ExecutionTemplate (Notebooks API v1-rev20241016-2.0.0)

java.lang.Object
- java.util.AbstractMap<String,Object>
- - com.google.api.client.util.GenericData
  - - com.google.api.client.json.GenericJson
    - - com.google.api.services.notebooks.v1.model.ExecutionTemplate

All Implemented Interfaces:

Cloneable, Map<String,Object>
```
public final class ExecutionTemplate
extends com.google.api.client.json.GenericJson
```
The description a notebook execution workload.
This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the Notebooks API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary
- Nested classes/interfaces inherited from class com.google.api.client.util.GenericData
  com.google.api.client.util.GenericData.Flags
- Nested classes/interfaces inherited from class java.util.AbstractMap
  AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>
- Nested classes/interfaces inherited from interface java.util.Map
  Map.Entry<K,V>

Constructor Summary

Constructors
Constructor and Description

ExecutionTemplate()

Constructors
Constructor and Description
`ExecutionTemplate()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`ExecutionTemplate`	`clone()`
`SchedulerAcceleratorConfig`	`getAcceleratorConfig()` Configuration (count and accelerator type) for hardware running notebook execution.
`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
`DataprocParameters`	`getDataprocParameters()` Parameters used in Dataproc JobType executions.
`String`	`getInputNotebookFile()` Path to the notebook file to execute.
`String`	`getJobType()` The type of Job to be used on this execution.
`String`	`getKernelSpec()` Name of the kernel spec to use.
`Map<String,String>`	`getLabels()` Labels for execution.
`String`	`getMasterType()` Specifies the type of virtual machine to use for your training job's master worker.
`String`	`getOutputNotebookFolder()` Path to the notebook folder to write to.
`String`	`getParameters()` Parameters used within the 'input_notebook_file' notebook.
`String`	`getParamsYamlFile()` Parameters to be overridden in the notebook during execution.
`String`	`getScaleTier()` Required.
`String`	`getServiceAccount()` The email address of a service account to use when running the execution.
`String`	`getTensorboard()` The name of a Vertex AI [Tensorboard] resource to which this execution will upload Tensorboard logs.
`VertexAIParameters`	`getVertexAiParameters()` Parameters used in Vertex AI JobType executions.
`ExecutionTemplate`	`set(String fieldName, Object value)`
`ExecutionTemplate`	`setAcceleratorConfig(SchedulerAcceleratorConfig acceleratorConfig)` Configuration (count and accelerator type) for hardware running notebook execution.
`ExecutionTemplate`	`setContainerImageUri(String containerImageUri)` 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
`ExecutionTemplate`	`setDataprocParameters(DataprocParameters dataprocParameters)` Parameters used in Dataproc JobType executions.
`ExecutionTemplate`	`setInputNotebookFile(String inputNotebookFile)` Path to the notebook file to execute.
`ExecutionTemplate`	`setJobType(String jobType)` The type of Job to be used on this execution.
`ExecutionTemplate`	`setKernelSpec(String kernelSpec)` Name of the kernel spec to use.
`ExecutionTemplate`	`setLabels(Map<String,String> labels)` Labels for execution.
`ExecutionTemplate`	`setMasterType(String masterType)` Specifies the type of virtual machine to use for your training job's master worker.
`ExecutionTemplate`	`setOutputNotebookFolder(String outputNotebookFolder)` Path to the notebook folder to write to.
`ExecutionTemplate`	`setParameters(String parameters)` Parameters used within the 'input_notebook_file' notebook.
`ExecutionTemplate`	`setParamsYamlFile(String paramsYamlFile)` Parameters to be overridden in the notebook during execution.
`ExecutionTemplate`	`setScaleTier(String scaleTier)` Required.
`ExecutionTemplate`	`setServiceAccount(String serviceAccount)` The email address of a service account to use when running the execution.
`ExecutionTemplate`	`setTensorboard(String tensorboard)` The name of a Vertex AI [Tensorboard] resource to which this execution will upload Tensorboard logs.
`ExecutionTemplate`	`setVertexAiParameters(VertexAIParameters vertexAiParameters)` Parameters used in Vertex AI JobType executions.

Methods inherited from class com.google.api.client.json.GenericJson
getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData
entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap
clear, containsKey, containsValue, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object
finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map
compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

- Constructor Detail
  - ExecutionTemplate
```
public ExecutionTemplate()
```
- Method Detail
  - getAcceleratorConfig
```
public SchedulerAcceleratorConfig getAcceleratorConfig()
```
    Configuration (count and accelerator type) for hardware running notebook execution.
    
    Returns:
    
    value or null for none
  - setAcceleratorConfig
```
public ExecutionTemplate setAcceleratorConfig(SchedulerAcceleratorConfig acceleratorConfig)
```
    Configuration (count and accelerator type) for hardware running notebook execution.
    
