (RTD) guidefor this plugin.The required AWS resources include a Batch Job Definition, Batch Job Role, Batch Queue, Batch Compute Environment, Log Group, Subnet, VPC, and an S3 Bucket.Getting Started with CovalentFor more information on how to get started with Covalent, check out the projecthomepageand the officialdocumentation.Release NotesRelease notes for this plugin 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 Apache License 2.0. See theLICENSEfile or contact thesupport teamfor more details.