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| apiVersion: argoproj.io/v1alpha1 | |
| kind: Workflow | |
| metadata: | |
| generateName: end-to-end-pipeline- | |
| annotations: {pipelines.kubeflow.org/kfp_sdk_version: 1.4.0, pipelines.kubeflow.org/pipeline_compilation_time: '2021-05-19T18:07:07.922414', | |
| pipelines.kubeflow.org/pipeline_spec: '{"description": "An end to end mnist example | |
| including hyperparameter tuning, train and inference", "inputs": [{"default": | |
| "mnist-e2e-2", "name": "name", "optional": true}, {"default": "profile-ref10", | |
| "name": "namespace", "optional": true}, {"default": "200", "name": "training_steps", | |
| "optional": true}], "name": "End to End Pipeline"}'} | |
| labels: {pipelines.kubeflow.org/kfp_sdk_version: 1.4.0} | |
| spec: | |
| entrypoint: end-to-end-pipeline | |
| templates: | |
| - name: convert-katib-results | |
| container: | |
| args: [--katib-results, '{{inputs.parameters.katib-launch-experiment-Best-Parameter-Set}}', | |
| '----output-paths', /tmp/outputs/Output/data] | |
| command: | |
| - sh | |
| - -ec | |
| - | | |
| program_path=$(mktemp) | |
| printf "%s" "$0" > "$program_path" | |
| python3 -u "$program_path" "$@" | |
| - | | |
| def convert_katib_results(katib_results): | |
| import json | |
| import pprint | |
| katib_results_json = json.loads(katib_results) | |
| print("Katib results:") | |
| pprint.pprint(katib_results_json) | |
| best_hps = [] | |
| for pa in katib_results_json["currentOptimalTrial"]["parameterAssignments"]: | |
| if pa["name"] == "learning_rate": | |
| best_hps.append("--tf-learning-rate=" + pa["value"]) | |
| elif pa["name"] == "batch_size": | |
| best_hps.append("--tf-batch-size=" + pa["value"]) | |
| print("Best Hyperparameters: {}".format(best_hps)) | |
| return " ".join(best_hps) | |
| def _serialize_str(str_value: str) -> str: | |
| if not isinstance(str_value, str): | |
| raise TypeError('Value "{}" has type "{}" instead of str.'.format(str(str_value), str(type(str_value)))) | |
| return str_value | |
| import argparse | |
| _parser = argparse.ArgumentParser(prog='Convert katib results', description='') | |
| _parser.add_argument("--katib-results", dest="katib_results", type=str, required=True, default=argparse.SUPPRESS) | |
| _parser.add_argument("----output-paths", dest="_output_paths", type=str, nargs=1) | |
| _parsed_args = vars(_parser.parse_args()) | |
| _output_files = _parsed_args.pop("_output_paths", []) | |
| _outputs = convert_katib_results(**_parsed_args) | |
| _outputs = [_outputs] | |
| _output_serializers = [ | |
| _serialize_str, | |
| ] | |
| import os | |
| for idx, output_file in enumerate(_output_files): | |
| try: | |
| os.makedirs(os.path.dirname(output_file)) | |
| except OSError: | |
| pass | |
| with open(output_file, 'w') as f: | |
| f.write(_output_serializers[idx](_outputs[idx])) | |
| image: python:3.7 | |
| inputs: | |
| parameters: | |
| - {name: katib-launch-experiment-Best-Parameter-Set} | |
| outputs: | |
| parameters: | |
| - name: convert-katib-results-Output | |
| valueFrom: {path: /tmp/outputs/Output/data} | |
| artifacts: | |
| - {name: convert-katib-results-Output, path: /tmp/outputs/Output/data} | |
| metadata: | |
| annotations: {pipelines.kubeflow.org/component_spec: '{"implementation": {"container": | |
| {"args": ["--katib-results", {"inputValue": "katib_results"}, "----output-paths", | |
| {"outputPath": "Output"}], "command": ["sh", "-ec", "program_path=$(mktemp)\nprintf | |
