Class VertexAIModel (0.21.0)
 
 
 
 
 
 
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VertexAIModel(
 endpoint: str,
 input: typing.Mapping[str, str],
 output: typing.Mapping[str, str],
 session: typing.Optional[bigframes.session.Session] = None,
 connection_name: typing.Optional[str] = None,
)Remote model from a Vertex AI https endpoint. User must specify https endpoint, input schema and output schema. How to deploy a model in Vertex AI https://cloud.google.com/bigquery/docs/bigquery-ml-remote-model-tutorial#Deploy-Model-on-Vertex-AI.
| Parameters | |
|---|---|
| Name | Description | 
| endpoint | strVertex AI https endpoint. | 
| input | MappingInput schema:  | 
| output | MappingOutput label schema:  | 
| session | bigframes.Session or NoneBQ session to create the model. If None, use the global default session. | 
| connection_name | str or NoneConnection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>. | 
Methods
__repr__
__repr__()Print the estimator's constructor with all non-default parameter values
get_params
get_params(deep: bool = True) -> typing.Dict[str, typing.Any]Get parameters for this estimator.
| Parameter | |
|---|---|
| Name | Description | 
| deep | bool, default TrueDefault  | 
| Returns | |
|---|---|
| Type | Description | 
| Dictionary | A dictionary of parameter names mapped to their values. | 
predict
predict(
 X: typing.Union[bigframes.dataframe.DataFrame, bigframes.series.Series]
) -> bigframes.dataframe.DataFramePredict the result from the input DataFrame.
| Parameter | |
|---|---|
| Name | Description | 
| X | bigframes.dataframe.DataFrame or bigframes.series.Series Input DataFrame or Series, which needs to comply with the input parameter of the model. | 
| Returns | |
|---|---|
| Type | Description | 
| bigframes.dataframe.DataFrame  | DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values. |