Interface CfnEndpointConfig.ClarifyInferenceConfigProperty
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnEndpointConfig.ClarifyInferenceConfigProperty.Jsii$Proxy
- Enclosing class:
CfnEndpointConfig
Example:
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import software.amazon.awscdk.services.sagemaker.*;
ClarifyInferenceConfigProperty clarifyInferenceConfigProperty = ClarifyInferenceConfigProperty.builder()
.contentTemplate("contentTemplate")
.featureHeaders(List.of("featureHeaders"))
.featuresAttribute("featuresAttribute")
.featureTypes(List.of("featureTypes"))
.labelAttribute("labelAttribute")
.labelHeaders(List.of("labelHeaders"))
.labelIndex(123)
.maxPayloadInMb(123)
.maxRecordCount(123)
.probabilityAttribute("probabilityAttribute")
.probabilityIndex(123)
.build();
- See Also:
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Nested Class Summary
Nested ClassesModifier and TypeInterfaceDescriptionstatic final classA builder forCfnEndpointConfig.ClarifyInferenceConfigPropertystatic final classAn implementation forCfnEndpointConfig.ClarifyInferenceConfigProperty -
Method Summary
Modifier and TypeMethodDescriptionbuilder()default StringA template string used to format a JSON record into an acceptable model container input.The names of the features.default StringProvides the JMESPath expression to extract the features from a model container input in JSON Lines format.A list of data types of the features (optional).default StringA JMESPath expression used to locate the list of label headers in the model container output.For multiclass classification problems, the label headers are the names of the classes.default NumberA zero-based index used to extract a label header or list of label headers from model container output in CSV format.default NumberThe maximum payload size (MB) allowed of a request from the explainer to the model container.default NumberThe maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset .default StringA JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.default NumberA zero-based index used to extract a probability value (score) or list from model container output in CSV format.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
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Method Details
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getContentTemplate
A template string used to format a JSON record into an acceptable model container input.For example, a
ContentTemplatestring'{"myfeatures":$features}'will format a list of features[1,2,3]into the record string'{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format.- See Also:
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getFeatureHeaders
The names of the features.If provided, these are included in the endpoint response payload to help readability of the
InvokeEndpointoutput. See the Response section under Invoke the endpoint in the Developer Guide for more information.- See Also:
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getFeaturesAttribute
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format.For example, if
FeaturesAttributeis the JMESPath expression'myfeatures', it extracts a list of features[1,2,3]from request data'{"myfeatures":[1,2,3]}'.- See Also:
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getFeatureTypes
A list of data types of the features (optional).Applicable only to NLP explainability. If provided,
FeatureTypesmust have at least one'text'string (for example,['text']). IfFeatureTypesis not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.- See Also:
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getLabelAttribute
A JMESPath expression used to locate the list of label headers in the model container output.Example : If the model container output of a batch request is
'{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}', then setLabelAttributeto'labels'to extract the list of label headers["cat","dog","fish"]- See Also:
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getLabelHeaders
For multiclass classification problems, the label headers are the names of the classes.Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the
InvokeEndpointAPI. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.- See Also:
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getLabelIndex
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.Example for a multiclass model: If the model container output consists of label headers followed by probabilities:
'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', setLabelIndexto0to select the label headers['cat','dog','fish'].- See Also:
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getMaxPayloadInMb
The maximum payload size (MB) allowed of a request from the explainer to the model container.Defaults to
6MB.- See Also:
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getMaxRecordCount
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset . A record is a unit of input data that inference can be made on, for example, a single line in CSV data. IfMaxRecordCountis1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime.- See Also:
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getProbabilityAttribute
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.Example : If the model container output of a single request is
'{"predicted_label":1,"probability":0.6}', then setProbabilityAttributeto'probability'.- See Also:
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getProbabilityIndex
A zero-based index used to extract a probability value (score) or list from model container output in CSV format.If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability:
'1,0.6', setProbabilityIndexto1to select the probability value0.6.Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability:
'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', setProbabilityIndexto1to select the probability values[0.1,0.6,0.3].- See Also:
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builder
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