| \"%s\" \"$0\" > \"$program_path\"\npython3 -u \"$program_path\" \"$@\"\n", | |
| "def convert_katib_results(katib_results):\n import json\n import | |
| pprint\n katib_results_json = json.loads(katib_results)\n print(\"Katib | |
| results:\")\n pprint.pprint(katib_results_json)\n best_hps = []\n for | |
| pa in katib_results_json[\"currentOptimalTrial\"][\"parameterAssignments\"]:\n if | |
| pa[\"name\"] == \"learning_rate\":\n best_hps.append(\"--tf-learning-rate=\" | |
| + pa[\"value\"])\n elif pa[\"name\"] == \"batch_size\":\n best_hps.append(\"--tf-batch-size=\" | |
| + pa[\"value\"])\n print(\"Best Hyperparameters: {}\".format(best_hps))\n return | |
| \" \".join(best_hps)\n\ndef _serialize_str(str_value: str) -> str:\n if | |
| not isinstance(str_value, str):\n raise TypeError(''Value \"{}\" | |
| has type \"{}\" instead of str.''.format(str(str_value), str(type(str_value))))\n return | |
| str_value\n\nimport argparse\n_parser = argparse.ArgumentParser(prog=''Convert | |
| katib results'', description='''')\n_parser.add_argument(\"--katib-results\", | |
| dest=\"katib_results\", type=str, required=True, default=argparse.SUPPRESS)\n_parser.add_argument(\"----output-paths\", | |
| dest=\"_output_paths\", type=str, nargs=1)\n_parsed_args = vars(_parser.parse_args())\n_output_files | |
| = _parsed_args.pop(\"_output_paths\", [])\n\n_outputs = convert_katib_results(**_parsed_args)\n\n_outputs | |
| = [_outputs]\n\n_output_serializers = [\n _serialize_str,\n\n]\n\nimport | |
| os\nfor idx, output_file in enumerate(_output_files):\n try:\n os.makedirs(os.path.dirname(output_file))\n except | |
| OSError:\n pass\n with open(output_file, ''w'') as f:\n f.write(_output_serializers[idx](_outputs[idx]))\n"], | |
| "image": "python:3.7"}}, "inputs": [{"name": "katib_results"}], "name": | |
| "Convert katib results", "outputs": [{"name": "Output", "type": "String"}]}', | |
| pipelines.kubeflow.org/component_ref: '{}', pipelines.kubeflow.org/arguments.parameters: '{"katib_results": | |
| "{{inputs.parameters.katib-launch-experiment-Best-Parameter-Set}}"}'} | |
| - name: end-to-end-pipeline | |
| inputs: | |
| parameters: | |
| - {name: name} | |
| - {name: namespace} | |
| - {name: training_steps} | |
| dag: | |
| tasks: | |
| - name: convert-katib-results | |
| template: convert-katib-results | |
| dependencies: [katib-launch-experiment] | |
| arguments: | |
| parameters: | |
| - {name: katib-launch-experiment-Best-Parameter-Set, value: '{{tasks.katib-launch-experiment.outputs.parameters.katib-launch-experiment-Best-Parameter-Set}}'} | |
| - name: katib-launch-experiment | |
| template: katib-launch-experiment | |
| arguments: | |
| parameters: | |
| - {name: name, value: '{{inputs.parameters.name}}'} | |
| - {name: namespace, value: '{{inputs.parameters.namespace}}'} | |
| - {name: training_steps, value: '{{inputs.parameters.training_steps}}'} | |
| - name: kubeflow-launch-tfjob | |
| template: kubeflow-launch-tfjob | |
| dependencies: [convert-katib-results, model-volume] | |
| arguments: | |
| parameters: | |
| - {name: convert-katib-results-Output, value: '{{tasks.convert-katib-results.outputs.parameters.convert-katib-results-Output}}'} | |
| - {name: model-volume-name, value: '{{tasks.model-volume.outputs.parameters.model-volume-name}}'} | |
| - {name: name, value: '{{inputs.parameters.name}}'} | |
| - {name: namespace, value: '{{inputs.parameters.namespace}}'} | |
| - {name: training_steps, value: '{{inputs.parameters.training_steps}}'} | |
