AutoMLImageConfig Class

Represents configuration for submitting an automated ML image experiment in Azure Machine Learning.

This configuration object contains and persists the parameters for configuring the experiment run, as well as the training data to be used at run time. For guidance on selecting your settings, see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.

Create an AutoMLImageConfig.

Inheritance
AutoMLImageConfig

Constructor

AutoMLImageConfig(task: ImageTask, compute_target: Any, training_data: TabularDataset, hyperparameter_sampling: HyperParameterSampling, iterations: int, max_concurrent_iterations: int | None = None, experiment_timeout_hours: float | int | None = None, early_termination_policy: EarlyTerminationPolicy | None = None, validation_data: TabularDataset | None = None, arguments: List[Any] | None = None, **kwargs: Any)

Parameters

Name Description
task
Required
<xref:ImageTask>

The type of task to run.

compute_target
Required
Any

The Azure Machine Learning compute target to run the ML image experiment on. Only remote GPU computes with more than 12 GB of GPU memory are supported. See https://docs.microsoft.com/azure/machine-learning/how-to-auto-train-remote for more information on compute targets.

training_data
Required
<xref:TabularDataset>

The training data to be used within the experiment.

hyperparameter_sampling
Required
<xref:HyperParameterSampling>

Object containing the hyperparameter space, the sampling method, and in some cases additional properties for specific sampling classes.

iterations
Required
int

The total number of different model and parameter combinations to test during an automated ML image experiment. If not specified, the default is 1 iteration.

max_concurrent_iterations

Represents the maximum number of iterations that would be executed in parallel. The default value is the same as the number of iterations provided.

Default value: None
experiment_timeout_hours

Maximum amount of time in hours that all iterations combined can take before the experiment terminates. Can be a decimal value like 0.25 representing 15 minutes. If not specified, the default experiment timeout is 6 days.

Default value: None
early_termination_policy
Optional[<xref:EarlyTerminationPolicy>]

Early termination policy use when using hyperparameter tuning with several iterations. An iteration is cancelled when the criteria of a specified policy are met.

Default value: None
validation_data
Optional[<xref:TabularDataset>]

The validation data to be used within the experiment.

Default value: None
arguments

Arguments to be passed to the remote script runs. Arguments are passed in name-value pairs and the name must be prefixed by a double dash.

Default value: None
task
Required
<xref:ImageTask>

The type of task to run.

compute_target
Required
Any

The Azure Machine Learning compute target to run the ML image experiment on. Only remote GPU computes with more than 12 GB of GPU memory are supported. See https://docs.microsoft.com/azure/machine-learning/how-to-auto-train-remote for more information on compute targets.

training_data
Required
<xref:TabularDataset>

The training data to be used within the experiment.

hyperparameter_sampling
Required
<xref:HyperParameterSampling>

Object containing the hyperparameter space, the sampling method, and in some cases additional properties for specific sampling classes.

iterations
Required
int

The total number of different model and parameter combinations to test during an automated ML image experiment. If not specified, the default is 1 iteration.

max_concurrent_iterations
Required

Represents the maximum number of iterations that would be executed in parallel. The default value is the same as the number of iterations provided.

experiment_timeout_hours
Required

Maximum amount of time in hours that all iterations combined can take before the experiment terminates. Can be a decimal value like 0.25 representing 15 minutes. If not specified, the default experiment timeout is 6 days.

early_termination_policy
Required
Optional[<xref:EarlyTerminationPolicy>]

Early termination policy use when using hyperparameter tuning with several iterations. An iteration is cancelled when the criteria of a specified policy are met.

validation_data
Required
Optional[<xref:TabularDataset>]

The validation data to be used within the experiment.

arguments
Required

Arguments to be passed to the remote script runs. Arguments are passed in name-value pairs and the name must be prefixed by a double dash.