mirror of https://github.com/kubeflow/examples.git
44 lines
1.6 KiB
YAML
44 lines
1.6 KiB
YAML
name: deploy
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description: Deploy the model with custom prediction route
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inputs:
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- name: Model path
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type: GCSPath
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description: 'Path of GCS directory containing exported Tensorflow model.'
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- name: Model name
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type: String
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description: 'The name specified for the model when it was or get created'
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- name: Model region
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type: String
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description: 'The region where the model is going to be deployed'
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- name: Model version
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type: String
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description: 'The version of the model'
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- name: Model runtime version
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type: String
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description: 'The runtime version of the model'
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- name: Model prediction class
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type: String
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description: 'The runtime version of the model'
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- name: Model python version
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type: String
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description: 'The python version of the model'
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- name: Model package uris
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type: String
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description: 'The packge uri of the model'
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outputs:
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implementation:
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container:
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image: gcr.io/<PROJECT-ID>/kubeflow/ner/deploy:latest
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command: [
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sh, /pipelines/component/src/deploy.sh
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]
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args: [
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--model-path, {inputValue: Model path},
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--model-name, {inputValue: Model name},
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--model-region, {inputValue: Model region},
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--model-version, {inputValue: Model version},
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--model-runtime-version, {inputValue: Model runtime version},
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--model-prediction-class, {inputValue: Model prediction class},
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--model-python-version, {inputValue: Model python version},
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--model-package-uris, {inputValue: Model package uris},
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] |