register_model: Register a model to a given workspace
In azuremlsdk: Interface to the 'Azure Machine Learning' 'SDK'

Description Usage Arguments Value Examples See Also

Register a model to the given workspace. A registered model is a logical container for one or more files that make up your model. For example, if you have a model that's stored in multiple files, you can register them as a single model in your workspace. After registration, you can then download or deploy the registered model and receive all the files that were registered.

Models are identified by name and version. Each time you register a model with the same name as an existing one, your workspace's model registry assumes that it's a new version. The version is incremented, and the new model is registered under the same name.

register_model(
  workspace,
  model_path,
  model_name,
  datasets = NULL,
  tags = NULL,
  properties = NULL,
  description = NULL,
  child_paths = NULL,
  sample_input_dataset = NULL,
  sample_output_dataset = NULL,
  resource_configuration = NULL
)

`workspace`	The `Workspace` object.
`model_path`	A string of the path on the local file system where the model assets are located. This can be a direct pointer to a single file or folder. If pointing to a folder, the `child_paths` parameter can be used to specify individual files to bundle together as the `Model` object, as opposed to using the entire contents of the folder.
`model_name`	A string of the name to register the model with.
`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. `list(list("training", train_ds), list("inferencing", infer_ds))`. Valid values for the data-model relationship are 'training', 'validation', and 'inferencing'.
`tags`	A named list of key-value tags to give the model, e.g. `list("key" = "value")`
`properties`	A named list of key-value properties to give the model, e.g. `list("key" = "value")`.
`description`	A string of the text description of the model.
`child_paths`	A list of strings of child paths of a folder specified by `model_name`. Must be provided in conjunction with a `model_path` pointing to a folder; only the specified files will be bundled into the `Model` object.
`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.

The Model object.

Registering a model from a single file:

ws <- load_workspace_from_config()
model <- register_model(ws,
                        model_path = "my_model.rds",
                        model_name = "my_model",
                        datasets = list(list("training", train_dataset)))