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Request message for PredictionService.Predict.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#endpoint
def endpoint() -> ::String
Returns
-
(::String) — Required. The name of the Endpoint requested to serve the prediction.
Format:
projects/{project}/locations/{location}/endpoints/{endpoint}
#endpoint=
def endpoint=(value) -> ::String
Parameter
-
value (::String) — Required. The name of the Endpoint requested to serve the prediction.
Format:
projects/{project}/locations/{location}/endpoints/{endpoint}
Returns
-
(::String) — Required. The name of the Endpoint requested to serve the prediction.
Format:
projects/{project}/locations/{location}/endpoints/{endpoint}
#instances
def instances() -> ::Array<::Google::Protobuf::Value>
Returns
- (::Array<::Google::Protobuf::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, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] instance_schema_uri.
#instances=
def instances=(value) -> ::Array<::Google::Protobuf::Value>
Parameter
- value (::Array<::Google::Protobuf::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, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] instance_schema_uri.
Returns
- (::Array<::Google::Protobuf::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, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] instance_schema_uri.
#parameters
def parameters() -> ::Google::Protobuf::Value
Returns
- (::Google::Protobuf::Value) — The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] parameters_schema_uri.
#parameters=
def parameters=(value) -> ::Google::Protobuf::Value
Parameter
- value (::Google::Protobuf::Value) — The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] parameters_schema_uri.
Returns
- (::Google::Protobuf::Value) — The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] parameters_schema_uri.