aws sagemaker create-flow-definition
Creates a flow definition
Options
| Name | Description |
|---|---|
--flow-definition-name <string> | The name of your flow definition |
--human-loop-request-source <structure> | Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source |
--human-loop-activation-config <structure> | An object containing information about the events that trigger a human workflow |
--human-loop-config <structure> | An object containing information about the tasks the human reviewers will perform |
--output-config <structure> | An object containing information about where the human review results will be uploaded |
--role-arn <string> | The Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298 |
--tags <list> | An array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define |
--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 |