register_model_from_run {azuremlsdk} | R Documentation |
Register a model for operationalization.
Description
Register a model for operationalization.
Usage
register_model_from_run(
run,
model_name,
model_path = NULL,
tags = NULL,
properties = NULL,
description = NULL,
datasets = NULL,
sample_input_dataset = NULL,
sample_output_dataset = NULL,
resource_configuration = NULL
)
Arguments
run |
The |
model_name |
The name of the model. |
model_path |
The relative cloud path to the model, for example,
"outputs/modelname". When not specified, |
tags |
A dictionary of key value tags to assign to the model. |
properties |
A dictionary of key value properties to assign to the model. These properties cannot be changed after model creation, however new key-value pairs can be added. |
description |
An optional description of the model. |
datasets |
A list of two-element lists where the first element is the
dataset-model relationship and the second is the corresponding dataset, e.g.
|
sample_input_dataset |
Sample input dataset for the registered model. |
sample_output_dataset |
Sample output dataset for the registered model. |
resource_configuration |
'ResourceConfiguration“ object to run the registered model. |
Value
The registered Model.
Examples
registered_model <- register_model_from_run(run = run, model_name = "my model", model_path = 'outputs/model.rds', tags = list("version" = "0"), datasets = list(list("training", train_dataset), list("validation", validation_dataset)), resource_configuration = resource_configuration(2, 2, 0))