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    Google Cloud Notebooks V1 Client - Class ExecutionTemplate (1.0.5)

    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 \ V1

    Methods

    __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 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 .

    ↳ accelerator_config
    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: gs://{bucket_name}/{folder}/{notebook_file_name} Ex: gs://notebook_user/scheduled_notebooks/sentiment_notebook.ipynb

    ↳ 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: gs://{bucket_name}/{folder} Ex: gs://notebook_user/scheduled_notebooks

    ↳ 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

    ↳ 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 iam.serviceAccounts.actAs permission for the specified service account.

    ↳ job_type
    int

    The type of Job to be used on this execution.

    ↳ dataproc_parameters
    ExecutionTemplate\DataprocParameters

    Parameters used in Dataproc JobType executions.

    ↳ vertex_ai_parameters
    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: projects/{project}/locations/{location}/tensorboards/{tensorboard}

    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, specify cloud_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, specify cloud_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
    ExecutionTemplate\SchedulerAcceleratorConfig |null

    hasAcceleratorConfig

    clearAcceleratorConfig

    setAcceleratorConfig

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

    Parameter
    Name
    Description
    var
    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
    ExecutionTemplate\DataprocParameters |null

    hasDataprocParameters

    setDataprocParameters

    Parameters used in Dataproc JobType executions.

    Parameter
    Name
    Description
    var
    ExecutionTemplate\DataprocParameters
    Returns
    Type
    Description
    $this

    getVertexAiParameters

    Parameters used in Vertex AI JobType executions.

    Returns
    Type
    Description
    ExecutionTemplate\VertexAIParameters |null

    hasVertexAiParameters

    setVertexAiParameters

    Parameters used in Vertex AI JobType executions.

    Parameter
    Name
    Description
    var
    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
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