Put Trained Model API
editPut Trained Model API
editCreates a new trained model for inference.
The API accepts a PutTrainedModelRequest object as a request and returns a PutTrainedModelResponse.
Put Trained Model request
editA PutTrainedModelRequest requires the following argument:
Trained Model configuration
editThe TrainedModelConfig object contains all the details about the trained model
configuration and contains the following arguments:
TrainedModelConfig trainedModelConfig = TrainedModelConfig.builder()
.setDefinition(definition)
.setCompressedDefinition(InferenceToXContentCompressor.deflate(definition))
.setModelId("my-new-trained-model")
.setInput(new TrainedModelInput("col1", "col2", "col3", "col4"))
.setDescription("test model")
.setMetadata(new HashMap<>())
.setTags("my_regression_models")
.build();
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The inference definition for the model |
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Optionally, if the inference definition is large, you may choose to compress it for transport. Do not supply both the compressed and uncompressed definitions. |
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The unique model id |
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The input field names for the model definition |
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Optionally, a human-readable description |
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Optionally, an object map contain metadata about the model |
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Optionally, an array of tags to organize the model |
Synchronous execution
editWhen executing a PutTrainedModelRequest in the following manner, the client waits
for the PutTrainedModelResponse to be returned before continuing with code execution:
PutTrainedModelResponse response = client.machineLearning().putTrainedModel(request, RequestOptions.DEFAULT);
Synchronous calls may throw an IOException in case of either failing to
parse the REST response in the high-level REST client, the request times out
or similar cases where there is no response coming back from the server.
In cases where the server returns a 4xx or 5xx error code, the high-level
client tries to parse the response body error details instead and then throws
a generic ElasticsearchException and adds the original ResponseException as a
suppressed exception to it.
Asynchronous execution
editExecuting a PutTrainedModelRequest can also be done in an asynchronous fashion so that
the client can return directly. Users need to specify how the response or
potential failures will be handled by passing the request and a listener to the
asynchronous put-trained-model method:
The asynchronous method does not block and returns immediately. Once it is
completed the ActionListener is called back using the onResponse method
if the execution successfully completed or using the onFailure method if
it failed. Failure scenarios and expected exceptions are the same as in the
synchronous execution case.
A typical listener for put-trained-model looks like:
Response
editThe returned PutTrainedModelResponse contains the newly created trained model.
The PutTrainedModelResponse will omit the model definition as a precaution against
streaming large model definitions back to the client.
TrainedModelConfig model = response.getResponse();