components automl_many_models_training - Azure/azureml-assets GitHub Wiki
Enables AutoML many models training.
Version: 0.0.7
View in Studio: https://ml.azure.com/registries/azureml/components/automl_many_models_training/version/0.0.7
| Name | Description | Type | Default | Optional | Enum |
|---|---|---|---|---|---|
| raw_data | Folder URI with training data. | uri_folder | |||
| automl_config | The automl config yml/json used for training. | uri_file | |||
| compute_name | Compute name for train pipeline. | string | |||
| max_nodes | Number of nodes in a compute cluster we will run the train step on. | integer | |||
| max_concurrency_per_node | Number of processes that will be run concurrently on any given node. This number should not be larger than 1/2 of the number of cores in an individual node in the specified cluster | integer | |||
| parallel_step_timeout_in_seconds | The PRS step time out settings | integer | 3600 | ||
| retrain_failed_model | Flag to enable re-training for failed models. This is useful if you have done previous many models runs that resulted in failed AutoML jobs on some data partitions. When this flag is enabled, many models will only launch training jobs for previously failed partitions. | boolean | False | ||
| early_validation_failure | Early failure when enabling validations in setup phase. | boolean | True |
| Name | Description | Type |
|---|---|---|
| run_output | Folder URI representing the location of the output data | uri_folder |