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ModelMonitoringServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1beta1.services.model_monitoring_service.transports.base.ModelMonitoringServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1beta1.services.model_monitoring_service.transports.base.ModelMonitoringServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
A service for creating and managing Vertex AI Model moitoring. This
includes ModelMonitor
resources, ModelMonitoringJob
resources.
Properties
api_endpoint
Return the API endpoint used by the client instance.
Returns | |
---|---|
Type | Description |
str |
The API endpoint used by the client instance. |
transport
Returns the transport used by the client instance.
Returns | |
---|---|
Type | Description |
ModelMonitoringServiceTransport |
The transport used by the client instance. |
universe_domain
Return the universe domain used by the client instance.
Returns | |
---|---|
Type | Description |
str |
The universe domain used by the client instance. |
Methods
ModelMonitoringServiceClient
ModelMonitoringServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1beta1.services.model_monitoring_service.transports.base.ModelMonitoringServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1beta1.services.model_monitoring_service.transports.base.ModelMonitoringServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Instantiates the model monitoring service client.
Parameters | |
---|---|
Name | Description |
credentials |
Optional[google.auth.credentials.Credentials]
The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment. |
transport |
Optional[Union[str,ModelMonitoringServiceTransport,Callable[..., ModelMonitoringServiceTransport]]]
The transport to use, or a Callable that constructs and returns a new transport. If a Callable is given, it will be called with the same set of initialization arguments as used in the ModelMonitoringServiceTransport constructor. If set to None, a transport is chosen automatically. NOTE: "rest" transport functionality is currently in a beta state (preview). We welcome your feedback via an issue in this library's source repository. |
client_options |
Optional[Union[google.api_core.client_options.ClientOptions, dict]]
Custom options for the client. 1. The |
client_info |
google.api_core.gapic_v1.client_info.ClientInfo
The client info used to send a user-agent string along with API requests. If |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTLSChannelError |
If mutual TLS transport creation failed for any reason. |
__exit__
__exit__(type, value, traceback)
Releases underlying transport's resources.
batch_prediction_job_path
batch_prediction_job_path(
project: str, location: str, batch_prediction_job: str
) -> str
Returns a fully-qualified batch_prediction_job string.
cancel_operation
cancel_operation(
request: typing.Optional[
google.longrunning.operations_pb2.CancelOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Starts asynchronous cancellation on a long-running operation.
The server makes a best effort to cancel the operation, but success
is not guaranteed. If the server doesn't support this method, it returns
google.rpc.Code.UNIMPLEMENTED
.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
common_billing_account_path
common_billing_account_path(billing_account: str) -> str
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str) -> str
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str) -> str
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str) -> str
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str) -> str
Returns a fully-qualified project string.
create_model_monitor
create_model_monitor(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.CreateModelMonitorRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
model_monitor: typing.Optional[
google.cloud.aiplatform_v1beta1.types.model_monitor.ModelMonitor
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
Creates a ModelMonitor.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_create_model_monitor():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.CreateModelMonitorRequest(
parent="parent_value",
)
# Make the request
operation = client.create_model_monitor(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.CreateModelMonitorRequest, dict]
The request object. Request message for ModelMonitoringService.CreateModelMonitor. |
parent |
str
Required. The resource name of the Location to create the ModelMonitor in. Format: |
model_monitor |
google.cloud.aiplatform_v1beta1.types.ModelMonitor
Required. The ModelMonitor to create. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation.Operation |
An object representing a long-running operation. The result type for the operation will be ModelMonitor Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks. |
create_model_monitoring_job
create_model_monitoring_job(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.CreateModelMonitoringJobRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
model_monitoring_job: typing.Optional[
google.cloud.aiplatform_v1beta1.types.model_monitoring_job.ModelMonitoringJob
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.model_monitoring_job.ModelMonitoringJob
Creates a ModelMonitoringJob.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_create_model_monitoring_job():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.CreateModelMonitoringJobRequest(
parent="parent_value",
)
# Make the request
response = client.create_model_monitoring_job(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.CreateModelMonitoringJobRequest, dict]
The request object. Request message for ModelMonitoringService.CreateModelMonitoringJob. |
parent |
str
Required. The parent of the ModelMonitoringJob. Format: |
model_monitoring_job |
google.cloud.aiplatform_v1beta1.types.ModelMonitoringJob
Required. The ModelMonitoringJob to create This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.ModelMonitoringJob |
Represents a model monitoring job that analyze dataset using different monitoring algorithm. |
dataset_path
dataset_path(project: str, location: str, dataset: str) -> str
Returns a fully-qualified dataset string.
