public sealed class AutoMlImageClassificationInputs : IMessage<AutoMlImageClassificationInputs>, IEquatable<AutoMlImageClassificationInputs>, IDeepCloneable<AutoMlImageClassificationInputs>, 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.
For modelType cloud(default), the budget must be between 8,000
and 800,000 milli node hours, inclusive. The default value is 192,000
which represents one day in wall time, considering 8 nodes are used.
For model types mobile-tf-low-latency-1, mobile-tf-versatile-1,
mobile-tf-high-accuracy-1, the training budget must be between
1,000 and 100,000 milli node hours, inclusive.
The default value is 24,000 which represents one day in wall time on a
single node that is used.
Use the entire training budget. This disables the early stopping feature.
When false the early stopping feature is enabled, which means that
AutoML Image Classification might stop training before the entire
training budget has been used.
If false, a single-label (multi-class) Model will be trained (i.e.
assuming that for each image just up to one annotation may be
applicable). If true, a multi-label Model will be trained (i.e.
assuming that for each image multiple annotations may be applicable).
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-20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 document outlines the different versions of \u003ccode\u003eAutoMlImageClassificationInputs\u003c/code\u003e, a class within the Google Cloud AI Platform's .NET library for defining inputs for automated image classification training jobs.\u003c/p\u003e\n"],["\u003cp\u003eThe latest version available is 3.22.0, and the document provides a complete list of versions from 1.0.0 up to this latest release, each linked to its specific documentation page.\u003c/p\u003e\n"],["\u003cp\u003e\u003ccode\u003eAutoMlImageClassificationInputs\u003c/code\u003e 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, indicating its role in message handling and data management.\u003c/p\u003e\n"],["\u003cp\u003eKey properties of the \u003ccode\u003eAutoMlImageClassificationInputs\u003c/code\u003e class include \u003ccode\u003eBaseModelId\u003c/code\u003e for leveraging existing models, \u003ccode\u003eBudgetMilliNodeHours\u003c/code\u003e for training budget management, \u003ccode\u003eDisableEarlyStopping\u003c/code\u003e to control training duration, \u003ccode\u003eModelType\u003c/code\u003e for different model configurations, and \u003ccode\u003eMultiLabel\u003c/code\u003e for specifying single or multi-label classification.\u003c/p\u003e\n"],["\u003cp\u003eThis class contains two constructors for default initialization and initialization based on another \u003ccode\u003eAutoMlImageClassificationInputs\u003c/code\u003e object.\u003c/p\u003e\n"]]],[],null,[]]
