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MachineLearningBatchDeploymentProperties.cs
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MachineLearningBatchDeploymentProperties.cs
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// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// <auto-generated/>
#nullable disable
using System.Collections.Generic;
namespace Azure.ResourceManager.MachineLearning.Models
{
/// <summary> Batch inference settings per deployment. </summary>
public partial class MachineLearningBatchDeploymentProperties : MachineLearningEndpointDeploymentProperties
{
/// <summary> Initializes a new instance of MachineLearningBatchDeploymentProperties. </summary>
public MachineLearningBatchDeploymentProperties()
{
}
/// <summary> Initializes a new instance of MachineLearningBatchDeploymentProperties. </summary>
/// <param name="codeConfiguration"> Code configuration for the endpoint deployment. </param>
/// <param name="description"> Description of the endpoint deployment. </param>
/// <param name="environmentId"> ARM resource ID or AssetId of the environment specification for the endpoint deployment. </param>
/// <param name="environmentVariables"> Environment variables configuration for the deployment. </param>
/// <param name="properties"> Property dictionary. Properties can be added, but not removed or altered. </param>
/// <param name="compute"> Compute target for batch inference operation. </param>
/// <param name="errorThreshold">
/// Error threshold, if the error count for the entire input goes above this value,
/// the batch inference will be aborted. Range is [-1, int.MaxValue].
/// For FileDataset, this value is the count of file failures.
/// For TabularDataset, this value is the count of record failures.
/// If set to -1 (the lower bound), all failures during batch inference will be ignored.
/// </param>
/// <param name="loggingLevel"> Logging level for batch inference operation. </param>
/// <param name="maxConcurrencyPerInstance"> Indicates maximum number of parallelism per instance. </param>
/// <param name="miniBatchSize">
/// Size of the mini-batch passed to each batch invocation.
/// For FileDataset, this is the number of files per mini-batch.
/// For TabularDataset, this is the size of the records in bytes, per mini-batch.
/// </param>
/// <param name="model">
/// Reference to the model asset for the endpoint deployment.
/// Please note <see cref="MachineLearningAssetReferenceBase"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
/// The available derived classes include <see cref="MachineLearningDataPathAssetReference"/>, <see cref="MachineLearningIdAssetReference"/> and <see cref="MachineLearningOutputPathAssetReference"/>.
/// </param>
/// <param name="outputAction"> Indicates how the output will be organized. </param>
/// <param name="outputFileName"> Customized output file name for append_row output action. </param>
/// <param name="provisioningState"> Provisioning state for the endpoint deployment. </param>
/// <param name="resources">
/// Indicates compute configuration for the job.
/// If not provided, will default to the defaults defined in ResourceConfiguration.
/// </param>
/// <param name="retrySettings">
/// Retry Settings for the batch inference operation.
/// If not provided, will default to the defaults defined in BatchRetrySettings.
/// </param>
internal MachineLearningBatchDeploymentProperties(MachineLearningCodeConfiguration codeConfiguration, string description, string environmentId, IDictionary<string, string> environmentVariables, IDictionary<string, string> properties, string compute, int? errorThreshold, MachineLearningBatchLoggingLevel? loggingLevel, int? maxConcurrencyPerInstance, long? miniBatchSize, MachineLearningAssetReferenceBase model, MachineLearningBatchOutputAction? outputAction, string outputFileName, MachineLearningDeploymentProvisioningState? provisioningState, MachineLearningDeploymentResourceConfiguration resources, MachineLearningBatchRetrySettings retrySettings) : base(codeConfiguration, description, environmentId, environmentVariables, properties)
{
Compute = compute;
ErrorThreshold = errorThreshold;
LoggingLevel = loggingLevel;
MaxConcurrencyPerInstance = maxConcurrencyPerInstance;
MiniBatchSize = miniBatchSize;
Model = model;
OutputAction = outputAction;
OutputFileName = outputFileName;
ProvisioningState = provisioningState;
Resources = resources;
RetrySettings = retrySettings;
}
/// <summary> Compute target for batch inference operation. </summary>
public string Compute { get; set; }
/// <summary>
/// Error threshold, if the error count for the entire input goes above this value,
/// the batch inference will be aborted. Range is [-1, int.MaxValue].
/// For FileDataset, this value is the count of file failures.
/// For TabularDataset, this value is the count of record failures.
/// If set to -1 (the lower bound), all failures during batch inference will be ignored.
/// </summary>
public int? ErrorThreshold { get; set; }
/// <summary> Logging level for batch inference operation. </summary>
public MachineLearningBatchLoggingLevel? LoggingLevel { get; set; }
/// <summary> Indicates maximum number of parallelism per instance. </summary>
public int? MaxConcurrencyPerInstance { get; set; }
/// <summary>
/// Size of the mini-batch passed to each batch invocation.
/// For FileDataset, this is the number of files per mini-batch.
/// For TabularDataset, this is the size of the records in bytes, per mini-batch.
/// </summary>
public long? MiniBatchSize { get; set; }
/// <summary>
/// Reference to the model asset for the endpoint deployment.
/// Please note <see cref="MachineLearningAssetReferenceBase"/> is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes.
/// The available derived classes include <see cref="MachineLearningDataPathAssetReference"/>, <see cref="MachineLearningIdAssetReference"/> and <see cref="MachineLearningOutputPathAssetReference"/>.
/// </summary>
public MachineLearningAssetReferenceBase Model { get; set; }
/// <summary> Indicates how the output will be organized. </summary>
public MachineLearningBatchOutputAction? OutputAction { get; set; }
/// <summary> Customized output file name for append_row output action. </summary>
public string OutputFileName { get; set; }
/// <summary> Provisioning state for the endpoint deployment. </summary>
public MachineLearningDeploymentProvisioningState? ProvisioningState { get; }
/// <summary>
/// Indicates compute configuration for the job.
/// If not provided, will default to the defaults defined in ResourceConfiguration.
/// </summary>
public MachineLearningDeploymentResourceConfiguration Resources { get; set; }
/// <summary>
/// Retry Settings for the batch inference operation.
/// If not provided, will default to the defaults defined in BatchRetrySettings.
/// </summary>
public MachineLearningBatchRetrySettings RetrySettings { get; set; }
}
}