public static interface AlgorithmSpecification.Builder extends SdkPojo, CopyableBuilder<AlgorithmSpecification.Builder,AlgorithmSpecification>
| Modifier and Type | Method and Description |
|---|---|
AlgorithmSpecification.Builder |
algorithmName(String algorithmName)
The name of the algorithm resource to use for the training job.
|
AlgorithmSpecification.Builder |
containerArguments(Collection<String> containerArguments)
The arguments for a container used to run a training job.
|
AlgorithmSpecification.Builder |
containerArguments(String... containerArguments)
The arguments for a container used to run a training job.
|
AlgorithmSpecification.Builder |
containerEntrypoint(Collection<String> containerEntrypoint)
The entrypoint script for a Docker container
used to run a training job.
|
AlgorithmSpecification.Builder |
containerEntrypoint(String... containerEntrypoint)
The entrypoint script for a Docker container
used to run a training job.
|
AlgorithmSpecification.Builder |
enableSageMakerMetricsTimeSeries(Boolean enableSageMakerMetricsTimeSeries)
To generate and save time-series metrics during training, set to
true. |
AlgorithmSpecification.Builder |
metricDefinitions(Collection<MetricDefinition> metricDefinitions)
A list of metric definition objects.
|
AlgorithmSpecification.Builder |
metricDefinitions(Consumer<MetricDefinition.Builder>... metricDefinitions)
A list of metric definition objects.
|
AlgorithmSpecification.Builder |
metricDefinitions(MetricDefinition... metricDefinitions)
A list of metric definition objects.
|
AlgorithmSpecification.Builder |
trainingImage(String trainingImage)
The registry path of the Docker image that contains the training algorithm.
|
default AlgorithmSpecification.Builder |
trainingImageConfig(Consumer<TrainingImageConfig.Builder> trainingImageConfig)
The configuration to use an image from a private Docker registry for a training job.
|
AlgorithmSpecification.Builder |
trainingImageConfig(TrainingImageConfig trainingImageConfig)
The configuration to use an image from a private Docker registry for a training job.
|
AlgorithmSpecification.Builder |
trainingInputMode(String trainingInputMode)
Sets the value of the TrainingInputMode property for this object.
|
AlgorithmSpecification.Builder |
trainingInputMode(TrainingInputMode trainingInputMode)
Sets the value of the TrainingInputMode property for this object.
|
equalsBySdkFields, sdkFieldscopyapplyMutation, buildAlgorithmSpecification.Builder trainingImage(String trainingImage)
The registry path of the Docker image that contains the training algorithm. For information about docker
registry paths for SageMaker built-in algorithms, see Docker
Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both
registry/repository[:tag] and registry/repository[@digest] image path formats. For
more information about using your custom training container, see Using Your Own Algorithms with
Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of
the algorithm container to the TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter description.
trainingImage - The registry path of the Docker image that contains the training algorithm. For information about
docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker
supports both registry/repository[:tag] and registry/repository[@digest]
image path formats. For more information about using your custom training container, see Using Your Own Algorithms
with Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName parameter or the image
URI of the algorithm container to the TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter description.
AlgorithmSpecification.Builder algorithmName(String algorithmName)
The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of
the algorithm container to the TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the TrainingImage
parameter. If you specify a value for the AlgorithmName parameter, you can't specify a value for
TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you don't specify any value for
both parameters, the training job might raise a null error.
algorithmName - The name of the algorithm resource to use for the training job. This must be an algorithm resource
that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName parameter or the image
URI of the algorithm container to the TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the
TrainingImage parameter. If you specify a value for the AlgorithmName
parameter, you can't specify a value for TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you don't specify any
value for both parameters, the training job might raise a null error.
AlgorithmSpecification.Builder trainingInputMode(String trainingInputMode)
trainingInputMode - The new value for the TrainingInputMode property for this object.TrainingInputMode,
TrainingInputModeAlgorithmSpecification.Builder trainingInputMode(TrainingInputMode trainingInputMode)
trainingInputMode - The new value for the TrainingInputMode property for this object.TrainingInputMode,
TrainingInputModeAlgorithmSpecification.Builder metricDefinitions(Collection<MetricDefinition> metricDefinitions)
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
metricDefinitions - A list of metric definition objects. Each object specifies the metric name and regular expressions
used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.AlgorithmSpecification.Builder metricDefinitions(MetricDefinition... metricDefinitions)
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
metricDefinitions - A list of metric definition objects. Each object specifies the metric name and regular expressions
used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.AlgorithmSpecification.Builder metricDefinitions(Consumer<MetricDefinition.Builder>... metricDefinitions)
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
This is a convenience method that creates an instance of theMetricDefinition.Builder avoiding the need to create
one manually via MetricDefinition.builder().
When the Consumer completes,
SdkBuilder.build() is called
immediately and its result is passed to #metricDefinitions(List.
metricDefinitions - a consumer that will call methods on
MetricDefinition.Builder#metricDefinitions(java.util.Collection) AlgorithmSpecification.Builder enableSageMakerMetricsTimeSeries(Boolean enableSageMakerMetricsTimeSeries)
To generate and save time-series metrics during training, set to true. The default is
false and time-series metrics aren't generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
enableSageMakerMetricsTimeSeries - To generate and save time-series metrics during training, set to true. The default is
false and time-series metrics aren't generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
AlgorithmSpecification.Builder containerEntrypoint(Collection<String> containerEntrypoint)
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 more information.
containerEntrypoint - 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 more information.AlgorithmSpecification.Builder containerEntrypoint(String... containerEntrypoint)
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 more information.
containerEntrypoint - 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 more information.AlgorithmSpecification.Builder containerArguments(Collection<String> containerArguments)
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
containerArguments - The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.AlgorithmSpecification.Builder containerArguments(String... containerArguments)
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
containerArguments - The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.AlgorithmSpecification.Builder trainingImageConfig(TrainingImageConfig trainingImageConfig)
The configuration to use an image from a private Docker registry for a training job.
trainingImageConfig - The configuration to use an image from a private Docker registry for a training job.default AlgorithmSpecification.Builder trainingImageConfig(Consumer<TrainingImageConfig.Builder> trainingImageConfig)
The configuration to use an image from a private Docker registry for a training job.
This is a convenience method that creates an instance of theTrainingImageConfig.Builder avoiding the
need to create one manually via TrainingImageConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and
its result is passed to trainingImageConfig(TrainingImageConfig).
trainingImageConfig - a consumer that will call methods on TrainingImageConfig.BuildertrainingImageConfig(TrainingImageConfig)Copyright © 2023. All rights reserved.