delete_model_monitor
delete_model_monitor(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.DeleteModelMonitorRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
Deletes a ModelMonitor.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_delete_model_monitor():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.DeleteModelMonitorRequest(
name="name_value",
)
# Make the request
operation = client.delete_model_monitor(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.DeleteModelMonitorRequest, dict]
The request object. Request message for ModelMonitoringService.DeleteModelMonitor. |
name |
str
Required. The name of the ModelMonitor resource to be deleted. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation.Operation |
An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } |
delete_model_monitoring_job
delete_model_monitoring_job(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.DeleteModelMonitoringJobRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
Deletes a ModelMonitoringJob.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_delete_model_monitoring_job():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.DeleteModelMonitoringJobRequest(
name="name_value",
)
# Make the request
operation = client.delete_model_monitoring_job(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.DeleteModelMonitoringJobRequest, dict]
The request object. Request message for ModelMonitoringService.DeleteModelMonitoringJob. |
name |
str
Required. The resource name of the model monitoring job to delete. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation.Operation |
An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } |
delete_operation
delete_operation(
request: typing.Optional[
google.longrunning.operations_pb2.DeleteOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Deletes a long-running operation.
This method indicates that the client is no longer interested
in the operation result. It does not cancel the operation.
If the server doesn't support this method, it returns
google.rpc.Code.UNIMPLEMENTED
.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
endpoint_path
endpoint_path(project: str, location: str, endpoint: str) -> str
Returns a fully-qualified endpoint string.
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
ModelMonitoringServiceClient |
The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Parameter | |
---|---|
Name | Description |
info |
dict
The service account private key info. |
Returns | |
---|---|
Type | Description |
ModelMonitoringServiceClient |
The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
ModelMonitoringServiceClient |
The constructed client. |
get_iam_policy
get_iam_policy(
request: typing.Optional[google.iam.v1.iam_policy_pb2.GetIamPolicyRequest] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy
Gets the IAM access control policy for a function.
Returns an empty policy if the function exists and does not have a policy set.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings . A binding binds one or more members to a single role . Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition , which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __. |
get_location
get_location(
request: typing.Optional[
google.cloud.location.locations_pb2.GetLocationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.Location
Gets information about a location.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
Location object. |
get_model_monitor
get_model_monitor(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.GetModelMonitorRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.model_monitor.ModelMonitor
Gets a ModelMonitor.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_get_model_monitor():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.GetModelMonitorRequest(
name="name_value",
)
# Make the request
response = client.get_model_monitor(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.GetModelMonitorRequest, dict]
The request object. Request message for ModelMonitoringService.GetModelMonitor. |
name |
str
Required. The name of the ModelMonitor resource. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.ModelMonitor |
Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks. |
get_model_monitoring_job
get_model_monitoring_job(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.GetModelMonitoringJobRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.model_monitoring_job.ModelMonitoringJob
Gets a ModelMonitoringJob.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_get_model_monitoring_job():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.GetModelMonitoringJobRequest(
name="name_value",
)
# Make the request
response = client.get_model_monitoring_job(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.GetModelMonitoringJobRequest, dict]
The request object. Request message for ModelMonitoringService.GetModelMonitoringJob. |
name |
str
Required. The resource name of the ModelMonitoringJob. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.ModelMonitoringJob |
Represents a model monitoring job that analyze dataset using different monitoring algorithm. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: typing.Optional[
google.api_core.client_options.ClientOptions
] = None,
)
Deprecated. 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 variable 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.
