Google Cloud Ai Platform V1 Client - Class RawPredictRequest (1.35.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class RawPredictRequest.

Request message for PredictionService.RawPredict.

Generated from protobuf message google.cloud.aiplatform.v1.RawPredictRequest

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name Description
data array

Optional. Data for populating the Message object.
↳ endpoint string

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint}
↳ http_body Google\Api\HttpBody

The prediction input. Supports HTTP headers and arbitrary data payload. A 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 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 field when you create a Model. This schema applies when you deploy the Model as a DeployedModel to an Endpoint and use the RawPredict method.

getEndpoint

Required. The name of the Endpoint requested to serve the prediction.

Format: projects/{project}/locations/{location}/endpoints/{endpoint}

Returns
Type Description
string

setEndpoint

Required. The name of the Endpoint requested to serve the prediction.

Format: projects/{project}/locations/{location}/endpoints/{endpoint}

Parameter
Name Description
var string
Returns
Type Description
$this

getHttpBody

The prediction input. Supports HTTP headers and arbitrary data payload.

A 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 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 field when you create a Model. This schema applies when you deploy the Model as a DeployedModel to an Endpoint and use the RawPredict method.

Returns
Type Description
Google\Api\HttpBody|null

hasHttpBody

clearHttpBody

setHttpBody

The prediction input. Supports HTTP headers and arbitrary data payload.

A 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 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 field when you create a Model. This schema applies when you deploy the Model as a DeployedModel to an Endpoint and use the RawPredict method.

Parameter
Name Description
var Google\Api\HttpBody
Returns
Type Description
$this

static::build

Parameters
Name Description
endpoint string

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint} Please see PredictionServiceClient::endpointName() for help formatting this field.
httpBody Google\Api\HttpBody

The prediction input. Supports HTTP headers and arbitrary data payload.

A 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 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 field when you create a Model. This schema applies when you deploy the Model as a DeployedModel to an Endpoint and use the RawPredict method.
Returns
Type Description
RawPredictRequest