class Google::Apis::NotebooksV1::ExecutionTemplate
The description a notebook execution workload.
Attributes
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` @return [Google::Apis::NotebooksV1::SchedulerAcceleratorConfig]
Container Image URI to a DLVM Example: 'gcr.io/deeplearning-platform-release/ base-cu100' More examples can be found at: cloud.google.com/ai- platform/deep-learning-containers/docs/choosing-container Corresponds to the JSON property `containerImageUri` @return [String]
Parameters used in Dataproc JobType executions. Corresponds to the JSON property `dataprocParameters` @return [Google::Apis::NotebooksV1::DataprocParameters]
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 Corresponds to the JSON property `inputNotebookFile` @return [String]
The type of Job to be used on this execution. Corresponds to the JSON property `jobType` @return [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` @return [Hash<String,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` @return [String]
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 Corresponds to the JSON property `outputNotebookFolder` @return [String]
Parameters used within the 'input_notebook_file' notebook. Corresponds to the JSON property `parameters` @return [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` @return [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` @return [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` @return [String]
Public Class Methods
# File lib/google/apis/notebooks_v1/classes.rb, line 580 def initialize(**args) update!(**args) end
Public Instance Methods
Update properties of this object
# File lib/google/apis/notebooks_v1/classes.rb, line 585 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) end