public sealed class RawPredictRequest : IMessage<RawPredictRequest>, IEquatable<RawPredictRequest>, IDeepCloneable<RawPredictRequest>, IBufferMessage, IMessage
Reference documentation and code samples for the Cloud AI Platform v1beta1 API class RawPredictRequest.
Request message for [PredictionService.RawPredict][google.cloud.aiplatform.v1beta1.PredictionService.RawPredict].
Implements
IMessageRawPredictRequest, IEquatableRawPredictRequest, IDeepCloneableRawPredictRequest, IBufferMessage, IMessageNamespace
Google.Cloud.AIPlatform.V1Beta1Assembly
Google.Cloud.AIPlatform.V1Beta1.dll
Constructors
RawPredictRequest()
public RawPredictRequest()
RawPredictRequest(RawPredictRequest)
public RawPredictRequest(RawPredictRequest other)
Parameter | |
---|---|
Name | Description |
other |
RawPredictRequest |
Properties
Endpoint
public string Endpoint { get; set; }
Required. The name of the Endpoint requested to serve the prediction.
Format:
projects/{project}/locations/{location}/endpoints/{endpoint}
Property Value | |
---|---|
Type | Description |
string |
EndpointAsEndpointName
public EndpointName EndpointAsEndpointName { get; set; }
EndpointName-typed view over the Endpoint resource name property.
Property Value | |
---|---|
Type | Description |
EndpointName |
HttpBody
public HttpBody HttpBody { get; set; }
The prediction input. Supports HTTP headers and arbitrary data payload.
A [DeployedModel][google.cloud.aiplatform.v1beta1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1beta1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model.
You can specify the schema for each instance in the
[predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
field when you create a [Model][google.cloud.aiplatform.v1beta1.Model].
This schema applies when you deploy the Model
as a DeployedModel
to an
[Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and use the
RawPredict
method.
Property Value | |
---|---|
Type | Description |
HttpBody |