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DeploymentResourcePool(
deployment_resource_pool_name: str,
project: typing.Optional[str] = None,
location: typing.Optional[str] = None,
credentials: typing.Optional[google.auth.credentials.Credentials] = None,
)
Retrieves a DeploymentResourcePool.
Parameters |
|
---|---|
Name | Description |
deployment_resource_pool_name |
str
Required. The fully-qualified resource name or ID of the deployment resource pool. Example: "projects/123/locations/us-central1/deploymentResourcePools/456" or "456" when project and location are initialized or passed. |
project |
str
Optional. Project containing the deployment resource pool to retrieve. If not set, the project given to |
location |
str
Optional. Location containing the deployment resource pool to retrieve. If not set, the location given to |
credentials |
typing.Optional[google.auth.credentials.Credentials]
Optional[auth_credentials.Credentials]=None, Custom credentials to use to retrieve the deployment resource pool. If not set, the credentials given to |
Properties
create_time
Time this resource was created.
display_name
Display name of this resource.
encryption_spec
Customer-managed encryption key options for this Vertex AI resource.
If this is set, then all resources created by this Vertex AI resource will be encrypted with the provided encryption key.
gca_resource
The underlying resource proto representation.
labels
User-defined labels containing metadata about this resource.
Read more about labels at https://goo.gl/xmQnxf
name
Name of this resource.
resource_name
Full qualified resource name.
update_time
Time this resource was last updated.
Methods
create
create(
deployment_resource_pool_id: str,
project: typing.Optional[str] = None,
location: typing.Optional[str] = None,
metadata: typing.Sequence[typing.Tuple[str, str]] = (),
credentials: typing.Optional[google.auth.credentials.Credentials] = None,
machine_type: typing.Optional[str] = None,
min_replica_count: int = 1,
max_replica_count: int = 1,
accelerator_type: typing.Optional[str] = None,
accelerator_count: typing.Optional[int] = None,
autoscaling_target_cpu_utilization: typing.Optional[int] = None,
autoscaling_target_accelerator_duty_cycle: typing.Optional[int] = None,
sync=True,
create_request_timeout: typing.Optional[float] = None,
reservation_affinity_type: typing.Optional[str] = None,
reservation_affinity_key: typing.Optional[str] = None,
reservation_affinity_values: typing.Optional[typing.List[str]] = None,
spot: bool = False,
) -> google.cloud.aiplatform.models.DeploymentResourcePool
Creates a new DeploymentResourcePool.
Parameters | |
---|---|
Name | Description |
deployment_resource_pool_id |
str
Required. User-specified name for the new deployment resource pool. |
project |
str
Optional. Project containing the deployment resource pool to retrieve. If not set, the project given to |
location |
str
Optional. Location containing the deployment resource pool to retrieve. If not set, the location given to |
metadata |
Sequence[Tuple[str, str]]
Optional. Strings which should be sent along with the request as metadata. |
credentials |
typing.Optional[google.auth.credentials.Credentials]
Optional[auth_credentials.Credentials]=None, Optional. Custom credentials to use to retrieve the deployment resource pool. If not set, the credentials given to |
machine_type |
str
Optional. Machine type to use for the deployment resource pool. If not set, the default machine type of |
min_replica_count |
int
Optional. The minimum replica count of the new deployment resource pool. Each replica serves a copy of each model deployed on the deployment resource pool. If this value is less than |
max_replica_count |
int
Optional. The maximum replica count of the new deployment resource pool. |
accelerator_type |
str
Optional. Hardware accelerator type. Must also set accelerator_ count if used. One of NVIDIA_TESLA_K80, NVIDIA_TESLA_P100, NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, or NVIDIA_TESLA_A100. |
accelerator_count |
int
Optional. The number of accelerators attached to each replica. |
autoscaling_target_cpu_utilization |
int
Optional. Target CPU utilization value for autoscaling. A default value of 60 will be used if not specified. |
autoscaling_target_accelerator_duty_cycle |
int
Optional. Target accelerator duty cycle percentage to use for autoscaling. Must also set accelerator_type and accelerator count if specified. A default value of 60 will be used if accelerators are requested and this is not specified. |
create_request_timeout |
float
Optional. The create request timeout in seconds. |
reservation_affinity_type |
str
Optional. The type of reservation affinity. One of NO_RESERVATION, ANY_RESERVATION, SPECIFIC_RESERVATION, SPECIFIC_THEN_ANY_RESERVATION, SPECIFIC_THEN_NO_RESERVATION |
reservation_affinity_key |
str
Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use |
reservation_affinity_values |
List[str]
Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation. Format: 'projects/{project_id_or_number}/zones/{zone}/reservations/{reservation_name}' |
spot |
bool
Optional. Whether to schedule the deployment workload on spot VMs. |
sync |
bool
Optional. Whether to execute this method synchronously. If False, this method will be executed in a concurrent Future and any downstream object will be immediately returned and synced when the Future has completed. |
delete
delete(sync: bool = True) -> None
Deletes this Vertex AI resource. WARNING: This deletion is permanent.
Parameter | |
---|---|
Name | Description |
sync |
bool
Whether to execute this deletion synchronously. If False, this method will be executed in concurrent Future and any downstream object will be immediately returned and synced when the Future has completed. |
list
list(
filter: typing.Optional[str] = None,
order_by: typing.Optional[str] = None,
project: typing.Optional[str] = None,
location: typing.Optional[str] = None,
credentials: typing.Optional[google.auth.credentials.Credentials] = None,
) -> typing.List[google.cloud.aiplatform.models.DeploymentResourcePool]
Lists the deployment resource pools.
filter (str):
Optional. An expression for filtering the results of the request.
For field names both snake_case and camelCase are supported.
order_by (str):
Optional. A comma-separated list of fields to order by, sorted in
ascending order. Use "desc" after a field name for descending.
Supported fields: display_name
, create_time
, update_time
project (str):
Optional. Project to retrieve list from. If not set, project
set in aiplatform.init will be used.
location (str):
Optional. Location to retrieve list from. If not set, location
set in aiplatform.init will be used.
credentials (auth_credentials.Credentials):
Optional. Custom credentials to use to retrieve list. Overrides
credentials set in aiplatform.init.
query_deployed_models
query_deployed_models(
project: typing.Optional[str] = None,
location: typing.Optional[str] = None,
credentials: typing.Optional[google.auth.credentials.Credentials] = None,
) -> typing.List[google.cloud.aiplatform_v1.types.deployed_model_ref.DeployedModelRef]
Lists the deployed models using this resource pool.
Parameters | |
---|---|
Name | Description |
project |
str
Optional. Project to retrieve list from. If not set, project set in aiplatform.init will be used. |
location |
str
Optional. Location to retrieve list from. If not set, location set in aiplatform.init will be used. |
credentials |
auth_credentials.Credentials
Optional. Custom credentials to use to retrieve list. Overrides credentials set in aiplatform.init. |
to_dict
to_dict() -> typing.Dict[str, typing.Any]
Returns the resource proto as a dictionary.
wait
wait()
Helper method that blocks until all futures are complete.