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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. For more information, see Deploy model on Vertex AI: https://cloud.google.com/bigquery/docs/bigquery-ml-remote-model-tutorial#Deploy-Model-on-Vertex-AI .
Parameters
endpoint
str
Vertex AI HTTPS endpoint.
input
Mapping
Input schema: {column_name: column_type}
. Supported types are "bool", "string", "int64", "float64", "array
output
Mapping
Output label schema: {column_name: column_type}
. Supported the same types as the input.
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.
deep
bool, default True
Default True
. If True, will return the parameters for this estimator and contained subobjects that are estimators.
Dictionary
predict
predict
(
X
:
typing
.
Union
[
bigframes
.
dataframe
.
DataFrame
,
bigframes
.
series
.
Series
,
pandas
.
core
.
frame
.
DataFrame
,
pandas
.
core
.
series
.
Series
,
],
)
-
> bigframes
.
dataframe
.
DataFrame
Predict the result from the input DataFrame.
X
bigframes.pandas.DataFrame
or bigframes.pandas.Series
or pandas.DataFrame or pandas.Series
Input DataFrame or Series, which needs to comply with the input parameter of the model.
