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long-running-resume.yaml
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long-running-resume.yaml
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---
apiVersion: kubeflow.org/v1beta1
kind: Experiment
metadata:
namespace: kubeflow
name: long-running-resume
spec:
objective:
type: minimize
goal: 0.001
objectiveMetricName: loss
algorithm:
algorithmName: random
parallelTrialCount: 3
maxTrialCount: 12
maxFailedTrialCount: 3
resumePolicy: LongRunning
parameters:
- name: lr
parameterType: double
feasibleSpace:
min: "0.01"
max: "0.05"
- name: momentum
parameterType: double
feasibleSpace:
min: "0.5"
max: "0.9"
trialTemplate:
primaryContainerName: training-container
trialParameters:
- name: learningRate
description: Learning rate for the training model
reference: lr
- name: momentum
description: Momentum for the training model
reference: momentum
trialSpec:
apiVersion: batch/v1
kind: Job
spec:
template:
spec:
containers:
- name: training-container
image: docker.io/kubeflowkatib/pytorch-mnist-cpu:latest
command:
- "python3"
- "/opt/pytorch-mnist/mnist.py"
- "--epochs=1"
- "--batch-size=16"
- "--lr=${trialParameters.learningRate}"
- "--momentum=${trialParameters.momentum}"
restartPolicy: Never