| - name: kubeflow-serve-model-using-kfserving | |
| template: kubeflow-serve-model-using-kfserving | |
| dependencies: [kubeflow-launch-tfjob, model-volume] | |
| arguments: | |
| parameters: | |
| - {name: model-volume-name, value: '{{tasks.model-volume.outputs.parameters.model-volume-name}}'} | |
| - {name: name, value: '{{inputs.parameters.name}}'} | |
| - {name: namespace, value: '{{inputs.parameters.namespace}}'} | |
| - {name: model-volume, template: model-volume} | |
| - name: katib-launch-experiment | |
| container: | |
| args: | |
| - --experiment-name | |
| - '{{inputs.parameters.name}}' | |
| - --experiment-namespace | |
| - '{{inputs.parameters.namespace}}' | |
| - --experiment-spec | |
| - '{"algorithm": {"algorithmName": "random"}, "maxFailedTrialCount": 3, "maxTrialCount": | |
| 5, "objective": {"goal": 0.001, "objectiveMetricName": "loss", "type": "minimize"}, | |
| "parallelTrialCount": 2, "parameters": [{"feasibleSpace": {"max": "0.05", | |
| "min": "0.01"}, "name": "learning_rate", "parameterType": "double"}, {"feasibleSpace": | |
| {"max": "100", "min": "80"}, "name": "batch_size", "parameterType": "int"}], | |
| "trialTemplate": {"primaryContainerName": "tensorflow", "trialParameters": | |
| [{"description": "Learning rate for the training model", "name": "learningRate", | |
| "reference": "learning_rate"}, {"description": "Batch size for the model", | |
| "name": "batchSize", "reference": "batch_size"}], "trialSpec": {"apiVersion": | |
| "kubeflow.org/v1", "kind": "TFJob", "spec": {"tfReplicaSpecs": {"Chief": {"replicas": | |
| 1, "restartPolicy": "OnFailure", "template": {"metadata": {"annotations": | |
| {"sidecar.istio.io/inject": "false"}}, "spec": {"containers": [{"command": | |
| ["python", "/opt/model.py", "--tf-train-steps={{inputs.parameters.training_steps}}", | |
| "--tf-learning-rate=${trialParameters.learningRate}", "--tf-batch-size=${trialParameters.batchSize}"], | |
| "image": "docker.io/liuhougangxa/tf-estimator-mnist", "name": "tensorflow"}]}}}, | |
| "Worker": {"replicas": 1, "restartPolicy": "OnFailure", "template": {"metadata": | |
| {"annotations": {"sidecar.istio.io/inject": "false"}}, "spec": {"containers": | |
| [{"command": ["python", "/opt/model.py", "--tf-train-steps={{inputs.parameters.training_steps}}", | |
| "--tf-learning-rate=${trialParameters.learningRate}", "--tf-batch-size=${trialParameters.batchSize}"], | |
| "image": "docker.io/liuhougangxa/tf-estimator-mnist", "name": "tensorflow"}]}}}}}}}}' | |
| - --experiment-timeout-minutes | |
| - '60' | |
| - --delete-after-done | |
| - "False" | |
| - --output-file | |
| - /tmp/outputs/Best_Parameter_Set/data | |
| command: [python, src/launch_experiment.py] | |
| image: docker.io/kubeflowkatib/kubeflow-pipelines-launcher | |
| inputs: | |
| parameters: | |
| - {name: name} | |
| - {name: namespace} | |
| - {name: training_steps} | |
| outputs: | |
| parameters: | |
| - name: katib-launch-experiment-Best-Parameter-Set | |
| valueFrom: {path: /tmp/outputs/Best_Parameter_Set/data} | |
| artifacts: | |
| - {name: katib-launch-experiment-Best-Parameter-Set, path: /tmp/outputs/Best_Parameter_Set/data} | |
| metadata: | |
| annotations: {pipelines.kubeflow.org/component_spec: '{"description": "Katib | |
| Experiment launcher", "implementation": {"container": {"args": ["--experiment-name", | |
| {"inputValue": "Experiment Name"}, "--experiment-namespace", {"inputValue": | |
| "Experiment Namespace"}, "--experiment-spec", {"inputValue": "Experiment | |
