Class: Google::Apis::NotebooksV1::ExecutionTemplate
- Inherits:
-
Object
- Object
- Google::Apis::NotebooksV1::ExecutionTemplate
- Includes:
- Core::Hashable, Core::JsonObjectSupport
- Defined in:
- lib/google/apis/notebooks_v1/classes.rb,
lib/google/apis/notebooks_v1/representations.rb,
lib/google/apis/notebooks_v1/representations.rb
Overview
The description a notebook execution workload.
Instance Attribute Summary collapse
-
#accelerator_config ⇒ Google::Apis::NotebooksV1::SchedulerAcceleratorConfig
Definition of a hardware accelerator.
-
#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 Corresponds to the JSON property
containerImageUri. -
#dataproc_parameters ⇒ Google::Apis::NotebooksV1::DataprocParameters
Parameters used in Dataproc JobType executions.
-
#input_notebook_file ⇒ String
Path to the notebook file to execute.
-
#job_type ⇒ String
The type of Job to be used on this execution.
-
#labels ⇒ Hash<String,String>
Labels for execution.
-
#master_type ⇒ String
Specifies the type of virtual machine to use for your training job's master worker.
-
#output_notebook_folder ⇒ String
Path to the notebook folder to write to.
-
#parameters ⇒ String
Parameters used within the 'input_notebook_file' notebook.
-
#params_yaml_file ⇒ String
Parameters to be overridden in the notebook during execution.
-
#scale_tier ⇒ String
Required.
-
#service_account ⇒ String
The email address of a service account to use when running the execution.
-
#vertex_ai_parameters ⇒ Google::Apis::NotebooksV1::VertexAiParameters
Parameters used in Vertex AI JobType executions.
Instance Method Summary collapse
-
#initialize(**args) ⇒ ExecutionTemplate
constructor
A new instance of ExecutionTemplate.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ ExecutionTemplate
Returns a new instance of ExecutionTemplate.
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 587 def initialize(**args) update!(**args) end |
Instance Attribute Details
#accelerator_config ⇒ Google::Apis::NotebooksV1::SchedulerAcceleratorConfig
Definition of a hardware accelerator. Note that not all combinations of type
and core_count are valid. Check GPUs on Compute Engine to find a valid combination. TPUs are not
supported.
Corresponds to the JSON property acceleratorConfig
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 495 def accelerator_config @accelerator_config end |
#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
Corresponds to the JSON property containerImageUri
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 502 def container_image_uri @container_image_uri end |
#dataproc_parameters ⇒ Google::Apis::NotebooksV1::DataprocParameters
Parameters used in Dataproc JobType executions.
Corresponds to the JSON property dataprocParameters
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 507 def dataproc_parameters @dataproc_parameters end |
#input_notebook_file ⇒ 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
Corresponds to the JSON property inputNotebookFile
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 514 def input_notebook_file @input_notebook_file end |
#job_type ⇒ String
The type of Job to be used on this execution.
Corresponds to the JSON property jobType
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 519 def job_type @job_type end |
#labels ⇒ Hash<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.
Corresponds to the JSON property labels
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 527 def labels @labels end |
#master_type ⇒ 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.
Corresponds to the JSON property masterType
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 547 def master_type @master_type end |
#output_notebook_folder ⇒ 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
Corresponds to the JSON property outputNotebookFolder
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 554 def output_notebook_folder @output_notebook_folder end |
#parameters ⇒ String
Parameters used within the 'input_notebook_file' notebook.
Corresponds to the JSON property parameters
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 559 def parameters @parameters end |
#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: gs://notebook_user/scheduled_notebooks/sentiment_notebook_params.yaml
Corresponds to the JSON property paramsYamlFile
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 567 def params_yaml_file @params_yaml_file end |
#scale_tier ⇒ String
Required. Scale tier of the hardware used for notebook execution. DEPRECATED
Will be discontinued. As right now only CUSTOM is supported.
Corresponds to the JSON property scaleTier
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 573 def scale_tier @scale_tier end |
#service_account ⇒ 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.
Corresponds to the JSON property serviceAccount
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 580 def service_account @service_account end |
#vertex_ai_parameters ⇒ Google::Apis::NotebooksV1::VertexAiParameters
Parameters used in Vertex AI JobType executions.
Corresponds to the JSON property vertexAiParameters
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 585 def vertex_ai_parameters @vertex_ai_parameters end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/notebooks_v1/classes.rb', line 592 def update!(**args) @accelerator_config = args[:accelerator_config] if args.key?(:accelerator_config) @container_image_uri = args[:container_image_uri] if args.key?(:container_image_uri) @dataproc_parameters = args[:dataproc_parameters] if args.key?(:dataproc_parameters) @input_notebook_file = args[:input_notebook_file] if args.key?(:input_notebook_file) @job_type = args[:job_type] if args.key?(:job_type) @labels = args[:labels] if args.key?(:labels) @master_type = args[:master_type] if args.key?(:master_type) @output_notebook_folder = args[:output_notebook_folder] if args.key?(:output_notebook_folder) @parameters = args[:parameters] if args.key?(:parameters) @params_yaml_file = args[:params_yaml_file] if args.key?(:params_yaml_file) @scale_tier = args[:scale_tier] if args.key?(:scale_tier) @service_account = args[:service_account] if args.key?(:service_account) @vertex_ai_parameters = args[:vertex_ai_parameters] if args.key?(:vertex_ai_parameters) end |