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feat(notebooks): update the api
#### notebooks:v1 The following keys were added: - schemas.DataprocParameters (Total Keys: 3) - schemas.ExecutionTemplate.properties.dataprocParameters.$ref (Total Keys: 1) - schemas.ExecutionTemplate.properties.jobType.type (Total Keys: 1)
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‎docs/dyn/notebooks_v1.projects.locations.executions.html

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@@ -117,7 +117,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},
@@ -224,7 +228,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},
@@ -273,7 +281,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},

‎docs/dyn/notebooks_v1.projects.locations.schedules.html

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@@ -121,7 +121,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},
@@ -144,7 +148,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},
@@ -257,7 +265,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},
@@ -280,7 +292,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},
@@ -336,7 +352,11 @@ <h3>Method Details</h3>
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},
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&quot;type&quot;: &quot;A String&quot;, # Type of this accelerator.
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},
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&quot;containerImageUri&quot;: &quot;A String&quot;, # Container Image URI to a DLVM Example: &#x27;gcr.io/deeplearning-platform-release/base-cu100&#x27; More examples can be found at: https://cloud.google.com/ai-platform/deep-learning-containers/docs/choosing-container
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&quot;dataprocParameters&quot;: { # Parameters used in Dataproc JobType executions. # Parameters used in Dataproc JobType executions.
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&quot;cluster&quot;: &quot;A String&quot;, # URI for cluster used to run Dataproc execution. Format: &#x27;projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}
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},
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&quot;inputNotebookFile&quot;: &quot;A String&quot;, # 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
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&quot;jobType&quot;: &quot;A String&quot;, # The type of Job to be used on this execution.
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&quot;labels&quot;: { # Labels for execution. If execution is scheduled, a field included will be &#x27;nbs-scheduled&#x27;. Otherwise, it is an immediate execution, and an included field will be &#x27;nbs-immediate&#x27;. Use fields to efficiently index between various types of executions.
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&quot;a_key&quot;: &quot;A String&quot;,
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},

‎googleapiclient/discovery_cache/documents/notebooks.v1.json

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}
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}
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},
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"revision": "20210729",
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"revision": "20210808",
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"rootUrl": "https://notebooks.googleapis.com/",
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"schemas": {
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"AcceleratorConfig": {
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},
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"type": "object"
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},
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"DataprocParameters": {
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"description": "Parameters used in Dataproc JobType executions.",
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"id": "DataprocParameters",
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"properties": {
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"cluster": {
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"description": "URI for cluster used to run Dataproc execution. Format: 'projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}",
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"type": "string"
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}
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},
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"type": "object"
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},
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"Disk": {
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"description": "An instance-attached disk resource.",
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"id": "Disk",
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"description": "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",
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"type": "string"
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},
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"dataprocParameters": {
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"$ref": "DataprocParameters",
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"description": "Parameters used in Dataproc JobType executions."
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},
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"inputNotebookFile": {
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"description": "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",
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"type": "string"
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},
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"jobType": {
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"description": "The type of Job to be used on this execution.",
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"enum": [
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"JOB_TYPE_UNSPECIFIED",
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"VERTEX_AI",
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"DATAPROC"
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],
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"enumDescriptions": [
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"No type specified.",
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"Custom Job in `aiplatform.googleapis.com`. Default value for an execution.",
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"Run execution on a cluster with Dataproc as a job. https://cloud.google.com/dataproc/docs/reference/rest/v1/projects.regions.jobs"
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],
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"type": "string"
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},
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"labels": {
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"additionalProperties": {
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"type": "string"

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