| Spec"}, "--experiment-timeout-minutes", {"inputValue": "Experiment Timeout | |
| Minutes"}, "--delete-after-done", {"inputValue": "Delete Finished Experiment"}, | |
| "--output-file", {"outputPath": "Best Parameter Set"}], "command": ["python", | |
| "src/launch_experiment.py"], "image": "docker.io/kubeflowkatib/kubeflow-pipelines-launcher"}}, | |
| "inputs": [{"default": "", "description": "Experiment name", "name": "Experiment | |
| Name", "type": "String"}, {"default": "anonymous", "description": "Experiment | |
| namespace", "name": "Experiment Namespace", "type": "String"}, {"default": | |
| "{}", "description": "Experiment specification in dict format", "name": | |
| "Experiment Spec", "type": "JsonObject"}, {"default": 1440, "description": | |
| "Time in minutes to wait for the Experiment to complete", "name": "Experiment | |
| Timeout Minutes", "type": "Integer"}, {"default": "True", "description": | |
| "Whether to delete the Experiment after it is finished", "name": "Delete | |
| Finished Experiment", "type": "Bool"}], "name": "Katib - Launch Experiment", | |
| "outputs": [{"description": "The hyperparameter set of the best Experiment | |
| Trial", "name": "Best Parameter Set", "type": "JsonObject"}]}', pipelines.kubeflow.org/component_ref: '{"digest": | |
| "a93c64b052e810a0d0d0ada3f28a03b3e45e5a3e3bf03272d4bf6c67d5e14bac", "url": | |
| "https://raw.githubusercontent.com/kubeflow/pipelines/master/components/kubeflow/katib-launcher/component.yaml"}', | |
| pipelines.kubeflow.org/arguments.parameters: '{"Delete Finished Experiment": | |
| "False", "Experiment Name": "{{inputs.parameters.name}}", "Experiment Namespace": | |
| "{{inputs.parameters.namespace}}", "Experiment Spec": "{\"algorithm\": {\"algorithmName\": | |
| \"random\"}, \"maxFailedTrialCount\": 3, \"maxTrialCount\": 5, \"objective\": | |
| {\"goal\": 0.001, \"objectiveMetricName\": \"loss\", \"type\": \"minimize\"}, | |
| \"parallelTrialCount\": 2, \"parameters\": [{\"feasibleSpace\": {\"max\": | |
| \"0.05\", \"min\": \"0.01\"}, \"name\": \"learning_rate\", \"parameterType\": | |
| \"double\"}, {\"feasibleSpace\": {\"max\": \"100\", \"min\": \"80\"}, \"name\": | |
| \"batch_size\", \"parameterType\": \"int\"}], \"trialTemplate\": {\"primaryContainerName\": | |
| \"tensorflow\", \"trialParameters\": [{\"description\": \"Learning rate | |
| for the training model\", \"name\": \"learningRate\", \"reference\": \"learning_rate\"}, | |
| {\"description\": \"Batch size for the model\", \"name\": \"batchSize\", | |
| \"reference\": \"batch_size\"}], \"trialSpec\": {\"apiVersion\": \"kubeflow.org/v1\", | |
| \"kind\": \"TFJob\", \"spec\": {\"tfReplicaSpecs\": {\"Chief\": {\"replicas\": | |
| 1, \"restartPolicy\": \"OnFailure\", \"template\": {\"metadata\": {\"annotations\": | |
| {\"sidecar.istio.io/inject\": \"false\"}}, \"spec\": {\"containers\": [{\"command\": | |
| [\"python\", \"/opt/model.py\", \"--tf-train-steps={{inputs.parameters.training_steps}}\", | |
| \"--tf-learning-rate=${trialParameters.learningRate}\", \"--tf-batch-size=${trialParameters.batchSize}\"], | |
| \"image\": \"docker.io/liuhougangxa/tf-estimator-mnist\", \"name\": \"tensorflow\"}]}}}, | |
| \"Worker\": {\"replicas\": 1, \"restartPolicy\": \"OnFailure\", \"template\": | |
| {\"metadata\": {\"annotations\": {\"sidecar.istio.io/inject\": \"false\"}}, | |
| \"spec\": {\"containers\": [{\"command\": [\"python\", \"/opt/model.py\", | |
