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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 |
str
Vertex AI https endpoint. |
session |
bigframes.Session or None
BQ session to create the model. If None, use the global default session. |
connection_name |
str or None
Connection 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 True
Default |
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.DataFrame
Predict 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. |