components automl_many_models_inference

AutoML Many Models - Inference

automl_many_models_inference

Overview

Inference components for AutoML many model.

Version: 0.0.6

View in Studio: https://ml.azure.com/registries/azureml/components/automl_many_models_inference/version/0.0.6

Inputs

Name	Description	Type	Default	Optional	Enum
raw_data	Folder URI with inference data.	uri_folder
compute_name	Compute name for inference pipeline.	string
max_nodes	Number of nodes in a compute cluster we will run the inference 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 setting in seconds.	integer	3600
train_run_id	The train run id used for training models that will be used to generate forecasts.	string		True
training_experiment_name	The training experiment that used for inference.	string		True
partition_column_names	The partition column names for inference.	string		True
forecast_quantiles	Space separated list of quantiles for forecasting jobs. It is applicable only when the forecast_mode is recursive.	string		True
inference_type	The inference type of the inference, possible values are forecast, predict and predict_proba. predict_proba`` should be used on the classification tasks, predictshould be used on the regression tasks andforecast` should be used on the forecasting tasks.	string		True	['forecast', 'predict', 'predict_proba']
forecast_mode	The forecast mode used for inference. The possible values are recursive and rolling.	string		True	['recursive', 'rolling']
forecast_step	The forecast step used for rolling forecast. See more details here: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-forecast?view=azureml-api-2#evaluating-model-accuracy-with-a-rolling-forecast	integer	1	True
allow_multi_partitions	Allow multi paritions in one partitioned file	boolean		True
skip_concat_results	Flag on skip concat inferece results	boolean		True
early_validation_failure	Enable early failure validations	boolean		True
optional_train_metadata	Metadata from training run.	uri_folder		True
label_column_name	Label column name for the data.	string		True

Outputs

Name	Description	Type
run_output	Folder URI representing the location of the output data	uri_folder
raw_predictions	The raw forecast results from each inferece run	uri_folder
evaluation_configs	The evaluation configs.	uri_file
evaluation_data	The evaluation data.	uri_file