| \"--tf-train-steps={{inputs.parameters.training_steps}}\", \"--tf-learning-rate=${trialParameters.learningRate}\", | |
| \"--tf-batch-size=${trialParameters.batchSize}\"], \"image\": \"docker.io/liuhougangxa/tf-estimator-mnist\", | |
| \"name\": \"tensorflow\"}]}}}}}}}}", "Experiment Timeout Minutes": "60"}'} | |
| - name: kubeflow-launch-tfjob | |
| container: | |
| args: | |
| - --name | |
| - '{{inputs.parameters.name}}' | |
| - --namespace | |
| - '{{inputs.parameters.namespace}}' | |
| - --version | |
| - v1 | |
| - --activeDeadlineSeconds | |
| - '-1' | |
| - --backoffLimit | |
| - '-1' | |
| - --cleanPodPolicy | |
| - Running | |
| - --ttlSecondsAfterFinished | |
| - '-1' | |
| - --psSpec | |
| - '{}' | |
| - --workerSpec | |
| - '{"replicas": 1, "restartPolicy": "OnFailure", "template": {"metadata": {"annotations": | |
| {"sidecar.istio.io/inject": "false"}}, "spec": {"containers": [{"name": "tensorflow", | |
| "image": "docker.io/liuhougangxa/tf-estimator-mnist", "command": ["sh", "-c"], | |
| "args": ["python /opt/model.py --tf-export-dir=/mnt/export --tf-train-steps={{inputs.parameters.training_steps}} | |
| {{inputs.parameters.convert-katib-results-Output}}"]}]}}}' | |
| - --chiefSpec | |
| - '{"replicas": 1, "restartPolicy": "OnFailure", "template": {"metadata": {"annotations": | |
| {"sidecar.istio.io/inject": "false"}}, "spec": {"containers": [{"name": "tensorflow", | |
| "image": "docker.io/liuhougangxa/tf-estimator-mnist", "command": ["sh", "-c"], | |
| "args": ["python /opt/model.py --tf-export-dir=/mnt/export --tf-train-steps={{inputs.parameters.training_steps}} | |
| {{inputs.parameters.convert-katib-results-Output}}"], "volumeMounts": [{"mountPath": | |
| "/mnt/export", "name": "model-volume"}]}], "volumes": [{"name": "model-volume", | |
| "persistentVolumeClaim": {"claimName": "{{inputs.parameters.model-volume-name}}"}}]}}}' | |
| - --evaluatorSpec | |
| - '{}' | |
| - --tfjobTimeoutMinutes | |
| - '60' | |
| - --deleteAfterDone | |
| - "True" | |
| command: [python, /ml/launch_tfjob.py] | |
| image: nikenano/launchernew:latest | |
| inputs: | |
| parameters: | |
| - {name: convert-katib-results-Output} | |
| - {name: model-volume-name} | |
| - {name: name} | |
| - {name: namespace} | |
| - {name: training_steps} | |
| metadata: | |
| annotations: {pipelines.kubeflow.org/component_spec: '{"description": "Kubeflow | |
| TFJob launcher", "implementation": {"container": {"args": ["--name", {"inputValue": | |
| "Name"}, "--namespace", {"inputValue": "Namespace"}, "--version", {"inputValue": | |
| "Version"}, "--activeDeadlineSeconds", {"inputValue": "ActiveDeadlineSeconds"}, | |
| "--backoffLimit", {"inputValue": "BackoffLimit"}, "--cleanPodPolicy", {"inputValue": | |
| "CleanPodPolicy"}, "--ttlSecondsAfterFinished", {"inputValue": "ttl Seconds | |
| After Finished"}, "--psSpec", {"inputValue": "PS Spec"}, "--workerSpec", | |
| {"inputValue": "Worker Spec"}, "--chiefSpec", {"inputValue": "Chief Spec"}, | |
| "--evaluatorSpec", {"inputValue": "Evaluator Spec"}, "--tfjobTimeoutMinutes", | |
| {"inputValue": "Tfjob Timeout Minutes"}, "--deleteAfterDone", {"inputValue": | |
| "Delete Finished Tfjob"}], "command": ["python", "/ml/launch_tfjob.py"], | |
| "image": "nikenano/launchernew:latest"}}, "inputs": [{"description": "TFJob | |
| name.", "name": "Name", "type": "String"}, {"default": "kubeflow", "description": | |
| "TFJob namespace.", "name": "Namespace", "type": "String"}, {"default": | |
