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"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-03-21 UTC."],[[["The document details various versions of `AutoMlImageClassificationInputs`, ranging from version 1.0.0 to the latest version 3.22.0, within the Google.Cloud.AIPlatform.V1 .NET library."],["`AutoMlImageClassificationInputs` is a class used for defining inputs for training image classification models and it implements several interfaces such as IMessage, IEquatable, IDeepCloneable, and IBufferMessage."],["This class has properties that allow you to set parameters like `BaseModelId`, `BudgetMilliNodeHours`, `DisableEarlyStopping`, `ModelType`, and `MultiLabel`, each influencing how the image classification model is trained."],["The latest `AutoMlImageClassificationInputs` version (3.22.0) can be found in the namespace `Google.Cloud.AIPlatform.V1.Schema.TrainingJob.Definition` within the `Google.Cloud.AIPlatform.V1.dll` assembly, and the full history of versions are displayed."],["The training budget for the model can be set via `BudgetMilliNodeHours`, and you can choose to disable early stopping to utilize the entire budget by using `DisableEarlyStopping`, which determines if the training process will use all the training budget or stop early if the model stops improving."]]],[]]
