Reference documentation and code samples for the Google Cloud Notebooks V1 Client class ExecutionTemplate.
The description a notebook execution workload.
Generated from protobuf message google.cloud.notebooks.v1.ExecutionTemplate
Namespace
Google \ Cloud \ Notebooks \ V1Methods
__construct
Constructor.
Parameters | |
---|---|
Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ scale_tier |
int
Required. Scale tier of the hardware used for notebook execution. DEPRECATED Will be discontinued. As right now only CUSTOM is supported. |
↳ master_type |
string
Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when |
↳ accelerator_config |
Google\Cloud\Notebooks\V1\ExecutionTemplate\SchedulerAcceleratorConfig
Configuration (count and accelerator type) for hardware running notebook execution. |
↳ labels |
array|Google\Protobuf\Internal\MapField
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. |
↳ input_notebook_file |
string
Path to the notebook file to execute. Must be in a Google Cloud Storage bucket. Format: |
↳ container_image_uri |
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 |
↳ output_notebook_folder |
string
Path to the notebook folder to write to. Must be in a Google Cloud Storage bucket path. Format: |
↳ params_yaml_file |
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: |
↳ parameters |
string
Parameters used within the 'input_notebook_file' notebook. |
↳ service_account |
string
The email address of a service account to use when running the execution. You must have the |
↳ job_type |
int
The type of Job to be used on this execution. |
↳ dataproc_parameters |
Google\Cloud\Notebooks\V1\ExecutionTemplate\DataprocParameters
Parameters used in Dataproc JobType executions. |
↳ vertex_ai_parameters |
Google\Cloud\Notebooks\V1\ExecutionTemplate\VertexAIParameters
Parameters used in Vertex AI JobType executions. |
↳ kernel_spec |
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. |
↳ tensorboard |
string
The name of a Vertex AI [Tensorboard] resource to which this execution will upload Tensorboard logs. Format: |
getScaleTier
Required. Scale tier of the hardware used for notebook execution.
DEPRECATED Will be discontinued. As right now only CUSTOM is supported.
Returns | |
---|---|
Type | Description |
int |
setScaleTier
Required. Scale tier of the hardware used for notebook execution.
DEPRECATED Will be discontinued. As right now only CUSTOM is supported.
Parameter | |
---|---|
Name | Description |
var |
int
|
Returns | |
---|---|
Type | Description |
$this |
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, specifycloud_tpu
in this field. Learn more about the special configuration options for training with TPU.
Returns | |
---|---|
Type | Description |
string |
setMasterType
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, specifycloud_tpu
in this field. Learn more about the special configuration options for training with TPU.
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
getAcceleratorConfig
Configuration (count and accelerator type) for hardware running notebook execution.
Returns | |
---|---|
Type | Description |
Google\Cloud\Notebooks\V1\ExecutionTemplate\SchedulerAcceleratorConfig|null |
hasAcceleratorConfig
clearAcceleratorConfig
setAcceleratorConfig
Configuration (count and accelerator type) for hardware running notebook execution.
Parameter | |
---|---|
Name | Description |
var |
Google\Cloud\Notebooks\V1\ExecutionTemplate\SchedulerAcceleratorConfig
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
Google\Protobuf\Internal\MapField |
setLabels
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.
Parameter | |
---|---|
Name | Description |
var |
array|Google\Protobuf\Internal\MapField
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
string |
setInputNotebookFile
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
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
string |
setContainerImageUri
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
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
string |
setOutputNotebookFolder
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
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
string |
setParamsYamlFile
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
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
getParameters
Parameters used within the 'input_notebook_file' notebook.
Returns | |
---|---|
Type | Description |
string |
setParameters
Parameters used within the 'input_notebook_file' notebook.
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
string |
setServiceAccount
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.
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
getJobType
The type of Job to be used on this execution.
Returns | |
---|---|
Type | Description |
int |
setJobType
The type of Job to be used on this execution.
Parameter | |
---|---|
Name | Description |
var |
int
|
Returns | |
---|---|
Type | Description |
$this |
getDataprocParameters
Parameters used in Dataproc JobType executions.
Returns | |
---|---|
Type | Description |
Google\Cloud\Notebooks\V1\ExecutionTemplate\DataprocParameters|null |
hasDataprocParameters
setDataprocParameters
Parameters used in Dataproc JobType executions.
Parameter | |
---|---|
Name | Description |
var |
Google\Cloud\Notebooks\V1\ExecutionTemplate\DataprocParameters
|
Returns | |
---|---|
Type | Description |
$this |
getVertexAiParameters
Parameters used in Vertex AI JobType executions.
Returns | |
---|---|
Type | Description |
Google\Cloud\Notebooks\V1\ExecutionTemplate\VertexAIParameters|null |
hasVertexAiParameters
setVertexAiParameters
Parameters used in Vertex AI JobType executions.
Parameter | |
---|---|
Name | Description |
var |
Google\Cloud\Notebooks\V1\ExecutionTemplate\VertexAIParameters
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
string |
setKernelSpec
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.
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
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 | |
---|---|
Type | Description |
string |
setTensorboard
The name of a Vertex AI [Tensorboard] resource to which this execution will upload Tensorboard logs.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}
Parameter | |
---|---|
Name | Description |
var |
string
|
Returns | |
---|---|
Type | Description |
$this |
getJobParameters
Returns | |
---|---|
Type | Description |
string |