| "v1", "description": "TFJob version.", "name": "Version", "type": "String"}, | |
| {"default": -1, "description": "Specifies the duration (in seconds) since | |
| startTime during which the job can remain active before it is terminated. | |
| Must be a positive integer. This setting applies only to pods where restartPolicy | |
| is OnFailure or Always.", "name": "ActiveDeadlineSeconds", "type": "Integer"}, | |
| {"default": -1, "description": "Number of retries before marking this job | |
| as failed.", "name": "BackoffLimit", "type": "Integer"}, {"default": -1, | |
| "description": "Defines the TTL for cleaning up finished TFJobs.", "name": | |
| "ttl Seconds After Finished", "type": "Integer"}, {"default": "Running", | |
| "description": "Defines the policy for cleaning up pods after the TFJob | |
| completes.", "name": "CleanPodPolicy", "type": "String"}, {"default": "{}", | |
| "description": "TFJob ps replicaSpecs.", "name": "PS Spec", "type": "JsonObject"}, | |
| {"default": "{}", "description": "TFJob worker replicaSpecs.", "name": "Worker | |
| Spec", "type": "JsonObject"}, {"default": "{}", "description": "TFJob chief | |
| replicaSpecs.", "name": "Chief Spec", "type": "JsonObject"}, {"default": | |
| "{}", "description": "TFJob evaluator replicaSpecs.", "name": "Evaluator | |
| Spec", "type": "JsonObject"}, {"default": 1440, "description": "Time in | |
| minutes to wait for the TFJob to complete.", "name": "Tfjob Timeout Minutes", | |
| "type": "Integer"}, {"default": "True", "description": "Whether to delete | |
| the tfjob after it is finished.", "name": "Delete Finished Tfjob", "type": | |
| "Bool"}], "name": "Kubeflow - Launch TFJob"}', pipelines.kubeflow.org/component_ref: '{"digest": | |
| "98fd1829c0a5ff1b36c53bc2a8d6482d33a7a5dc042e2ee661840be06065c325", "url": | |
| "https://raw.githubusercontent.com/kubeflow/pipelines/master/components/kubeflow/launcher/component.yaml"}', | |
| pipelines.kubeflow.org/arguments.parameters: '{"ActiveDeadlineSeconds": "-1", | |
| "BackoffLimit": "-1", "Chief Spec": "{\"replicas\": 1, \"restartPolicy\": | |
| \"OnFailure\", \"template\": {\"metadata\": {\"annotations\": {\"sidecar.istio.io/inject\": | |
| \"false\"}}, \"spec\": {\"containers\": [{\"name\": \"tensorflow\", \"image\": | |
| \"docker.io/liuhougangxa/tf-estimator-mnist\", \"command\": [\"sh\", \"-c\"], | |
| \"args\": [\"python /opt/model.py --tf-export-dir=/mnt/export --tf-train-steps={{inputs.parameters.training_steps}} | |
| {{inputs.parameters.convert-katib-results-Output}}\"], \"volumeMounts\": | |
| [{\"mountPath\": \"/mnt/export\", \"name\": \"model-volume\"}]}], \"volumes\": | |
| [{\"name\": \"model-volume\", \"persistentVolumeClaim\": {\"claimName\": | |
| \"{{inputs.parameters.model-volume-name}}\"}}]}}}", "CleanPodPolicy": "Running", | |
| "Delete Finished Tfjob": "True", "Evaluator Spec": "{}", "Name": "{{inputs.parameters.name}}", | |
| "Namespace": "{{inputs.parameters.namespace}}", "PS Spec": "{}", "Tfjob | |
| Timeout Minutes": "60", "Version": "v1", "Worker Spec": "{\"replicas\": | |
| 1, \"restartPolicy\": \"OnFailure\", \"template\": {\"metadata\": {\"annotations\": | |
| {\"sidecar.istio.io/inject\": \"false\"}}, \"spec\": {\"containers\": [{\"name\": | |
| \"tensorflow\", \"image\": \"docker.io/liuhougangxa/tf-estimator-mnist\", | |
| \"command\": [\"sh\", \"-c\"], \"args\": [\"python /opt/model.py --tf-export-dir=/mnt/export | |
| --tf-train-steps={{inputs.parameters.training_steps}} {{inputs.parameters.convert-katib-results-Output}}\"]}]}}}", | |
