@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class CustomModelTrainingParameters extends Object implements Serializable, Cloneable, StructuredPojo
Contains custom model training parameters. See Custom models in Neptune ML.
Constructor and Description |
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CustomModelTrainingParameters() |
Modifier and Type | Method and Description |
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CustomModelTrainingParameters |
clone() |
boolean |
equals(Object obj) |
String |
getSourceS3DirectoryPath()
The path to the Amazon S3 location where the Python module implementing your model is located.
|
String |
getTrainingEntryPointScript()
The name of the entry point in your module of a script that performs model training and takes hyperparameters as
command-line arguments, including fixed hyperparameters.
|
String |
getTransformEntryPointScript()
The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment.
|
int |
hashCode() |
void |
marshall(ProtocolMarshaller protocolMarshaller)
Marshalls this structured data using the given
ProtocolMarshaller . |
void |
setSourceS3DirectoryPath(String sourceS3DirectoryPath)
The path to the Amazon S3 location where the Python module implementing your model is located.
|
void |
setTrainingEntryPointScript(String trainingEntryPointScript)
The name of the entry point in your module of a script that performs model training and takes hyperparameters as
command-line arguments, including fixed hyperparameters.
|
void |
setTransformEntryPointScript(String transformEntryPointScript)
The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment.
|
String |
toString()
Returns a string representation of this object.
|
CustomModelTrainingParameters |
withSourceS3DirectoryPath(String sourceS3DirectoryPath)
The path to the Amazon S3 location where the Python module implementing your model is located.
|
CustomModelTrainingParameters |
withTrainingEntryPointScript(String trainingEntryPointScript)
The name of the entry point in your module of a script that performs model training and takes hyperparameters as
command-line arguments, including fixed hyperparameters.
|
CustomModelTrainingParameters |
withTransformEntryPointScript(String transformEntryPointScript)
The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment.
|
public void setSourceS3DirectoryPath(String sourceS3DirectoryPath)
The path to the Amazon S3 location where the Python module implementing your model is located. This must point to
a valid existing Amazon S3 location that contains, at a minimum, a training script, a transform script, and a
model-hpo-configuration.json
file.
sourceS3DirectoryPath
- The path to the Amazon S3 location where the Python module implementing your model is located. This must
point to a valid existing Amazon S3 location that contains, at a minimum, a training script, a transform
script, and a model-hpo-configuration.json
file.public String getSourceS3DirectoryPath()
The path to the Amazon S3 location where the Python module implementing your model is located. This must point to
a valid existing Amazon S3 location that contains, at a minimum, a training script, a transform script, and a
model-hpo-configuration.json
file.
model-hpo-configuration.json
file.public CustomModelTrainingParameters withSourceS3DirectoryPath(String sourceS3DirectoryPath)
The path to the Amazon S3 location where the Python module implementing your model is located. This must point to
a valid existing Amazon S3 location that contains, at a minimum, a training script, a transform script, and a
model-hpo-configuration.json
file.
sourceS3DirectoryPath
- The path to the Amazon S3 location where the Python module implementing your model is located. This must
point to a valid existing Amazon S3 location that contains, at a minimum, a training script, a transform
script, and a model-hpo-configuration.json
file.public void setTrainingEntryPointScript(String trainingEntryPointScript)
The name of the entry point in your module of a script that performs model training and takes hyperparameters as
command-line arguments, including fixed hyperparameters. The default is training.py
.
trainingEntryPointScript
- The name of the entry point in your module of a script that performs model training and takes
hyperparameters as command-line arguments, including fixed hyperparameters. The default is
training.py
.public String getTrainingEntryPointScript()
The name of the entry point in your module of a script that performs model training and takes hyperparameters as
command-line arguments, including fixed hyperparameters. The default is training.py
.
training.py
.public CustomModelTrainingParameters withTrainingEntryPointScript(String trainingEntryPointScript)
The name of the entry point in your module of a script that performs model training and takes hyperparameters as
command-line arguments, including fixed hyperparameters. The default is training.py
.
trainingEntryPointScript
- The name of the entry point in your module of a script that performs model training and takes
hyperparameters as command-line arguments, including fixed hyperparameters. The default is
training.py
.public void setTransformEntryPointScript(String transformEntryPointScript)
The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment. It
should be able to run with no command-line arguments.The default is transform.py
.
transformEntryPointScript
- The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment.
It should be able to run with no command-line arguments.The default is transform.py
.public String getTransformEntryPointScript()
The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment. It
should be able to run with no command-line arguments.The default is transform.py
.
transform.py
.public CustomModelTrainingParameters withTransformEntryPointScript(String transformEntryPointScript)
The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment. It
should be able to run with no command-line arguments.The default is transform.py
.
transformEntryPointScript
- The name of the entry point in your module of a script that should be run after the best model from the
hyperparameter search has been identified, to compute the model artifacts necessary for model deployment.
It should be able to run with no command-line arguments.The default is transform.py
.public String toString()
toString
in class Object
Object.toString()
public CustomModelTrainingParameters clone()
public void marshall(ProtocolMarshaller protocolMarshaller)
StructuredPojo
ProtocolMarshaller
.marshall
in interface StructuredPojo
protocolMarshaller
- Implementation of ProtocolMarshaller
used to marshall this object's data.