| yoshi-code-bot | b6dc1b9 | 2021-03-02 11:49:08 -0800 | [diff] [blame] | 1 | <html><body> |
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| 74 | |
| 75 | <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> |
| 76 | <h2>Instance Methods</h2> |
| 77 | <p class="toc_element"> |
| 78 | <code><a href="#close">close()</a></code></p> |
| 79 | <p class="firstline">Close httplib2 connections.</p> |
| 80 | <p class="toc_element"> |
| 81 | <code><a href="#create">create(parent, body=None, executionId=None, x__xgafv=None)</a></code></p> |
| 82 | <p class="firstline">Creates a new Scheduled Notebook in a given project and location.</p> |
| 83 | <p class="toc_element"> |
| 84 | <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p> |
| 85 | <p class="firstline">Deletes execution</p> |
| 86 | <p class="toc_element"> |
| 87 | <code><a href="#get">get(name, x__xgafv=None)</a></code></p> |
| 88 | <p class="firstline">Gets details of executions</p> |
| 89 | <p class="toc_element"> |
| 90 | <code><a href="#list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p> |
| 91 | <p class="firstline">Lists executions in a given project and location</p> |
| 92 | <p class="toc_element"> |
| 93 | <code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p> |
| 94 | <p class="firstline">Retrieves the next page of results.</p> |
| 95 | <h3>Method Details</h3> |
| 96 | <div class="method"> |
| 97 | <code class="details" id="close">close()</code> |
| 98 | <pre>Close httplib2 connections.</pre> |
| 99 | </div> |
| 100 | |
| 101 | <div class="method"> |
| 102 | <code class="details" id="create">create(parent, body=None, executionId=None, x__xgafv=None)</code> |
| 103 | <pre>Creates a new Scheduled Notebook in a given project and location. |
| 104 | |
| 105 | Args: |
| 106 | parent: string, Required. Format: `parent=projects/{project_id}/locations/{location}` (required) |
| 107 | body: object, The request body. |
| 108 | The object takes the form of: |
| 109 | |
| 110 | { # The definition of a single executed notebook. |
| 111 | "createTime": "A String", # Output only. Time the Execution was instantiated. |
| 112 | "description": "A String", # A brief description of this execution. |
| 113 | "displayName": "A String", # Output only. Name used for UI purposes. Name can only contain alphanumeric characters and underscores '_'. |
| 114 | "executionTemplate": { # The description a notebook execution workload. # execute metadata including name, hardware spec, region, labels, etc. |
| 115 | "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. |
| 116 | "coreCount": "A String", # Count of cores of this accelerator. |
| 117 | "type": "A String", # Type of this accelerator. |
| 118 | }, |
| 119 | "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 |
| 120 | "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 |
| 121 | "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. |
| 122 | "a_key": "A String", |
| 123 | }, |
| 124 | "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. |
| 125 | "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 |
| 126 | "parameters": "A String", # Parameters used within the 'input_notebook_file' notebook. |
| 127 | "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 |
| 128 | "scaleTier": "A String", # Required. Scale tier of the hardware used for notebook execution. |
| 129 | }, |
| 130 | "name": "A String", # Output only. The resource name of the execute. Format: `projects/{project_id}/locations/{location}/execution/{execution_id} |
| 131 | "outputNotebookFile": "A String", # Output notebook file generated by this execution |
| 132 | "state": "A String", # Output only. State of the underlying AI Platform job. |
| 133 | "updateTime": "A String", # Output only. Time the Execution was last updated. |
| 134 | } |
| 135 | |
| 136 | executionId: string, Required. User-defined unique ID of this execution. |
| 137 | x__xgafv: string, V1 error format. |
| 138 | Allowed values |
| 139 | 1 - v1 error format |
| 140 | 2 - v2 error format |
| 141 | |
| 142 | Returns: |
| 143 | An object of the form: |
| 144 | |
| 145 | { # This resource represents a long-running operation that is the result of a network API call. |
| 146 | "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. |
| 147 | "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. |
| 148 | "code": 42, # The status code, which should be an enum value of google.rpc.Code. |
| 149 | "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use. |
| 150 | { |
| 151 | "a_key": "", # Properties of the object. Contains field @type with type URL. |
| 152 | }, |
| 153 | ], |
| 154 | "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. |
| 155 | }, |
| 156 | "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. |
| 157 | "a_key": "", # Properties of the object. Contains field @type with type URL. |
| 158 | }, |
| 159 | "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}`. |
| 160 | "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`. |
| 161 | "a_key": "", # Properties of the object. Contains field @type with type URL. |
| 162 | }, |
| 163 | }</pre> |
| 164 | </div> |
| 165 | |
| 166 | <div class="method"> |
| 167 | <code class="details" id="delete">delete(name, x__xgafv=None)</code> |
| 168 | <pre>Deletes execution |
| 169 | |
| 170 | Args: |
| 171 | name: string, Required. Format: `projects/{project_id}/locations/{location}/executions/{execution_id}` (required) |
| 172 | x__xgafv: string, V1 error format. |
| 173 | Allowed values |
| 174 | 1 - v1 error format |
| 175 | 2 - v2 error format |
| 176 | |
| 177 | Returns: |
| 178 | An object of the form: |
| 179 | |
| 180 | { # This resource represents a long-running operation that is the result of a network API call. |
| 181 | "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. |
| 182 | "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. |
| 183 | "code": 42, # The status code, which should be an enum value of google.rpc.Code. |
| 184 | "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use. |
| 185 | { |
| 186 | "a_key": "", # Properties of the object. Contains field @type with type URL. |
| 187 | }, |
| 188 | ], |
| 189 | "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. |
| 190 | }, |
| 191 | "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. |
| 192 | "a_key": "", # Properties of the object. Contains field @type with type URL. |
