Google Cloud Ai Platform V1 Client - Class RawPredictRequest (0.29.0)

Version 0.29.0

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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 Google\Cloud\AIPlatform\V1\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
Google\Cloud\AIPlatform\V1\RawPredictRequest