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[ aws . machinelearning ]

add-tags

Description

Adds one or more tags to an object, up to a limit of 10. Each tag consists of a key and an optional value. If you add a tag using a key that is already associated with the ML object, AddTags updates the tag's value.

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  add-tags
--tags <value>
--resource-id <value>
--resource-type <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--tags (list)

The key-value pairs to use to create tags. If you specify a key without specifying a value, Amazon ML creates a tag with the specified key and a value of null.

Shorthand Syntax:

Key=string,Value=string ...

JSON Syntax:

[
  {
    "Key": "string",
    "Value": "string"
  }
  ...
]

--resource-id (string)

The ID of the ML object to tag. For example, exampleModelId .

--resource-type (string)

The type of the ML object to tag.

Possible values:

  • BatchPrediction
  • DataSource
  • Evaluation
  • MLModel

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

ResourceId -> (string)

The ID of the ML object that was tagged.

ResourceType -> (string)

The type of the ML object that was tagged.