chore: Update discovery artifacts (#1195)
* chore(accesscontextmanager): update the api
* chore(adexchangebuyer2): update the api
* chore(admin): update the api
* chore(alertcenter): update the api
* chore(analyticsadmin): update the api
* chore(analyticsdata): update the api
* chore(androidmanagement): update the api
* chore(apigateway): update the api
* chore(apigee): update the api
* chore(appengine): update the api
* chore(area120tables): update the api
* chore(artifactregistry): update the api
* chore(bigquery): update the api
* chore(bigqueryconnection): update the api
* chore(bigqueryreservation): update the api
* chore(billingbudgets): update the api
* chore(binaryauthorization): update the api
* chore(blogger): update the api
* chore(calendar): update the api
* chore(chat): update the api
* chore(cloudasset): update the api
* chore(cloudbuild): update the api
* chore(cloudfunctions): update the api
* chore(cloudidentity): update the api
* chore(cloudkms): update the api
* chore(cloudresourcemanager): update the api
* chore(cloudscheduler): update the api
* chore(cloudtasks): update the api
* chore(composer): update the api
* chore(compute): update the api
* chore(container): update the api
* chore(containeranalysis): update the api
* chore(content): update the api
* chore(datacatalog): update the api
* chore(dataflow): update the api
* chore(datafusion): update the api
* chore(datamigration): update the api
* chore(dataproc): update the api
* chore(deploymentmanager): update the api
* chore(dialogflow): update the api
* chore(displayvideo): update the api
* chore(dlp): update the api
* chore(dns): update the api
* chore(documentai): update the api
* chore(eventarc): update the api
* chore(file): update the api
* chore(firebaseml): update the api
* chore(games): update the api
* chore(gameservices): update the api
* chore(genomics): update the api
* chore(healthcare): update the api
* chore(homegraph): update the api
* chore(iam): update the api
* chore(iap): update the api
* chore(jobs): update the api
* chore(lifesciences): update the api
* chore(localservices): update the api
* chore(managedidentities): update the api
* chore(manufacturers): update the api
* chore(memcache): update the api
* chore(ml): update the api
* chore(monitoring): update the api
* chore(notebooks): update the api
* chore(osconfig): update the api
* chore(pagespeedonline): update the api
* chore(people): update the api
* chore(privateca): update the api
* chore(prod_tt_sasportal): update the api
* chore(pubsub): update the api
* chore(pubsublite): update the api
* chore(recommender): update the api
* chore(remotebuildexecution): update the api
* chore(reseller): update the api
* chore(run): update the api
* chore(safebrowsing): update the api
* chore(sasportal): update the api
* chore(searchconsole): update the api
* chore(secretmanager): update the api
* chore(securitycenter): update the api
* chore(serviceconsumermanagement): update the api
* chore(servicecontrol): update the api
* chore(servicenetworking): update the api
* chore(serviceusage): update the api
* chore(sheets): update the api
* chore(slides): update the api
* chore(spanner): update the api
* chore(speech): update the api
* chore(sqladmin): update the api
* chore(storage): update the api
* chore(storagetransfer): update the api
* chore(sts): update the api
* chore(tagmanager): update the api
* chore(testing): update the api
* chore(toolresults): update the api
* chore(transcoder): update the api
* chore(vectortile): update the api
* chore(videointelligence): update the api
* chore(vision): update the api
* chore(webmasters): update the api
* chore(workflowexecutions): update the api
* chore(youtube): update the api
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+
+<h1><a href="notebooks_v1.html">Notebooks API</a> . <a href="notebooks_v1.projects.html">projects</a> . <a href="notebooks_v1.projects.locations.html">locations</a> . <a href="notebooks_v1.projects.locations.executions.html">executions</a></h1>
+<h2>Instance Methods</h2>
+<p class="toc_element">
+ <code><a href="#close">close()</a></code></p>
+<p class="firstline">Close httplib2 connections.</p>
+<p class="toc_element">
+ <code><a href="#create">create(parent, body=None, executionId=None, x__xgafv=None)</a></code></p>
+<p class="firstline">Creates a new Scheduled Notebook in a given project and location.</p>
+<p class="toc_element">
+ <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
+<p class="firstline">Deletes execution</p>
+<p class="toc_element">
+ <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
+<p class="firstline">Gets details of executions</p>
+<p class="toc_element">
+ <code><a href="#list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p>
+<p class="firstline">Lists executions in a given project and location</p>
+<p class="toc_element">
+ <code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p>
+<p class="firstline">Retrieves the next page of results.</p>
+<h3>Method Details</h3>
+<div class="method">
+ <code class="details" id="close">close()</code>
+ <pre>Close httplib2 connections.</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="create">create(parent, body=None, executionId=None, x__xgafv=None)</code>
+ <pre>Creates a new Scheduled Notebook in a given project and location.
+
+Args:
+ parent: string, Required. Format: `parent=projects/{project_id}/locations/{location}` (required)
+ body: object, The request body.
+ The object takes the form of:
+
+{ # The definition of a single executed notebook.
+ "createTime": "A String", # Output only. Time the Execution was instantiated.
+ "description": "A String", # A brief description of this execution.
+ "displayName": "A String", # Output only. Name used for UI purposes. Name can only contain alphanumeric characters and underscores '_'.
+ "executionTemplate": { # The description a notebook execution workload. # execute metadata including name, hardware spec, region, labels, etc.
+ "acceleratorConfig": { # 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. # Configuration (count and accelerator type) for hardware running notebook execution.
+ "coreCount": "A String", # Count of cores of this accelerator.
+ "type": "A String", # Type of this accelerator.
