ExecutionTemplate(mapping=None, *, ignore_unknown_fields=False, **kwargs)
The description a notebook execution workload. .. attribute:: scale_tier
Required. Scale tier of the hardware used for notebook execution. DEPRECATED Will be discontinued. As right now only CUSTOM is supported.
:type: google.cloud.notebooks_v1.types.ExecutionTemplate.ScaleTier
Attributes | |
---|---|
Name | Description |
master_type |
str
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 |
google.cloud.notebooks_v1.types.ExecutionTemplate.SchedulerAcceleratorConfig
Configuration (count and accelerator type) for hardware running notebook execution. |
labels |
Sequence[google.cloud.notebooks_v1.types.ExecutionTemplate.LabelsEntry]
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 |
str
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
|
container_image_uri |
str
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 |
str
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
|
params_yaml_file |
str
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 |
str
Parameters used within the 'input_notebook_file' notebook. |
service_account |
str
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 |
google.cloud.notebooks_v1.types.ExecutionTemplate.JobType
The type of Job to be used on this execution. |
dataproc_parameters |
google.cloud.notebooks_v1.types.ExecutionTemplate.DataprocParameters
Parameters used in Dataproc JobType executions. |
Classes
DataprocParameters
DataprocParameters(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Parameters used in Dataproc JobType executions. .. attribute:: cluster
URI for cluster used to run Dataproc execution. Format:
projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
:type: str
JobType
JobType(value)
The backend used for this execution.
LabelsEntry
LabelsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)
The abstract base class for a message.
Parameters | |
---|---|
Name | Description |
kwargs |
dict
Keys and values corresponding to the fields of the message. |
mapping |
Union[dict,
A dictionary or message to be used to determine the values for this message. |
ignore_unknown_fields |
Optional(bool)
If True, do not raise errors for unknown fields. Only applied if |
ScaleTier
ScaleTier(value)
Required. Specifies the machine types, the number of replicas for workers and parameter servers.
SchedulerAcceleratorConfig
SchedulerAcceleratorConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)
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.
SchedulerAcceleratorType
SchedulerAcceleratorType(value)
Hardware accelerator types for AI Platform Training jobs.