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google-native.aiplatform/v1.Run
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Google Cloud Native is in preview. Google Cloud Classic is fully supported.
Creates a TensorboardRun. Auto-naming is currently not supported for this resource.
Create Run Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new Run(name: string, args: RunArgs, opts?: CustomResourceOptions);
@overload
def Run(resource_name: str,
args: RunArgs,
opts: Optional[ResourceOptions] = None)
@overload
def Run(resource_name: str,
opts: Optional[ResourceOptions] = None,
display_name: Optional[str] = None,
experiment_id: Optional[str] = None,
tensorboard_id: Optional[str] = None,
tensorboard_run_id: Optional[str] = None,
description: Optional[str] = None,
etag: Optional[str] = None,
labels: Optional[Mapping[str, str]] = None,
location: Optional[str] = None,
project: Optional[str] = None)
func NewRun(ctx *Context, name string, args RunArgs, opts ...ResourceOption) (*Run, error)
public Run(string name, RunArgs args, CustomResourceOptions? opts = null)
type: google-native:aiplatform/v1:Run
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args RunArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args RunArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args RunArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args RunArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args RunArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var runResource = new GoogleNative.Aiplatform.V1.Run("runResource", new()
{
DisplayName = "string",
ExperimentId = "string",
TensorboardId = "string",
TensorboardRunId = "string",
Description = "string",
Etag = "string",
Labels =
{
{ "string", "string" },
},
Location = "string",
Project = "string",
});
example, err := aiplatform.NewRun(ctx, "runResource", &aiplatform.RunArgs{
DisplayName: pulumi.String("string"),
ExperimentId: pulumi.String("string"),
TensorboardId: pulumi.String("string"),
TensorboardRunId: pulumi.String("string"),
Description: pulumi.String("string"),
Etag: pulumi.String("string"),
Labels: pulumi.StringMap{
"string": pulumi.String("string"),
},
Location: pulumi.String("string"),
Project: pulumi.String("string"),
})
var runResource = new Run("runResource", RunArgs.builder()
.displayName("string")
.experimentId("string")
.tensorboardId("string")
.tensorboardRunId("string")
.description("string")
.etag("string")
.labels(Map.of("string", "string"))
.location("string")
.project("string")
.build());
run_resource = google_native.aiplatform.v1.Run("runResource",
display_name="string",
experiment_id="string",
tensorboard_id="string",
tensorboard_run_id="string",
description="string",
etag="string",
labels={
"string": "string",
},
location="string",
project="string")
const runResource = new google_native.aiplatform.v1.Run("runResource", {
displayName: "string",
experimentId: "string",
tensorboardId: "string",
tensorboardRunId: "string",
description: "string",
etag: "string",
labels: {
string: "string",
},
location: "string",
project: "string",
});
type: google-native:aiplatform/v1:Run
properties:
description: string
displayName: string
etag: string
experimentId: string
labels:
string: string
location: string
project: string
tensorboardId: string
tensorboardRunId: string
Run Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
The Run resource accepts the following input properties:
- Display
Name string - User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
- Experiment
Id string - Tensorboard
Id string - Tensorboard
Run stringId - Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are
/a-z-/
. - Description string
- Description of this TensorboardRun.
- Etag string
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- Labels Dictionary<string, string>
- The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- Location string
- Project string
- Display
Name string - User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
- Experiment
Id string - Tensorboard
Id string - Tensorboard
Run stringId - Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are
/a-z-/
. - Description string
- Description of this TensorboardRun.
- Etag string
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- Labels map[string]string
- The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- Location string
- Project string
- display
Name String - User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
- experiment
Id String - tensorboard
Id String - tensorboard
Run StringId - Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are
/a-z-/
. - description String
- Description of this TensorboardRun.
- etag String
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels Map<String,String>
- The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location String
- project String
- display
Name string - User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
- experiment
Id string - tensorboard
Id string - tensorboard
Run stringId - Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are
/a-z-/
. - description string
- Description of this TensorboardRun.
- etag string
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels {[key: string]: string}
- The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location string
- project string
- display_
name str - User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
- experiment_
id str - tensorboard_
id str - tensorboard_
run_ strid - Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are
/a-z-/
. - description str
- Description of this TensorboardRun.
- etag str
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels Mapping[str, str]
- The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location str
- project str
- display
Name String - User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
- experiment
Id String - tensorboard
Id String - tensorboard
Run StringId - Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are
/a-z-/
. - description String
- Description of this TensorboardRun.
- etag String
- Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
- labels Map<String>
- The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location String
- project String
Outputs
All input properties are implicitly available as output properties. Additionally, the Run resource produces the following output properties:
- Create
Time string - Timestamp when this TensorboardRun was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- Name string
- Name of the TensorboardRun. Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
- Update
Time string - Timestamp when this TensorboardRun was last updated.
- Create
Time string - Timestamp when this TensorboardRun was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- Name string
- Name of the TensorboardRun. Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
- Update
Time string - Timestamp when this TensorboardRun was last updated.
- create
Time String - Timestamp when this TensorboardRun was created.
- id String
- The provider-assigned unique ID for this managed resource.
- name String
- Name of the TensorboardRun. Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
- update
Time String - Timestamp when this TensorboardRun was last updated.
- create
Time string - Timestamp when this TensorboardRun was created.
- id string
- The provider-assigned unique ID for this managed resource.
- name string
- Name of the TensorboardRun. Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
- update
Time string - Timestamp when this TensorboardRun was last updated.
- create_
time str - Timestamp when this TensorboardRun was created.
- id str
- The provider-assigned unique ID for this managed resource.
- name str
- Name of the TensorboardRun. Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
- update_
time str - Timestamp when this TensorboardRun was last updated.
- create
Time String - Timestamp when this TensorboardRun was created.
- id String
- The provider-assigned unique ID for this managed resource.
- name String
- Name of the TensorboardRun. Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}
- update
Time String - Timestamp when this TensorboardRun was last updated.
Package Details
- Repository
- Google Cloud Native pulumi/pulumi-google-native
- License
- Apache-2.0
Google Cloud Native is in preview. Google Cloud Classic is fully supported.