how to include environment when submitting an automl experiment in azure machine learning - azure-machine-learning-studio

Question

I use code like below to create an AutoML object to submit an experiment for classification training
automl_settings = {
"n_cross_validations": 2,
"primary_metric": 'accuracy',
"enable_early_stopping": True,
"experiment_timeout_hours": 1.0,
"max_concurrent_iterations": 4,
"verbosity": logging.INFO,
}
automl_config = AutoMLConfig(task = 'classification',
compute_target = compute_target,
training_data = train_data,
label_column_name = label,
**automl_settings
)
ws = Workspace.from_config()
experiment = Experiment(ws, "your-experiment-name")
run = experiment.submit(automl_config, show_output=True)
I want to include my conda yml file (like below) in my experiment submission.
env = Environment.from_conda_specification(name='myenv', file_path='conda_dependencies.yml')
However, I don't see any environment parameter in AutoMLConfig class documentation (similar to what environment parameter does in ScriptRunConfig) or find any example how to do so.
I notice after the experiment is submitted, I get message like this
Running on remote.
No run_configuration provided, running on aml-compute with default configuration
Is run_configuration used for specifying environment? If so, how do I provide run_configuration in my AutoML experiment run?
Thank you.

Answer 1

I figured out how to fix the issues associated with the sdk 1.19.0 upgrade in the AML environment I use, thus no need for the workaround (ie. pass in a SDK 1.18.0 conda environment file to AutoML experiment run) I was thinking about. My original question no longer needs an answer, I just want to add this note in case someone else has the same question later on.
I still don't know why AutoML experiment run has no option to pass in a conda environment file. It would be nice if a reason is given in the AML documentation.