Package prediction.aiplatform.gdc.goog.v1

Index

PredictionService (interface)
PredictRequest (message)
PredictResponse (message)
RawPredictRequest (message)

PredictionService

A service for online predictions and explanations.

Predict

Predict
`rpc Predict(PredictRequest) returns (PredictResponse)` Perform an online prediction.

rpc Predict(PredictRequest) returns (PredictResponse)

Perform an online prediction.

RawPredict

RawPredict
`rpc RawPredict(RawPredictRequest) returns (HttpBody)` Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers: `X-Vertex-AI-Endpoint-Id`: ID of the Endpoint that served this prediction. `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's DeployedModel that served this prediction.

rpc RawPredict(RawPredictRequest) returns (HttpBody)

Perform an online prediction with an arbitrary HTTP payload.

The response includes the following HTTP headers:

X-Vertex-AI-Endpoint-Id: ID of the Endpoint that served this prediction.
X-Vertex-AI-Deployed-Model-Id: ID of the Endpoint's DeployedModel that served this prediction.

PredictRequest

Request message for PredictionService.Predict.

Fields

Fields
`endpoint`	`string` Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
`instances[]`	`Value` Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request. In case of customer-created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified on the Endpoint's DeployedModels.
`parameters`	`Value` The parameters that govern the prediction. The schema of the parameters may be specified on the Endpoint's DeployedModels.

endpoint

string

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instances[]

Value

Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request. In case of customer-created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified on the Endpoint's DeployedModels.

parameters

Value

The parameters that govern the prediction. The schema of the parameters may be specified on the Endpoint's DeployedModels.

PredictResponse

Response message for PredictionService.Predict.

Fields
`predictions[]`	`Value` The predictions that are the output of the predictions call. The schema of any single prediction may be specified on the Endpoint's DeployedModels.
`deployed_model_id`	`string` ID of the Endpoint's DeployedModel that served this prediction.
`model`	`string` Output only. The resource name of the Model which is deployed as the DeployedModel that this prediction hits.
`model_version_id`	`string` Output only. The version ID of the Model which is deployed as the DeployedModel that this prediction hits.
`model_display_name`	`string` Output only. The display name of the Model which is deployed as the DeployedModel that this prediction hits.
`metadata`	`Value` Output only. Request-level metadata returned by the model. The metadata type will be dependent upon the model implementation.

RawPredictRequest

Request message for PredictionService.RawPredict.

Fields

Fields
`endpoint`	`string` Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
`http_body`	`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 PredictSchemata 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.

endpoint

string

Required. The name of the Endpoint requested to serve the prediction. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

http_body

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 PredictSchemata 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.