| 193 | }, |
| 194 | "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}`. |
| 195 | "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`. |
| 196 | "a_key": "", # Properties of the object. Contains field @type with type URL. |
| 197 | }, |
| 198 | }</pre> |
| 199 | </div> |
| 200 | |
| 201 | <div class="method"> |
| 202 | <code class="details" id="get">get(name, x__xgafv=None)</code> |
| 203 | <pre>Gets details of executions |
| 204 | |
| 205 | Args: |
| 206 | name: string, Required. Format: `projects/{project_id}/locations/{location}/schedules/{execution_id}` (required) |
| 207 | x__xgafv: string, V1 error format. |
| 208 | Allowed values |
| 209 | 1 - v1 error format |
| 210 | 2 - v2 error format |
| 211 | |
| 212 | Returns: |
| 213 | An object of the form: |
| 214 | |
| 215 | { # The definition of a single executed notebook. |
| 216 | "createTime": "A String", # Output only. Time the Execution was instantiated. |
| 217 | "description": "A String", # A brief description of this execution. |
| 218 | "displayName": "A String", # Output only. Name used for UI purposes. Name can only contain alphanumeric characters and underscores '_'. |
| 219 | "executionTemplate": { # The description a notebook execution workload. # execute metadata including name, hardware spec, region, labels, etc. |
| 220 | "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. |
| 221 | "coreCount": "A String", # Count of cores of this accelerator. |
| 222 | "type": "A String", # Type of this accelerator. |
| 223 | }, |
| 224 | "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 |
| 225 | "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 |
| 226 | "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. |
| 227 | "a_key": "A String", |
| 228 | }, |
| 229 | "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. |
| 230 | "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 |
| 231 | "parameters": "A String", # Parameters used within the 'input_notebook_file' notebook. |
| 232 | "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 |
| 233 | "scaleTier": "A String", # Required. Scale tier of the hardware used for notebook execution. |
| 234 | }, |
| 235 | "name": "A String", # Output only. The resource name of the execute. Format: `projects/{project_id}/locations/{location}/execution/{execution_id} |
| 236 | "outputNotebookFile": "A String", # Output notebook file generated by this execution |
| 237 | "state": "A String", # Output only. State of the underlying AI Platform job. |
| 238 | "updateTime": "A String", # Output only. Time the Execution was last updated. |
| 239 | }</pre> |
| 240 | </div> |
| 241 | |
| 242 | <div class="method"> |
| 243 | <code class="details" id="list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</code> |
| 244 | <pre>Lists executions in a given project and location |
| 245 | |
| 246 | Args: |
| 247 | parent: string, Required. Format: `parent=projects/{project_id}/locations/{location}` (required) |
| 248 | filter: string, Filter applied to resulting executions. |
| 249 | orderBy: string, Sort by field. |
| 250 | pageSize: integer, Maximum return size of the list call. |
| 251 | pageToken: string, A previous returned page token that can be used to continue listing from the last result. |
| 252 | x__xgafv: string, V1 error format. |
| 253 | Allowed values |
| 254 | 1 - v1 error format |
| 255 | 2 - v2 error format |
| 256 | |
| 257 | Returns: |
| 258 | An object of the form: |
| 259 | |
| 260 | { # Response for listing scheduled notebook executions |
| 261 | "executions": [ # A list of returned instances. |
| 262 | { # The definition of a single executed notebook. |
| 263 | "createTime": "A String", # Output only. Time the Execution was instantiated. |
| 264 | "description": "A String", # A brief description of this execution. |
| 265 | "displayName": "A String", # Output only. Name used for UI purposes. Name can only contain alphanumeric characters and underscores '_'. |
| 266 | "executionTemplate": { # The description a notebook execution workload. # execute metadata including name, hardware spec, region, labels, etc. |
| 267 | "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. |
| 268 | "coreCount": "A String", # Count of cores of this accelerator. |
| 269 | "type": "A String", # Type of this accelerator. |
| 270 | }, |
| 271 | "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 |
| 272 | "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 |
| 273 | "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. |
| 274 | "a_key": "A String", |
| 275 | }, |
| 276 | "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. |
| 277 | "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 |
| 278 | "parameters": "A String", # Parameters used within the 'input_notebook_file' notebook. |
| 279 | "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 |
| 280 | "scaleTier": "A String", # Required. Scale tier of the hardware used for notebook execution. |
| 281 | }, |
| 282 | "name": "A String", # Output only. The resource name of the execute. Format: `projects/{project_id}/locations/{location}/execution/{execution_id} |
| 283 | "outputNotebookFile": "A String", # Output notebook file generated by this execution |
| 284 | "state": "A String", # Output only. State of the underlying AI Platform job. |
| 285 | "updateTime": "A String", # Output only. Time the Execution was last updated. |
| 286 | }, |
| 287 | ], |
| 288 | "nextPageToken": "A String", # Page token that can be used to continue listing from the last result in the next list call. |
| 289 | "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']. |
| 290 | "A String", |
| 291 | ], |
| 292 | }</pre> |
| 293 | </div> |
| 294 | |
| 295 | <div class="method"> |
| 296 | <code class="details" id="list_next">list_next(previous_request, previous_response)</code> |
| 297 | <pre>Retrieves the next page of results. |
| 298 | |
| 299 | Args: |
| 300 | previous_request: The request for the previous page. (required) |
| 301 | previous_response: The response from the request for the previous page. (required) |
| 302 | |
| 303 | Returns: |
| 304 | A request object that you can call 'execute()' on to request the next |
| 305 | page. Returns None if there are no more items in the collection. |
| 306 | </pre> |
| 307 | </div> |
| 308 | |
| 309 | </body></html> |