83 lines
3.0 KiB
YAML
83 lines
3.0 KiB
YAML
name: 'Sagemaker - Create Model'
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description: |
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Create Models in SageMaker
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inputs:
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- name: region
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description: 'The region where the training job launches.'
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type: String
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- name: model_name
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description: 'The name of the new model.'
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type: String
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- name: role
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description: 'The Amazon Resource Name (ARN) that Amazon SageMaker assumes to perform tasks on your behalf.'
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type: String
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- name: container_host_name
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description: 'When a ContainerDefinition is part of an inference pipeline, this value uniquely identifies the container for the purposes of logging and metrics.'
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default: ''
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type: String
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- name: image
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description: 'The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.'
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default: ''
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type: String
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- name: model_artifact_url
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description: 'S3 path where Amazon SageMaker to store the model artifacts.'
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default: ''
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type: String
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- name: environment
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description: 'The dictionary of the environment variables to set in the Docker container. Up to 16 key-value entries in the map.'
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default: '{}'
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type: JsonObject
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- name: model_package
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description: 'The name or Amazon Resource Name (ARN) of the model package to use to create the model.'
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default: ''
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type: String
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- name: secondary_containers
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description: 'A list of dicts that specifies the additional containers in the inference pipeline.'
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default: '[]'
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type: JsonArray
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- name: vpc_security_group_ids
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description: 'The VPC security group IDs, in the form sg-xxxxxxxx.'
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default: ''
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type: String
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- name: vpc_subnets
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description: 'The ID of the subnets in the VPC to which you want to connect your hpo job.'
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default: ''
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type: String
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- name: network_isolation
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description: 'Isolates the training container.'
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default: 'True'
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type: Bool
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- name: endpoint_url
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description: 'The endpoint URL for the private link VPC endpoint.'
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default: ''
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type: String
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- name: tags
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description: 'Key-value pairs to categorize AWS resources.'
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default: '{}'
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type: JsonObject
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outputs:
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- {name: model_name, description: 'The model name Sagemaker created'}
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implementation:
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container:
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image: amazon/aws-sagemaker-kfp-components:0.5.0
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command: ['python3']
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args: [
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create_model.py,
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--region, {inputValue: region},
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--endpoint_url, {inputValue: endpoint_url},
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--model_name, {inputValue: model_name},
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--role, {inputValue: role},
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--container_host_name, {inputValue: container_host_name},
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--image, {inputValue: image},
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--model_artifact_url, {inputValue: model_artifact_url},
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--environment, {inputValue: environment},
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--model_package, {inputValue: model_package},
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--secondary_containers, {inputValue: secondary_containers},
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--vpc_security_group_ids, {inputValue: vpc_security_group_ids},
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--vpc_subnets, {inputValue: vpc_subnets},
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--network_isolation, {inputValue: network_isolation},
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--tags, {inputValue: tags}
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]
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fileOutputs:
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model_name: /tmp/model_name.txt
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