public sealed class ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig : IMessage<ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig>, IEquatable<ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig>, IDeepCloneable<ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig>, IBufferMessage, IMessage
Reference documentation and code samples for the Vertex AI v1beta1 API class ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig.
Specification message containing the config for this SliceSpec.
When kind is selected as value and/or range, only a single slice
will be computed.
When all_values is present, a separate slice will be computed for
each possible label/value for the corresponding key in config.
Examples, with feature zip_code with values 12345, 23334, 88888 and
feature country with values "US", "Canada", "Mexico" in the dataset:
A single slice containing data where the zip_codes between 10000 and
20000 has the country "US". For this example, data with the zip_code of
12345 and country "US" will be in this slice.
Example 4:
{ "country": {"all_values": { "value": true } } }
Three slices are computed, one for each unique country in the dataset.
Three slices are computed, one for each unique country in the dataset
where the zip_code is also 12345. For this example, data with zip_code
12345 and country "US" will be in one slice, zip_code 12345 and country
"Canada" in another slice, and zip_code 12345 and country "Mexico" in
another slice, totaling 3 slices.
[[["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 2025-09-04 UTC."],[[["\u003cp\u003eThis documentation details the \u003ccode\u003eSliceConfig\u003c/code\u003e class, part of the Vertex AI v1beta1 API, which is used to specify configurations for creating slices of model evaluation data.\u003c/p\u003e\n"],["\u003cp\u003e\u003ccode\u003eSliceConfig\u003c/code\u003e allows defining slices based on specific values, ranges of values, or all possible values for a given feature within a dataset.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eAllValues\u003c/code\u003e property, when set to true, will generate a separate slice for each unique value of the selected feature within the data.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eRange\u003c/code\u003e property defines a numerical range, including both its high and low values, to determine which data points will be included in the slice, and the \u003ccode\u003eValue\u003c/code\u003e property defines a singular and specific value for the feature that the data should have to be included in the slice.\u003c/p\u003e\n"],["\u003cp\u003eMultiple configurations, such as a \u003ccode\u003erange\u003c/code\u003e and a \u003ccode\u003evalue\u003c/code\u003e, can be combined to specify complex slices that contain data that meet multiple conditions simultaneously, or when \u003ccode\u003eAllValues\u003c/code\u003e is used with a specific \u003ccode\u003eValue\u003c/code\u003e, a new slice will be computed for each unique value where the data also matches the specific \u003ccode\u003eValue\u003c/code\u003e.\u003c/p\u003e\n"]]],[],null,["# Vertex AI v1beta1 API - Class ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig (1.0.0-beta47)\n\nVersion latestkeyboard_arrow_down\n\n- [1.0.0-beta47 (latest)](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig)\n- [1.0.0-beta46](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/1.0.0-beta46/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig) \n\n public sealed class ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig : IMessage\u003cModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig\u003e, IEquatable\u003cModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig\u003e, IDeepCloneable\u003cModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig\u003e, IBufferMessage, IMessage\n\nReference documentation and code samples for the Vertex AI v1beta1 API class ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig.\n\nSpecification message containing the config for this SliceSpec.\nWhen `kind` is selected as `value` and/or `range`, only a single slice\nwill be computed.\nWhen `all_values` is present, a separate slice will be computed for\neach possible label/value for the corresponding key in `config`.\nExamples, with feature zip_code with values 12345, 23334, 88888 and\nfeature country with values \"US\", \"Canada\", \"Mexico\" in the dataset:\n\nExample 1: \n\n {\n \"zip_code\": { \"value\": { \"float_value\": 12345.0 } }\n }\n\nA single slice for any data with zip_code 12345 in the dataset.\n\nExample 2: \n\n {\n \"zip_code\": { \"range\": { \"low\": 12345, \"high\": 20000 } }\n }\n\nA single slice containing data where the zip_codes between 12345 and\n20000 For this example, data with the zip_code of 12345 will be in this\nslice.\n\nExample 3: \n\n {\n \"zip_code\": { \"range\": { \"low\": 10000, \"high\": 20000 } },\n \"country\": { \"value\": { \"string_value\": \"US\" } }\n }\n\nA single slice containing data where the zip_codes between 10000 and\n20000 has the country \"US\". For this example, data with the zip_code of\n12345 and country \"US\" will be in this slice.\n\nExample 4: \n\n { \"country\": {\"all_values\": { \"value\": true } } }\n\nThree slices are computed, one for each unique country in the dataset.\n\nExample 5: \n\n {\n \"country\": { \"all_values\": { \"value\": true } },\n \"zip_code\": { \"value\": { \"float_value\": 12345.0 } }\n }\n\nThree slices are computed, one for each unique country in the dataset\nwhere the zip_code is also 12345. For this example, data with zip_code\n12345 and country \"US\" will be in one slice, zip_code 12345 and country\n\"Canada\" in another slice, and zip_code 12345 and country \"Mexico\" in\nanother slice, totaling 3 slices. \n\nInheritance\n-----------\n\n[object](https://learn.microsoft.com/dotnet/api/system.object) \\\u003e ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig \n\nImplements\n----------\n\n[IMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IMessage-1.html)[ModelEvaluationSlice](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types)[Slice](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types)[SliceSpec](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types)[SliceConfig](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig), [IEquatable](https://learn.microsoft.com/dotnet/api/system.iequatable-1)[ModelEvaluationSlice](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types)[Slice](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types)[SliceSpec](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types)[SliceConfig](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig), [IDeepCloneable](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IDeepCloneable-1.html)[ModelEvaluationSlice](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types)[Slice](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types)[SliceSpec](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec)[Types](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types)[SliceConfig](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig), [IBufferMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IBufferMessage.html), [IMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IMessage.html) \n\nInherited Members\n-----------------\n\n[object.GetHashCode()](https://learn.microsoft.com/dotnet/api/system.object.gethashcode) \n[object.GetType()](https://learn.microsoft.com/dotnet/api/system.object.gettype) \n[object.ToString()](https://learn.microsoft.com/dotnet/api/system.object.tostring)\n\nNamespace\n---------\n\n[Google.Cloud.AIPlatform.V1Beta1](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1)\n\nAssembly\n--------\n\nGoogle.Cloud.AIPlatform.V1Beta1.dll\n\nConstructors\n------------\n\n### SliceConfig()\n\n public SliceConfig()\n\n### SliceConfig(SliceConfig)\n\n public SliceConfig(ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig other)\n\nProperties\n----------\n\n### AllValues\n\n public bool? AllValues { get; set; }\n\nIf all_values is set to true, then all possible labels of the keyed\nfeature will have another slice computed.\nExample: `{\"all_values\":{\"value\":true}}`\n\n### KindCase\n\n public ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.SliceConfig.KindOneofCase KindCase { get; }\n\n### Range\n\n public ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.Range Range { get; set; }\n\nA range of values for a numerical feature.\nExample: `{\"range\":{\"low\":10000.0,\"high\":50000.0}}`\nwill capture 12345 and 23334 in the slice.\n\n### Value\n\n public ModelEvaluationSlice.Types.Slice.Types.SliceSpec.Types.Value Value { get; set; }\n\nA unique specific value for a given feature.\nExample: `{ \"value\": { \"string_value\": \"12345\" } }`"]]
