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AWS::CleanRoomsML::ConfiguredModelAlgorithm ContainerConfig
Provides configuration information for the training container, including entrypoints and arguments.
Syntax
To declare this entity in your CloudFormation template, use the following syntax:
JSON
{ "Arguments" :[ String, ... ], "Entrypoint" :[ String, ... ], "ImageUri" :String, "MetricDefinitions" :[ MetricDefinition, ... ]}
YAML
Arguments:- StringEntrypoint:- StringImageUri:StringMetricDefinitions:- MetricDefinition
Properties
Arguments-
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.
Required: No
Type: Array of String
Minimum:
1 | 1Maximum:
256 | 100Update requires: Replacement
Entrypoint-
The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.
Required: No
Type: Array of String
Minimum:
1 | 1Maximum:
256 | 100Update requires: Replacement
ImageUri-
The registry path of the docker image that contains the algorithm. Clean Rooms ML currently only supports the
registry/repository[:tag]image path format. For more information about using images in Clean Rooms ML, see the Sagemaker API reference.Required: Yes
Type: String
Pattern:
^.*$Minimum:
1Maximum:
255Update requires: Replacement
MetricDefinitions-
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. AWS Clean Rooms ML publishes each metric to all members' Amazon CloudWatch using IAM role configured in PutMLConfiguration.
Required: No
Type: Array of MetricDefinition
Minimum:
0Maximum:
40Update requires: Replacement