public sealed class AutoMlImageSegmentationInputs : IMessage<AutoMlImageSegmentationInputs>, IEquatable<AutoMlImageSegmentationInputs>, IDeepCloneable<AutoMlImageSegmentationInputs>, IBufferMessage, IMessage
The ID of the base model. If it is specified, the new model will be
trained based on the base model. Otherwise, the new model will be
trained from scratch. The base model must be in the same
Project and Location as the new Model to train, and have the same
modelType.
The training budget of creating this model, expressed in milli node
hours i.e. 1,000 value in this field means 1 node hour. The actual
metadata.costMilliNodeHours will be equal or less than this value.
If further model training ceases to provide any improvements, it will
stop without using the full budget and the metadata.successfulStopReason
will be model-converged.
Note, node_hour = actual_hour * number_of_nodes_involved. Or
actaul_wall_clock_hours = train_budget_milli_node_hours /
(number_of_nodes_involved * 1000)
For modelType cloud-high-accuracy-1(default), the budget must be between
20,000 and 2,000,000 milli node hours, inclusive. The default value is
192,000 which represents one day in wall time
(1000 milli * 24 hours * 8 nodes).
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-20 UTC."],[[["\u003cp\u003eThis webpage provides documentation for the \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e class within the Google Cloud AI Platform V1 .NET library, specifically within the \u003ccode\u003eGoogle.Cloud.AIPlatform.V1.Schema.TrainingJob.Definition\u003c/code\u003e namespace.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eAutoMlImageSegmentationInputs\u003c/code\u003e class is used for defining inputs for automated image segmentation training jobs and is available in numerous versions ranging from version 1.0.0 to the latest, 3.22.0.\u003c/p\u003e\n"],["\u003cp\u003eThe class implements several interfaces, including \u003ccode\u003eIMessage\u003c/code\u003e, \u003ccode\u003eIEquatable\u003c/code\u003e, \u003ccode\u003eIDeepCloneable\u003c/code\u003e, and \u003ccode\u003eIBufferMessage\u003c/code\u003e, and is derived from the base \u003ccode\u003eObject\u003c/code\u003e class, indicating its integration with .NET functionalities and the Google Protocol Buffers library.\u003c/p\u003e\n"],["\u003cp\u003eKey properties of this class include \u003ccode\u003eBaseModelId\u003c/code\u003e, allowing for training based on an existing model, \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e, which sets the training budget in milli node hours, and \u003ccode\u003eModelType\u003c/code\u003e, which defines the model type used for the training job.\u003c/p\u003e\n"],["\u003cp\u003eThe most recent version of this class is 3.22.0, however there are many other options to choose from, all the way down to 1.0.0, offering flexibility in your project.\u003c/p\u003e\n"]]],[],null,[]]