Parameter | |
---|---|
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTLSChannelError |
If any errors happen. |
Returns | |
---|---|
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] |
returns the API endpoint and the client cert source to use. |
get_operation
get_operation(
request: typing.Optional[
google.longrunning.operations_pb2.GetOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation
Gets the latest state of a long-running operation.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
An Operation object. |
list_locations
list_locations(
request: typing.Optional[
google.cloud.location.locations_pb2.ListLocationsRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.ListLocationsResponse
Lists information about the supported locations for this service.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
Response message for ListLocations method. |
list_model_monitoring_jobs
list_model_monitoring_jobs(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.ListModelMonitoringJobsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.ListModelMonitoringJobsPager
)
Lists ModelMonitoringJobs. Callers may choose to read across
multiple Monitors as per
AIP-159 <https://google.aip.dev/159>
__ by using '-' (the
hyphen or dash character) as a wildcard character instead of
modelMonitor id in the parent. Format
projects/{project_id}/locations/{location}/moodelMonitors/-/modelMonitoringJobs
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_list_model_monitoring_jobs():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.ListModelMonitoringJobsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_model_monitoring_jobs(request=request)
# Handle the response
for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ListModelMonitoringJobsRequest, dict]
The request object. Request message for ModelMonitoringService.ListModelMonitoringJobs. |
parent |
str
Required. The parent of the ModelMonitoringJob. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.ListModelMonitoringJobsPager |
Response message for ModelMonitoringService.ListModelMonitoringJobs. Iterating over this object will yield results and resolve additional pages automatically. |
list_model_monitors
list_model_monitors(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.ListModelMonitorsRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.ListModelMonitorsPager
)
Lists ModelMonitors in a Location.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_list_model_monitors():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.ListModelMonitorsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_model_monitors(request=request)
# Handle the response
for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.ListModelMonitorsRequest, dict]
The request object. Request message for ModelMonitoringService.ListModelMonitors. |
parent |
str
Required. The resource name of the Location to list the ModelMonitors from. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.ListModelMonitorsPager |
Response message for ModelMonitoringService.ListModelMonitors Iterating over this object will yield results and resolve additional pages automatically. |
list_operations
list_operations(
request: typing.Optional[
google.longrunning.operations_pb2.ListOperationsRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse
Lists operations that match the specified filter in the request.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
Response message for ListOperations method. |
model_monitor_path
model_monitor_path(project: str, location: str, model_monitor: str) -> str
Returns a fully-qualified model_monitor string.
model_monitoring_job_path
model_monitoring_job_path(
project: str, location: str, model_monitor: str, model_monitoring_job: str
) -> str
Returns a fully-qualified model_monitoring_job string.
model_path
model_path(project: str, location: str, model: str) -> str
Returns a fully-qualified model string.
parse_batch_prediction_job_path
parse_batch_prediction_job_path(path: str) -> typing.Dict[str, str]
Parses a batch_prediction_job path into its component segments.
parse_common_billing_account_path
parse_common_billing_account_path(path: str) -> typing.Dict[str, str]
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str) -> typing.Dict[str, str]
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str) -> typing.Dict[str, str]
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str) -> typing.Dict[str, str]
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str) -> typing.Dict[str, str]
Parse a project path into its component segments.
parse_dataset_path
parse_dataset_path(path: str) -> typing.Dict[str, str]
Parses a dataset path into its component segments.
parse_endpoint_path
parse_endpoint_path(path: str) -> typing.Dict[str, str]
Parses a endpoint path into its component segments.
parse_model_monitor_path
parse_model_monitor_path(path: str) -> typing.Dict[str, str]
Parses a model_monitor path into its component segments.
parse_model_monitoring_job_path
parse_model_monitoring_job_path(path: str) -> typing.Dict[str, str]
Parses a model_monitoring_job path into its component segments.
parse_model_path
parse_model_path(path: str) -> typing.Dict[str, str]
Parses a model path into its component segments.