    Parameters:
    
    acceleratorConfig - acceleratorConfig or null for none
  - getContainerImageUri
```
public 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
    
    Returns:
    
    value or null for none
  - setContainerImageUri
```
public ExecutionTemplate setContainerImageUri(String containerImageUri)
```
    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
    
    Parameters:
    
    containerImageUri - containerImageUri or null for none
  - getDataprocParameters
```
public DataprocParameters getDataprocParameters()
```
    Parameters used in Dataproc JobType executions.
    
    Returns:
    
    value or null for none
  - setDataprocParameters
```
public ExecutionTemplate setDataprocParameters(DataprocParameters dataprocParameters)
```
    Parameters used in Dataproc JobType executions.
    
    Parameters:
    
    dataprocParameters - dataprocParameters or null for none
  - getInputNotebookFile
```
public String getInputNotebookFile()
```
    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`
    
    Returns:
    
    value or null for none
  - setInputNotebookFile
```
public ExecutionTemplate setInputNotebookFile(String inputNotebookFile)
```
    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`
    
    Parameters:
    
    inputNotebookFile - inputNotebookFile or null for none
  - getJobType
```
public String getJobType()
```
    The type of Job to be used on this execution.
    
    Returns:
    
    value or null for none
  - setJobType
```
public ExecutionTemplate setJobType(String jobType)
```
    The type of Job to be used on this execution.
    
    Parameters:
    
    jobType - jobType or null for none
  - getKernelSpec
```
public String getKernelSpec()
```
    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.
    
    Returns:
    
    value or null for none
  - setKernelSpec
```
public ExecutionTemplate setKernelSpec(String kernelSpec)
```
    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.
    
    Parameters:
    
    kernelSpec - kernelSpec or null for none
  - getLabels
```
public Map<String,String> getLabels()
```
    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.
    
    Returns:
    
    value or null for none
  - setLabels
```
public ExecutionTemplate setLabels(Map<String,String> labels)
```
    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.
    
    Parameters:
    
    labels - labels or null for none
  - getMasterType
```
public 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](https://cloud.google.com/ai- platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).
    
    Returns:
    
    value or null for none
  - setMasterType
```
public ExecutionTemplate setMasterType(String masterType)
```
    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](https://cloud.google.com/ai- platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).
    
    Parameters:
    
    masterType - masterType or null for none
  - getOutputNotebookFolder
```
public String getOutputNotebookFolder()
```
    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`
    
    Returns:
    
    value or null for none
  - setOutputNotebookFolder
```
public ExecutionTemplate setOutputNotebookFolder(String outputNotebookFolder)
```
    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:
    
    outputNotebookFolder - outputNotebookFolder or null for none
  - getParameters
```
public String getParameters()
```
    Parameters used within the 'input_notebook_file' notebook.
    
    Returns:
    
    value or null for none
  - setParameters
```
public ExecutionTemplate setParameters(String parameters)
```
    Parameters used within the 'input_notebook_file' notebook.
    
    Parameters:
    
    parameters - parameters or null for none
  - getParamsYamlFile
```
public 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`
    
    Returns:
    
    value or null for none
  - setParamsYamlFile
```
public ExecutionTemplate setParamsYamlFile(String paramsYamlFile)
```
    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`
    
    Parameters:
    
    paramsYamlFile - paramsYamlFile or null for none
  - getScaleTier
```
public String getScaleTier()
```
    Required. Scale tier of the hardware used for notebook execution. DEPRECATED Will be discontinued. As right now only CUSTOM is supported.
    
    Returns:
    
    value or null for none
  - setScaleTier
```
public ExecutionTemplate setScaleTier(String scaleTier)
```
    Required. Scale tier of the hardware used for notebook execution. DEPRECATED Will be discontinued. As right now only CUSTOM is supported.
    
    Parameters:
    
    scaleTier - scaleTier or null for none
  - getServiceAccount
```
public 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.
    
    Returns:
    
    value or null for none
  - setServiceAccount
```
public ExecutionTemplate setServiceAccount(String serviceAccount)
```
    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.
    
    Parameters:
    
    serviceAccount - serviceAccount or null for none
  - getTensorboard
```
public String getTensorboard()
```
    The name of a Vertex AI [Tensorboard] resource to which this execution will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
    
    Returns:
    
    value or null for none
  - setTensorboard
```
public ExecutionTemplate setTensorboard(String tensorboard)
```
    The name of a Vertex AI [Tensorboard] resource to which this execution will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
    
    Parameters:
    
    tensorboard - tensorboard or null for none
  - getVertexAiParameters
```
public VertexAIParameters getVertexAiParameters()
```
    Parameters used in Vertex AI JobType executions.
    
    Returns:
    
    value or null for none
  - setVertexAiParameters
```
public ExecutionTemplate setVertexAiParameters(VertexAIParameters vertexAiParameters)
```
    Parameters used in Vertex AI JobType executions.
    
    Parameters:
    
    vertexAiParameters - vertexAiParameters or null for none
  - set
```
public ExecutionTemplate set(String fieldName,
                             Object value)
```
    Overrides:
    
    set in class com.google.api.client.json.GenericJson
  - clone
```
public ExecutionTemplate clone()
```
    Overrides:
    
    clone in class com.google.api.client.json.GenericJson

Class ExecutionTemplate

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

Nested classes/interfaces inherited from class java.util.AbstractMap

Nested classes/interfaces inherited from interface java.util.Map

Constructor Summary

Method Summary

Methods inherited from class com.google.api.client.json.GenericJson

Methods inherited from class com.google.api.client.util.GenericData

Methods inherited from class java.util.AbstractMap

Methods inherited from class java.lang.Object

Methods inherited from interface java.util.Map

Constructor Detail

ExecutionTemplate

Method Detail

getAcceleratorConfig

setAcceleratorConfig

getContainerImageUri

setContainerImageUri

getDataprocParameters

setDataprocParameters

getInputNotebookFile

setInputNotebookFile

getJobType

setJobType

getKernelSpec

setKernelSpec

getLabels

setLabels

getMasterType

setMasterType

getOutputNotebookFolder

setOutputNotebookFolder

getParameters

setParameters

getParamsYamlFile

setParamsYamlFile

getScaleTier

setScaleTier

getServiceAccount

setServiceAccount

getTensorboard

setTensorboard

getVertexAiParameters

setVertexAiParameters

set

clone