| "ttl Seconds After Finished": "-1"}'} | |
| - name: kubeflow-serve-model-using-kfserving | |
| container: | |
| args: | |
| - -u | |
| - kfservingdeployer.py | |
| - --action | |
| - create | |
| - --model-name | |
| - '' | |
| - --model-uri | |
| - '' | |
| - --canary-traffic-percent | |
| - '100' | |
| - --namespace | |
| - '' | |
| - --framework | |
| - '' | |
| - --custom-model-spec | |
| - '{}' | |
| - --autoscaling-target | |
| - '0' | |
| - --service-account | |
| - '' | |
| - --enable-istio-sidecar | |
| - "True" | |
| - --output-path | |
| - /tmp/outputs/InferenceService_Status/data | |
| - --inferenceservice-yaml | |
| - |2 | |
| apiVersion: "serving.kubeflow.org/v1beta1" | |
| kind: "InferenceService" | |
| metadata: | |
| name: {{inputs.parameters.name}} | |
| namespace: {{inputs.parameters.namespace}} | |
| annotations: | |
| "sidecar.istio.io/inject": "false" | |
| spec: | |
| predictor: | |
| tensorflow: | |
| storageUri: "pvc://{{inputs.parameters.model-volume-name}}/" | |
| - --watch-timeout | |
| - '300' | |
| - --min-replicas | |
| - '-1' | |
| - --max-replicas | |
| - '-1' | |
| - --request-timeout | |
| - '60' | |
| command: [python] | |
| image: quay.io/aipipeline/kfserving-component:v0.5.1 | |
| inputs: | |
| parameters: | |
| - {name: model-volume-name} | |
| - {name: name} | |
| - {name: namespace} | |
| outputs: | |
| artifacts: | |
| - {name: kubeflow-serve-model-using-kfserving-InferenceService-Status, path: /tmp/outputs/InferenceService_Status/data} | |
| metadata: | |
| annotations: {pipelines.kubeflow.org/component_spec: '{"description": "Serve | |
| Models using Kubeflow KFServing", "implementation": {"container": {"args": | |
| ["-u", "kfservingdeployer.py", "--action", {"inputValue": "Action"}, "--model-name", | |
| {"inputValue": "Model Name"}, "--model-uri", {"inputValue": "Model URI"}, | |
| "--canary-traffic-percent", {"inputValue": "Canary Traffic Percent"}, "--namespace", | |
| {"inputValue": "Namespace"}, "--framework", {"inputValue": "Framework"}, | |
| "--custom-model-spec", {"inputValue": "Custom Model Spec"}, "--autoscaling-target", | |
| {"inputValue": "Autoscaling Target"}, "--service-account", {"inputValue": | |
| "Service Account"}, "--enable-istio-sidecar", {"inputValue": "Enable Istio | |
| Sidecar"}, "--output-path", {"outputPath": "InferenceService Status"}, "--inferenceservice-yaml", | |
| {"inputValue": "InferenceService YAML"}, "--watch-timeout", {"inputValue": | |
| "Watch Timeout"}, "--min-replicas", {"inputValue": "Min Replicas"}, "--max-replicas", | |
| {"inputValue": "Max Replicas"}, "--request-timeout", {"inputValue": "Request | |
| Timeout"}], "command": ["python"], "image": "quay.io/aipipeline/kfserving-component:v0.5.1"}}, | |
| "inputs": [{"default": "create", "description": "Action to execute on KFServing", | |
| "name": "Action", "type": "String"}, {"default": "", "description": "Name | |
| to give to the deployed model", "name": "Model Name", "type": "String"}, | |
| {"default": "", "description": "Path of the S3 or GCS compatible directory | |
| containing the model.", "name": "Model URI", "type": "String"}, {"default": | |
| "100", "description": "The traffic split percentage between the candidate | |
| model and the last ready model", "name": "Canary Traffic Percent", "type": | |
| "String"}, {"default": "", "description": "Kubernetes namespace where the | |
| KFServing service is deployed.", "name": "Namespace", "type": "String"}, | |
