Interface ExecutionTemplateOrBuilder

public interface ExecutionTemplateOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

containsLabels(String key)

public abstract boolean containsLabels(String key)

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.

map<string, string> labels = 4;

Parameter
NameDescription
keyString
Returns
TypeDescription
boolean

getAcceleratorConfig()

public abstract ExecutionTemplate.SchedulerAcceleratorConfig getAcceleratorConfig()

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

.google.cloud.notebooks.v1.ExecutionTemplate.SchedulerAcceleratorConfig accelerator_config = 3;

Returns
TypeDescription
ExecutionTemplate.SchedulerAcceleratorConfig

The acceleratorConfig.

getAcceleratorConfigOrBuilder()

public abstract ExecutionTemplate.SchedulerAcceleratorConfigOrBuilder getAcceleratorConfigOrBuilder()

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

.google.cloud.notebooks.v1.ExecutionTemplate.SchedulerAcceleratorConfig accelerator_config = 3;

Returns
TypeDescription
ExecutionTemplate.SchedulerAcceleratorConfigOrBuilder

getContainerImageUri()

public abstract String getContainerImageUri()

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

string container_image_uri = 6;

Returns
TypeDescription
String

The containerImageUri.

getContainerImageUriBytes()

public abstract ByteString getContainerImageUriBytes()

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

string container_image_uri = 6;

Returns
TypeDescription
ByteString

The bytes for containerImageUri.

getDataprocParameters()

public abstract ExecutionTemplate.DataprocParameters getDataprocParameters()

Parameters used in Dataproc JobType executions.

.google.cloud.notebooks.v1.ExecutionTemplate.DataprocParameters dataproc_parameters = 12;

Returns
TypeDescription
ExecutionTemplate.DataprocParameters

The dataprocParameters.

getDataprocParametersOrBuilder()

public abstract ExecutionTemplate.DataprocParametersOrBuilder getDataprocParametersOrBuilder()

Parameters used in Dataproc JobType executions.

.google.cloud.notebooks.v1.ExecutionTemplate.DataprocParameters dataproc_parameters = 12;

Returns
TypeDescription
ExecutionTemplate.DataprocParametersOrBuilder

getInputNotebookFile()

public abstract String getInputNotebookFile()

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

string input_notebook_file = 5;

Returns
TypeDescription
String

The inputNotebookFile.

getInputNotebookFileBytes()

public abstract ByteString getInputNotebookFileBytes()

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

string input_notebook_file = 5;

Returns
TypeDescription
ByteString

The bytes for inputNotebookFile.

getJobParametersCase()

public abstract ExecutionTemplate.JobParametersCase getJobParametersCase()
Returns
TypeDescription
ExecutionTemplate.JobParametersCase

getJobType()

public abstract ExecutionTemplate.JobType getJobType()

The type of Job to be used on this execution.

.google.cloud.notebooks.v1.ExecutionTemplate.JobType job_type = 11;

Returns
TypeDescription
ExecutionTemplate.JobType

The jobType.

getJobTypeValue()

public abstract int getJobTypeValue()

The type of Job to be used on this execution.

.google.cloud.notebooks.v1.ExecutionTemplate.JobType job_type = 11;

Returns
TypeDescription
int

The enum numeric value on the wire for jobType.

getLabels()

public abstract Map<String,String> getLabels()

Use #getLabelsMap() instead.

Returns
TypeDescription
Map<String,String>

getLabelsCount()

public abstract int getLabelsCount()

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.

map<string, string> labels = 4;

Returns
TypeDescription
int

getLabelsMap()

public abstract Map<String,String> getLabelsMap()

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.

map<string, string> labels = 4;

Returns
TypeDescription
Map<String,String>

getLabelsOrDefault(String key, String defaultValue)

public abstract String getLabelsOrDefault(String key, String defaultValue)

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.

map<string, string> labels = 4;

Parameters
NameDescription
keyString
defaultValueString
Returns
TypeDescription
String

getLabelsOrThrow(String key)

public abstract String getLabelsOrThrow(String key)

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.

map<string, string> labels = 4;

Parameter
NameDescription
keyString
Returns
TypeDescription
String

getMasterType()

public abstract String getMasterType()

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.

string master_type = 2;

Returns
TypeDescription
String

The masterType.

getMasterTypeBytes()

public abstract ByteString getMasterTypeBytes()

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.

string master_type = 2;

Returns
TypeDescription
ByteString

The bytes for masterType.

getOutputNotebookFolder()

public abstract String getOutputNotebookFolder()

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

string output_notebook_folder = 7;

Returns
TypeDescription
String

The outputNotebookFolder.

getOutputNotebookFolderBytes()

public abstract ByteString getOutputNotebookFolderBytes()

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

string output_notebook_folder = 7;

Returns
TypeDescription
ByteString

The bytes for outputNotebookFolder.

getParameters()

public abstract String getParameters()

Parameters used within the 'input_notebook_file' notebook.

string parameters = 9;

Returns
TypeDescription
String

The parameters.

getParametersBytes()

public abstract ByteString getParametersBytes()

Parameters used within the 'input_notebook_file' notebook.

string parameters = 9;

Returns
TypeDescription
ByteString

The bytes for parameters.

getParamsYamlFile()

public abstract String getParamsYamlFile()

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

string params_yaml_file = 8;

Returns
TypeDescription
String

The paramsYamlFile.

getParamsYamlFileBytes()

public abstract ByteString getParamsYamlFileBytes()

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

string params_yaml_file = 8;

Returns
TypeDescription
ByteString

The bytes for paramsYamlFile.

getScaleTier()

public abstract ExecutionTemplate.ScaleTier getScaleTier()

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

.google.cloud.notebooks.v1.ExecutionTemplate.ScaleTier scale_tier = 1 [deprecated = true, (.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
ExecutionTemplate.ScaleTier

The scaleTier.

getScaleTierValue()

public abstract int getScaleTierValue()

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

.google.cloud.notebooks.v1.ExecutionTemplate.ScaleTier scale_tier = 1 [deprecated = true, (.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
int

The enum numeric value on the wire for scaleTier.

getServiceAccount()

public abstract String getServiceAccount()

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.

string service_account = 10;

Returns
TypeDescription
String

The serviceAccount.

getServiceAccountBytes()

public abstract ByteString getServiceAccountBytes()

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.

string service_account = 10;

Returns
TypeDescription
ByteString

The bytes for serviceAccount.

hasAcceleratorConfig()

public abstract boolean hasAcceleratorConfig()

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

.google.cloud.notebooks.v1.ExecutionTemplate.SchedulerAcceleratorConfig accelerator_config = 3;

Returns
TypeDescription
boolean

Whether the acceleratorConfig field is set.

hasDataprocParameters()

public abstract boolean hasDataprocParameters()

Parameters used in Dataproc JobType executions.

.google.cloud.notebooks.v1.ExecutionTemplate.DataprocParameters dataproc_parameters = 12;

Returns
TypeDescription
boolean

Whether the dataprocParameters field is set.