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feat: add dedicated_resources to DeployedIndex message in aiplatform v1 index_endpoint.proto chore: sort imports #990

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Jan 31, 2022
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feat: add dedicated_resources to DeployedIndex message in aiplatform v1 index_endpoint.proto chore: sort imports #990

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feat: add dedicated_resources to DeployedIndex message in aiplatform …
gcf-owl-bot[bot] Jan 31, 2022
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gcf-owl-bot[bot] Jan 31, 2022
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16 changes: 8 additions & 8 deletions google/cloud/aiplatform/v1/schema/trainingjob/definition_v1/types/automl_tables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,21 +99,21 @@ class AutoMlTablesInputs(proto.Message):
operating characteristic (ROC) curve.
"minimize-log-loss" - Minimize log loss.
"maximize-au-prc" - Maximize the area under
the precision-recall curve. "maximize-
precision-at-recall" - Maximize precision for a
specified
the precision-recall curve.
"maximize-precision-at-recall" - Maximize
precision for a specified
recall value. "maximize-recall-at-precision" -
Maximize recall for a specified
precision value.
classification (multi-class):
"minimize-log-loss" (default) - Minimize log
loss.
regression:
"minimize-rmse" (default) - Minimize root-
mean-squared error (RMSE). "minimize-mae" -
Minimize mean-absolute error (MAE). "minimize-
rmsle" - Minimize root-mean-squared log error
(RMSLE).
"minimize-rmse" (default) - Minimize
root-mean-squared error (RMSE). "minimize-mae"
- Minimize mean-absolute error (MAE).
"minimize-rmsle" - Minimize root-mean-squared
log error (RMSLE).
train_budget_milli_node_hours (int):
Required. The train budget of creating this
model, expressed in milli node hours i.e. 1,000
Expand Down
16 changes: 8 additions & 8 deletions google/cloud/aiplatform/v1beta1/schema/trainingjob/definition_v1beta1/types/automl_tables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,21 +99,21 @@ class AutoMlTablesInputs(proto.Message):
operating characteristic (ROC) curve.
"minimize-log-loss" - Minimize log loss.
"maximize-au-prc" - Maximize the area under
the precision-recall curve. "maximize-
precision-at-recall" - Maximize precision for a
specified
the precision-recall curve.
"maximize-precision-at-recall" - Maximize
precision for a specified
recall value. "maximize-recall-at-precision" -
Maximize recall for a specified
precision value.
classification (multi-class):
"minimize-log-loss" (default) - Minimize log
loss.
regression:
"minimize-rmse" (default) - Minimize root-
mean-squared error (RMSE). "minimize-mae" -
Minimize mean-absolute error (MAE). "minimize-
rmsle" - Minimize root-mean-squared log error
(RMSLE).
"minimize-rmse" (default) - Minimize
root-mean-squared error (RMSE). "minimize-mae"
- Minimize mean-absolute error (MAE).
"minimize-rmsle" - Minimize root-mean-squared
log error (RMSLE).
train_budget_milli_node_hours (int):
Required. The train budget of creating this
model, expressed in milli node hours i.e. 1,000
Expand Down
58 changes: 47 additions & 11 deletions google/cloud/aiplatform_v1/services/dataset_service/async_client.py
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Expand Up @@ -16,7 +16,7 @@
from collections import OrderedDict
import functools
import re
from typing import Dict, Sequence, Tuple, Type, Union
from typing import Dict, Optional, Sequence, Tuple, Type, Union
import pkg_resources

from google.api_core.client_options import ClientOptions
Expand Down Expand Up @@ -129,6 +129,42 @@ def from_service_account_file(cls, filename: str, *args, **kwargs):

from_service_account_json = from_service_account_file

@classmethod
def get_mtls_endpoint_and_cert_source(
cls, client_options: Optional[ClientOptions] = None
):
"""Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order:
(1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
client cert source is None.
(2) if `client_options.client_cert_source` is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.

The API endpoint is determined in the following order:
(1) if `client_options.api_endpoint` if provided, use the provided one.
(2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
default mTLS endpoint; if the environment variabel is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Args:
client_options (google.api_core.client_options.ClientOptions): Custom options for the
client. Only the `api_endpoint` and `client_cert_source` properties may be used
in this method.

Returns:
Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
client cert source to use.

Raises:
google.auth.exceptions.MutualTLSChannelError: If any errors happen.
"""
return DatasetServiceClient.get_mtls_endpoint_and_cert_source(client_options) # type: ignore

@property
def transport(self) -> DatasetServiceTransport:
"""Returns the transport used by the client instance.
Expand Down Expand Up @@ -234,7 +270,7 @@ async def create_dataset(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent, dataset])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -315,7 +351,7 @@ async def get_dataset(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -400,7 +436,7 @@ async def update_dataset(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([dataset, update_mask])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -478,7 +514,7 @@ async def list_datasets(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -569,7 +605,7 @@ async def delete_dataset(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -661,7 +697,7 @@ async def import_data(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name, import_configs])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -754,7 +790,7 @@ async def export_data(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name, export_config])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -839,7 +875,7 @@ async def list_data_items(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -917,7 +953,7 @@ async def get_annotation_spec(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
Expand Down Expand Up @@ -992,7 +1028,7 @@ async def list_annotations(

"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent])
if request is not None and has_flattened_params:
Expand Down
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