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create argo workflow template for autoad
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DockerizedAutoAD/run.sh

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@@ -5,4 +5,6 @@ docker run -it --rm --platform=linux/amd64 automlad
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# julia --project -- ./main.jl -c low -t classification -f 3 -w 3 iris.csv
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# julia --project -- ./main.jl -c low -t anomalydetection iris.csv
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# podman run -it --rm --platform=linux/amd64 localhost/automlai -u http://spendor2.sl.cloud9.ibm.com:30412 iris.csv
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podman run -it --rm --platform=linux/amd64 localhost/automlad -u http://spendor3.sl.cloud9.ibm.com:30412 ../AutoAD/data/node_cpu_ratio_rate_5m_1d_1m.csv
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# podman run -it --rm --platform=linux/amd64 localhost/automlad -u http://spendor3.sl.cloud9.ibm.com:30412 ../AutoAD/data/node_cpu_ratio_rate_5m_1d_1m.csv
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# argo -n argo submit --from clusterworkflowtemplate/automlad-template -p votepercent=0.0 -p input=node_cpu_ratio_rate_5m_1d_1m.csv -p predictiontype=anomalydetection --watch --log
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# docker run -it --rm --platform=linux/amd64 -v ${HOME}/phome/julia/AutoMLPipeline.jl/AutoAD/data/:/data/ ppalmes/automlad:v2.0 -v 0.0 -u http://mlflow.isiath.duckdns.org:8082 /data/node_cpu_ratio_rate_5m_1d_1m.csv
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apiVersion: argoproj.io/v1alpha1
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kind: ClusterWorkflowTemplate
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metadata:
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name: automlad-template
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spec:
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entrypoint: run-automlad
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arguments:
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parameters:
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- name: url
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value: http://sunrise-mlflow-tracking.mlflow:5080
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- name: predictiontype
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value: anomalydetection
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- name: input
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value: node_cpu_ratio.csv
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- name: outputloc
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value: NONE
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- name: votepercent
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value: 0.0
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- name: runid
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value: NONE
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templates:
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- name: run-automlad
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inputs:
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parameters:
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- name: url
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- name: predictiontype
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- name: input
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- name: outputloc
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- name: votepercent
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- name: runid
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artifacts:
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- name: file
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path: /inputfile
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s3:
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key: csv/
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container:
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image: ppalmes/automlad:v2.0
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command:
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args:
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- "-u{{inputs.parameters.url}}"
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- "-t{{inputs.parameters.predictiontype}}"
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- "-v{{inputs.parameters.votepercent}}"
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- "-o/outputfile"
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- "/inputfile/{{inputs.parameters.input}}"

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