examples/named_entity_recognition/components/deploy/component.yaml

44 lines
1.6 KiB
YAML

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