#!/usr/bin/env python3 # Uncomment the apply(use_aws_secret()) below if you are not using OIDC # more info : https://github.com/kubeflow/pipelines/tree/master/samples/contrib/aws-samples/README.md import kfp import os from kfp import components from kfp import dsl import random import string from kfp.aws import use_aws_secret cur_file_dir = os.path.dirname(__file__) components_dir = os.path.join(cur_file_dir, "../../../../components/aws/sagemaker/") robomaker_create_sim_app_op = components.load_component_from_file( components_dir + "/create_simulation_app/component.yaml" ) robomaker_sim_job_op = components.load_component_from_file( components_dir + "/simulation_job/component.yaml" ) robomaker_delete_sim_app_op = components.load_component_from_file( components_dir + "/delete_simulation_app/component.yaml" ) launch_config = { "packageName": "object_tracker_simulation", "launchFile": "evaluation.launch", "environmentVariables": { "MODEL_S3_BUCKET": "your_sagemaker_bucket_name", "MODEL_S3_PREFIX": "rl-object-tracker-sagemaker-201116-051751", "ROS_AWS_REGION": "us-east-1", "MARKOV_PRESET_FILE": "object_tracker.py", "NUMBER_OF_ROLLOUT_WORKERS": "1", }, "streamUI": True, } simulation_app_name = "robomaker-pipeline-simulation-application" sources_bucket = "your_sagemaker_bucket_name" sources_key = "object-tracker/simulation_ws.tar.gz" sources_architecture = "X86_64" simulation_software_name = "Gazebo" simulation_software_version = "7" robot_software_name = "ROS" robot_software_version = "Kinetic" rendering_engine_name = "OGRE" rendering_engine_version = "1.x" role = "your_sagemaker_role_name" output_bucket = "kf-pipelines-robomaker-output" output_key = "test-output-key" security_groups = ["sg-0490601e83f220e82"] subnets = [ "subnet-0efc73526db16a4a4", "subnet-0b8af626f39e7d462", ] @dsl.pipeline( name="RoboMaker Simulation Job Pipeline", description="RoboMaker simulation job and simulation application created via pipeline components", ) def robomaker_simulation_job_app_pipeline( region="us-east-1", role=role, name=simulation_app_name + "".join(random.choice(string.ascii_lowercase) for i in range(10)), sources=[ { "s3Bucket": sources_bucket, "s3Key": sources_key, "architecture": sources_architecture, } ], simulation_software_name=simulation_software_name, simulation_software_version=simulation_software_version, robot_software_name=robot_software_name, robot_software_version=robot_software_version, rendering_engine_name=rendering_engine_name, rendering_engine_version=rendering_engine_version, output_bucket=output_bucket, output_path=output_key, sim_app_launch_config=launch_config, vpc_security_group_ids=security_groups, vpc_subnets=subnets, ): robomaker_create_sim_app = robomaker_create_sim_app_op( region=region, app_name=name, sources=sources, simulation_software_name=simulation_software_name, simulation_software_version=simulation_software_version, robot_software_name=robot_software_name, robot_software_version=robot_software_version, rendering_engine_name=rendering_engine_name, rendering_engine_version=rendering_engine_version, ) # .apply(use_aws_secret('aws-secret', 'AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY')) robomaker_simulation_job = robomaker_sim_job_op( region=region, role=role, output_bucket=output_bucket, output_path=output_path, max_run=300, failure_behavior="Fail", sim_app_arn=robomaker_create_sim_app.outputs["arn"], sim_app_launch_config=sim_app_launch_config, vpc_security_group_ids=vpc_security_group_ids, vpc_subnets=vpc_subnets, use_public_ip="True", ).after(robomaker_create_sim_app) # .apply(use_aws_secret('aws-secret', 'AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY')) robomaker_delete_sim_app = robomaker_delete_sim_app_op( region=region, arn=robomaker_create_sim_app.outputs["arn"], ).after(robomaker_simulation_job, robomaker_create_sim_app) # .apply(use_aws_secret('aws-secret', 'AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY')) if __name__ == "__main__": kfp.compiler.Compiler().compile( robomaker_simulation_job_app_pipeline, __file__ + ".zip" )