pulumi-google-native-kotlin/com.pulumi.googlenative.notebooks.v1.kotlin.outputs/ExecutionTemplateResponse

ExecutionTemplateResponse

data class ExecutionTemplateResponse(val acceleratorConfig: SchedulerAcceleratorConfigResponse, val containerImageUri: String, val dataprocParameters: DataprocParametersResponse, val inputNotebookFile: String, val jobType: String, val kernelSpec: String, val labels: Map<String, String>, val masterType: String, val outputNotebookFolder: String, val parameters: String, val paramsYamlFile: String, val scaleTier: String, val serviceAccount: String, val tensorboard: String, val vertexAiParameters: VertexAIParametersResponse)

The description a notebook execution workload.

Constructors

fun ExecutionTemplateResponse(acceleratorConfig: SchedulerAcceleratorConfigResponse, containerImageUri: String, dataprocParameters: DataprocParametersResponse, inputNotebookFile: String, jobType: String, kernelSpec: String, labels: Map<String, String>, masterType: String, outputNotebookFolder: String, parameters: String, paramsYamlFile: String, scaleTier: String, serviceAccount: String, tensorboard: String, vertexAiParameters: VertexAIParametersResponse)

Types

Companion

object Companion

Properties

acceleratorConfig

val acceleratorConfig: SchedulerAcceleratorConfigResponse

Configuration (count and accelerator type) for hardware running notebook execution.

containerImageUri

val containerImageUri: String

Container Image URI to a DLVM Example: 'gcr.io/deeplearning-platform-release/base-cu100' More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container

dataprocParameters

val dataprocParameters: DataprocParametersResponse

Parameters used in Dataproc JobType executions.

inputNotebookFile

val inputNotebookFile: String

Path to the notebook file to execute. Must be in a Google Cloud Storage bucket. Format: gs://{bucket_name}/{folder}/{notebook_file_name} Ex: gs://notebook_user/scheduled_notebooks/sentiment_notebook.ipynb

jobType

val jobType: String

The type of Job to be used on this execution.

kernelSpec

val kernelSpec: String

Name of the kernel spec to use. This must be specified if the kernel spec name on the execution target does not match the name in the input notebook file.

labels

val labels: Map<String, String>

Labels for execution. If execution is scheduled, a field included will be 'nbs-scheduled'. Otherwise, it is an immediate execution, and an included field will be 'nbs-immediate'. Use fields to efficiently index between various types of executions.

masterType

val masterType: String

Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when scaleTier is set to CUSTOM. You can use certain Compute Engine machine types directly in this field. The following types are supported: - n1-standard-4 - n1-standard-8 - n1-standard-16 - n1-standard-32 - n1-standard-64 - n1-standard-96 - n1-highmem-2 - n1-highmem-4 - n1-highmem-8 - n1-highmem-16 - n1-highmem-32 - n1-highmem-64 - n1-highmem-96 - n1-highcpu-16 - n1-highcpu-32 - n1-highcpu-64 - n1-highcpu-96 Alternatively, you can use the following legacy machine types: - standard - large_model - complex_model_s - complex_model_m - complex_model_l - standard_gpu - complex_model_m_gpu - complex_model_l_gpu - standard_p100 - complex_model_m_p100 - standard_v100 - large_model_v100 - complex_model_m_v100 - complex_model_l_v100 Finally, if you want to use a TPU for training, specify cloud_tpu in this field. Learn more about the special configuration options for training with TPU.

outputNotebookFolder

val outputNotebookFolder: String

Path to the notebook folder to write to. Must be in a Google Cloud Storage bucket path. Format: gs://{bucket_name}/{folder} Ex: gs://notebook_user/scheduled_notebooks

parameters

val parameters: String

Parameters used within the 'input_notebook_file' notebook.

paramsYamlFile

val paramsYamlFile: String

Parameters to be overridden in the notebook during execution. Ref https://papermill.readthedocs.io/en/latest/usage-parameterize.html on how to specifying parameters in the input notebook and pass them here in an YAML file. Ex: gs://notebook_user/scheduled_notebooks/sentiment_notebook_params.yaml

scaleTier

val ~~scaleTier~~: String

Scale tier of the hardware used for notebook execution. DEPRECATED Will be discontinued. As right now only CUSTOM is supported.

serviceAccount

val serviceAccount: String

The email address of a service account to use when running the execution. You must have the iam.serviceAccounts.actAs permission for the specified service account.

tensorboard

val tensorboard: String

The name of a Vertex AI Tensorboard resource to which this execution will upload Tensorboard logs. Format: projects/{project}/locations/{location}/tensorboards/{tensorboard}

vertexAiParameters

val vertexAiParameters: VertexAIParametersResponse

Parameters used in Vertex AI JobType executions.