parse_schedule_path
parse_schedule_path(path: str) -> typing.Dict[str, str]
Parses a schedule path into its component segments.
schedule_path
schedule_path(project: str, location: str, schedule: str) -> str
Returns a fully-qualified schedule string.
search_model_monitoring_alerts
search_model_monitoring_alerts(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.SearchModelMonitoringAlertsRequest,
dict,
]
] = None,
*,
model_monitor: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringAlertsPager
)
Returns the Model Monitoring alerts.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_search_model_monitoring_alerts():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.SearchModelMonitoringAlertsRequest(
model_monitor="model_monitor_value",
)
# Make the request
page_result = client.search_model_monitoring_alerts(request=request)
# Handle the response
for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.SearchModelMonitoringAlertsRequest, dict]
The request object. Request message for ModelMonitoringService.SearchModelMonitoringAlerts. |
model_monitor |
str
Required. ModelMonitor resource name. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringAlertsPager |
Response message for ModelMonitoringService.SearchModelMonitoringAlerts. Iterating over this object will yield results and resolve additional pages automatically. |
search_model_monitoring_stats
search_model_monitoring_stats(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.SearchModelMonitoringStatsRequest,
dict,
]
] = None,
*,
model_monitor: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringStatsPager
)
Searches Model Monitoring Stats generated within a given time window.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_search_model_monitoring_stats():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.SearchModelMonitoringStatsRequest(
model_monitor="model_monitor_value",
)
# Make the request
page_result = client.search_model_monitoring_stats(request=request)
# Handle the response
for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.SearchModelMonitoringStatsRequest, dict]
The request object. Request message for ModelMonitoringService.SearchModelMonitoringStats. |
model_monitor |
str
Required. ModelMonitor resource name. Format: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringStatsPager |
Response message for ModelMonitoringService.SearchModelMonitoringStats. Iterating over this object will yield results and resolve additional pages automatically. |
set_iam_policy
set_iam_policy(
request: typing.Optional[google.iam.v1.iam_policy_pb2.SetIamPolicyRequest] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy
Sets the IAM access control policy on the specified function.
Replaces any existing policy.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings . A binding binds one or more members to a single role . Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition , which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __. |
test_iam_permissions
test_iam_permissions(
request: typing.Optional[
google.iam.v1.iam_policy_pb2.TestIamPermissionsRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.iam_policy_pb2.TestIamPermissionsResponse
Tests the specified IAM permissions against the IAM access control policy for a function.
If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
Response message for TestIamPermissions method. |
update_model_monitor
update_model_monitor(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.model_monitoring_service.UpdateModelMonitorRequest,
dict,
]
] = None,
*,
model_monitor: typing.Optional[
google.cloud.aiplatform_v1beta1.types.model_monitor.ModelMonitor
] = None,
update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
Updates a ModelMonitor.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1
def sample_update_model_monitor():
# Create a client
client = aiplatform_v1beta1.ModelMonitoringServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.UpdateModelMonitorRequest(
)
# Make the request
operation = client.update_model_monitor(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.aiplatform_v1beta1.types.UpdateModelMonitorRequest, dict]
The request object. Request message for ModelMonitoringService.UpdateModelMonitor. |
model_monitor |
google.cloud.aiplatform_v1beta1.types.ModelMonitor
Required. The model monitoring configuration which replaces the resource on the server. This corresponds to the |
update_mask |
google.protobuf.field_mask_pb2.FieldMask
Required. Mask specifying which fields to update. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
google.api_core.operation.Operation |
An object representing a long-running operation. The result type for the operation will be ModelMonitor Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks. |
wait_operation
wait_operation(
request: typing.Optional[
google.longrunning.operations_pb2.WaitOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation
Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.
If the operation is already done, the latest state is immediately returned.
If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC
timeout is used. If the server does not support this method, it returns
google.rpc.Code.UNIMPLEMENTED
.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Returns | |
---|---|
Type | Description |
|
An Operation object. |