submit_experiment {azuremlsdk} | R Documentation |
Submit an experiment and return the active created run
Description
submit_experiment()
is an asynchronous call to Azure Machine Learning
service to execute a trial on local or remote compute. Depending on the
configuration, submit_experiment()
will automatically prepare your
execution environments, execute your code, and capture your source code
and results in the experiment's run history.
To submit an experiment you first need to create a configuration object
describing how the experiment is to be run. The configuration depends on
the type of trial required. For a script run, provide an Estimator
object
to the config
parameter. For a HyperDrive run for hyperparameter tuning,
provide a HyperDriveConfig
to config
.
Usage
submit_experiment(experiment, config, tags = NULL)
Arguments
experiment |
The |
config |
The |
tags |
A named list of tags for the submitted run, e.g.
|
Value
The ScriptRun
or HyperDriveRun
object.
See Also
estimator()
, hyperdrive_config()
Examples
# This example submits an Estimator experiment
## Not run:
ws <- load_workspace_from_config()
compute_target <- get_compute(ws, cluster_name = 'mycluster')
exp <- experiment(ws, name = 'myexperiment')
est <- estimator(source_directory = '.',
entry_script = 'train.R',
compute_target = compute_target)
run <- submit_experiment(exp, est)
## End(Not run)