| {"default": "", "description": "Machine Learning Framework for Model Serving.", | |
| "name": "Framework", "type": "String"}, {"default": "{}", "description": | |
| "Custom model runtime container spec in JSON", "name": "Custom Model Spec", | |
| "type": "String"}, {"default": "0", "description": "Autoscaling Target Number", | |
| "name": "Autoscaling Target", "type": "String"}, {"default": "", "description": | |
| "ServiceAccount to use to run the InferenceService pod", "name": "Service | |
| Account", "type": "String"}, {"default": "True", "description": "Whether | |
| to enable istio sidecar injection", "name": "Enable Istio Sidecar", "type": | |
| "Bool"}, {"default": "{}", "description": "Raw InferenceService serialized | |
| YAML for deployment", "name": "InferenceService YAML", "type": "String"}, | |
| {"default": "300", "description": "Timeout seconds for watching until InferenceService | |
| becomes ready.", "name": "Watch Timeout", "type": "String"}, {"default": | |
| "-1", "description": "Minimum number of InferenceService replicas", "name": | |
| "Min Replicas", "type": "String"}, {"default": "-1", "description": "Maximum | |
| number of InferenceService replicas", "name": "Max Replicas", "type": "String"}, | |
| {"default": "60", "description": "Specifies the number of seconds to wait | |
| before timing out a request to the component.", "name": "Request Timeout", | |
| "type": "String"}], "name": "Kubeflow - Serve Model using KFServing", "outputs": | |
| [{"description": "Status JSON output of InferenceService", "name": "InferenceService | |
| Status", "type": "String"}]}', pipelines.kubeflow.org/component_ref: '{"digest": | |
| "84f27d18805744db98e4d08804ea3c0e6ca5daa1a3a90dd057b5323f19d9dd2c", "url": | |
| "https://raw.githubusercontent.com/kubeflow/pipelines/master/components/kubeflow/kfserving/component.yaml"}', | |
| pipelines.kubeflow.org/arguments.parameters: '{"Action": "create", "Autoscaling | |
| Target": "0", "Canary Traffic Percent": "100", "Custom Model Spec": "{}", | |
| "Enable Istio Sidecar": "True", "Framework": "", "InferenceService YAML": | |
| "\napiVersion: \"serving.kubeflow.org/v1beta1\"\nkind: \"InferenceService\"\nmetadata:\n name: | |
| {{inputs.parameters.name}}\n namespace: {{inputs.parameters.namespace}}\n annotations:\n \"sidecar.istio.io/inject\": | |
| \"false\"\nspec:\n predictor:\n tensorflow:\n storageUri: \"pvc://{{inputs.parameters.model-volume-name}}/\"\n", | |
| "Max Replicas": "-1", "Min Replicas": "-1", "Model Name": "", "Model URI": | |
| "", "Namespace": "", "Request Timeout": "60", "Service Account": "", "Watch | |
| Timeout": "300"}'} | |
| - name: model-volume | |
| resource: | |
| action: create | |
| manifest: | | |
| apiVersion: v1 | |
| kind: PersistentVolumeClaim | |
| metadata: | |
| name: '{{workflow.name}}-model-volume' | |
| spec: | |
| accessModes: | |
| - ReadWriteOnce | |
| resources: | |
| requests: | |
| storage: 1Gi | |
| outputs: | |
| parameters: | |
| - name: model-volume-manifest | |
| valueFrom: {jsonPath: '{}'} | |
| - name: model-volume-name | |
| valueFrom: {jsonPath: '{.metadata.name}'} | |
| - name: model-volume-size | |
| valueFrom: {jsonPath: '{.status.capacity.storage}'} | |
| arguments: | |
| parameters: | |
| - {name: name, value: mnist-e2e-2} | |
| - {name: namespace, value: profile-ref10} | |
| - {name: training_steps, value: '200'} | |
| serviceAccountName: pipeline-runner |
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