mirror of https://github.com/kubeflow/examples.git
46 lines
1.3 KiB
Plaintext
46 lines
1.3 KiB
Plaintext
local env = std.extVar("__ksonnet/environments");
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local params = std.extVar("__ksonnet/params").components["create-pet-record-job"];
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local k = import "k.libsonnet";
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// This job converts our dataset to TFRecord format which is what TensorFlow
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// Object Detection API uses
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local createPetRecordJob = {
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apiVersion: "batch/v1",
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kind: "Job",
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metadata: {
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name: params.name,
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namespace: env.namespace,
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},
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spec: {
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template: {
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spec: {
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containers: [{
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name: "create-tf-record",
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image: params.image,
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imagePullPolicy: "IfNotPresent",
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command: ["python", "/models/research/object_detection/dataset_tools/create_pet_tf_record.py"],
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args: ["--label_map_path=/models/research/object_detection/data/pet_label_map.pbtxt",
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"--data_dir=" + params.dataDirPath,
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"--output_dir=" + params.outputDirPath],
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volumeMounts: [{
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mountPath: params.mountPath,
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name: "pets-data",
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},],
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},],
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volumes: [{
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name: "pets-data",
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persistentVolumeClaim: {
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claimName: params.pvc,
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},
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},],
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restartPolicy: "Never",
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},
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},
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backoffLimit: 4,
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},
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};
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std.prune(k.core.v1.list.new([createPetRecordJob,]))
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