+ },
+ "containerImageUri": "A 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
+ "inputNotebookFile": "A String", # 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
+ "labels": { # 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.
+ "a_key": "A String",
+ },
+ "masterType": "A 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.
+ "outputNotebookFolder": "A 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
+ "parameters": "A String", # Parameters used within the 'input_notebook_file' notebook.
+ "paramsYamlFile": "A 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
+ "scaleTier": "A String", # Required. Scale tier of the hardware used for notebook execution.
+ },
+ "name": "A String", # Output only. The resource name of the execute. Format: `projects/{project_id}/locations/{location}/execution/{execution_id}
+ "outputNotebookFile": "A String", # Output notebook file generated by this execution
+ "state": "A String", # Output only. State of the underlying AI Platform job.
+ "updateTime": "A String", # Output only. Time the Execution was last updated.
+}
+
+ executionId: string, Required. User-defined unique ID of this execution.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal response of the operation in case of success. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="delete">delete(name, x__xgafv=None)</code>
+ <pre>Deletes execution
+
+Args:
+ name: string, Required. Format: `projects/{project_id}/locations/{location}/executions/{execution_id}` (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal response of the operation in case of success. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="get">get(name, x__xgafv=None)</code>
+ <pre>Gets details of executions
+
+Args:
+ name: string, Required. Format: `projects/{project_id}/locations/{location}/schedules/{execution_id}` (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # The definition of a single executed notebook.
+ "createTime": "A String", # Output only. Time the Execution was instantiated.
+ "description": "A String", # A brief description of this execution.
+ "displayName": "A String", # Output only. Name used for UI purposes. Name can only contain alphanumeric characters and underscores '_'.
+ "executionTemplate": { # The description a notebook execution workload. # execute metadata including name, hardware spec, region, labels, etc.
+ "acceleratorConfig": { # 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. # Configuration (count and accelerator type) for hardware running notebook execution.
+ "coreCount": "A String", # Count of cores of this accelerator.
+ "type": "A String", # Type of this accelerator.
+ },
+ "containerImageUri": "A 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
+ "inputNotebookFile": "A String", # 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
+ "labels": { # 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.
+ "a_key": "A String",
+ },
+ "masterType": "A 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.
+ "outputNotebookFolder": "A 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
+ "parameters": "A String", # Parameters used within the 'input_notebook_file' notebook.
+ "paramsYamlFile": "A 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
+ "scaleTier": "A String", # Required. Scale tier of the hardware used for notebook execution.
+ },
+ "name": "A String", # Output only. The resource name of the execute. Format: `projects/{project_id}/locations/{location}/execution/{execution_id}
+ "outputNotebookFile": "A String", # Output notebook file generated by this execution
+ "state": "A String", # Output only. State of the underlying AI Platform job.
+ "updateTime": "A String", # Output only. Time the Execution was last updated.
+}</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</code>
+ <pre>Lists executions in a given project and location
+
+Args:
+ parent: string, Required. Format: `parent=projects/{project_id}/locations/{location}` (required)
+ filter: string, Filter applied to resulting executions.
+ orderBy: string, Sort by field.
+ pageSize: integer, Maximum return size of the list call.
+ pageToken: string, A previous returned page token that can be used to continue listing from the last result.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # Response for listing scheduled notebook executions
+ "executions": [ # A list of returned instances.
+ { # The definition of a single executed notebook.
+ "createTime": "A String", # Output only. Time the Execution was instantiated.
+ "description": "A String", # A brief description of this execution.
+ "displayName": "A String", # Output only. Name used for UI purposes. Name can only contain alphanumeric characters and underscores '_'.
+ "executionTemplate": { # The description a notebook execution workload. # execute metadata including name, hardware spec, region, labels, etc.
+ "acceleratorConfig": { # 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. # Configuration (count and accelerator type) for hardware running notebook execution.
+ "coreCount": "A String", # Count of cores of this accelerator.
+ "type": "A String", # Type of this accelerator.
+ },
+ "containerImageUri": "A 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
+ "inputNotebookFile": "A String", # 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
+ "labels": { # 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.
+ "a_key": "A String",
+ },
+ "masterType": "A 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.
+ "outputNotebookFolder": "A 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
+ "parameters": "A String", # Parameters used within the 'input_notebook_file' notebook.
+ "paramsYamlFile": "A 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
+ "scaleTier": "A String", # Required. Scale tier of the hardware used for notebook execution.
+ },
+ "name": "A String", # Output only. The resource name of the execute. Format: `projects/{project_id}/locations/{location}/execution/{execution_id}
+ "outputNotebookFile": "A String", # Output notebook file generated by this execution
+ "state": "A String", # Output only. State of the underlying AI Platform job.
+ "updateTime": "A String", # Output only. Time the Execution was last updated.
+ },
+ ],
+ "nextPageToken": "A String", # Page token that can be used to continue listing from the last result in the next list call.
+ "unreachable": [ # Executions IDs that could not be reached. For example, ['projects/{project_id}/location/{location}/executions/imagenet_test1', 'projects/{project_id}/location/{location}/executions/classifier_train1'].
+ "A String",
+ ],
+}</pre>
+</div>
+
+<div class="method">
+ <code class="details" id="list_next">list_next(previous_request, previous_response)</code>
+ <pre>Retrieves the next page of results.
+
+Args:
+ previous_request: The request for the previous page. (required)
+ previous_response: The response from the request for the previous page. (required)
+
+Returns:
+ A request object that you can call 'execute()' on to request the next
+ page. Returns None if there are no more items in the collection.
+ </pre>
+</div>
+
+</body></html>
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