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Diffstat (limited to 'third_party/googleapis/google/cloud/notebooks/v1/execution.proto')
| -rw-r--r-- | third_party/googleapis/google/cloud/notebooks/v1/execution.proto | 349 |
1 files changed, 0 insertions, 349 deletions
diff --git a/third_party/googleapis/google/cloud/notebooks/v1/execution.proto b/third_party/googleapis/google/cloud/notebooks/v1/execution.proto deleted file mode 100644 index 03940f3..0000000 --- a/third_party/googleapis/google/cloud/notebooks/v1/execution.proto +++ /dev/null @@ -1,349 +0,0 @@ -// Copyright 2022 Google LLC -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -syntax = "proto3"; - -package google.cloud.notebooks.v1; - -import "google/api/field_behavior.proto"; -import "google/api/resource.proto"; -import "google/protobuf/timestamp.proto"; - -option go_package = "google.golang.org/genproto/googleapis/cloud/notebooks/v1;notebooks"; -option java_multiple_files = true; -option java_outer_classname = "ExecutionProto"; -option java_package = "com.google.cloud.notebooks.v1"; -option (google.api.resource_definition) = { - type: "aiplatform.googleapis.com/Tensorboard" - pattern: "projects/{project}/locations/{location}/tensorboards/{tensorboard}" -}; - -// The description a notebook execution workload. -message ExecutionTemplate { - // Required. Specifies the machine types, the number of replicas for workers - // and parameter servers. - enum ScaleTier { - // Unspecified Scale Tier. - SCALE_TIER_UNSPECIFIED = 0; - - // A single worker instance. This tier is suitable for learning how to use - // Cloud ML, and for experimenting with new models using small datasets. - BASIC = 1; - - // Many workers and a few parameter servers. - STANDARD_1 = 2; - - // A large number of workers with many parameter servers. - PREMIUM_1 = 3; - - // A single worker instance with a K80 GPU. - BASIC_GPU = 4; - - // A single worker instance with a Cloud TPU. - BASIC_TPU = 5; - - // The CUSTOM tier is not a set tier, but rather enables you to use your - // own cluster specification. When you use this tier, set values to - // configure your processing cluster according to these guidelines: - // - // * You _must_ set `ExecutionTemplate.masterType` to specify the type - // of machine to use for your master node. This is the only required - // setting. - CUSTOM = 6; - } - - // Hardware accelerator types for AI Platform Training jobs. - enum SchedulerAcceleratorType { - // Unspecified accelerator type. Default to no GPU. - SCHEDULER_ACCELERATOR_TYPE_UNSPECIFIED = 0; - - // Nvidia Tesla K80 GPU. - NVIDIA_TESLA_K80 = 1; - - // Nvidia Tesla P100 GPU. - NVIDIA_TESLA_P100 = 2; - - // Nvidia Tesla V100 GPU. - NVIDIA_TESLA_V100 = 3; - - // Nvidia Tesla P4 GPU. - NVIDIA_TESLA_P4 = 4; - - // Nvidia Tesla T4 GPU. - NVIDIA_TESLA_T4 = 5; - - // Nvidia Tesla A100 GPU. - NVIDIA_TESLA_A100 = 10; - - // TPU v2. - TPU_V2 = 6; - - // TPU v3. - TPU_V3 = 7; - } - - // Definition of a hardware accelerator. Note that not all combinations - // of `type` and `core_count` are valid. Check [GPUs on - // Compute Engine](https://cloud.google.com/compute/docs/gpus) to find a valid - // combination. TPUs are not supported. - message SchedulerAcceleratorConfig { - // Type of this accelerator. - SchedulerAcceleratorType type = 1; - - // Count of cores of this accelerator. - int64 core_count = 2; - } - - // The backend used for this execution. - enum JobType { - // No type specified. - JOB_TYPE_UNSPECIFIED = 0; - - // Custom Job in `aiplatform.googleapis.com`. - // Default value for an execution. - VERTEX_AI = 1; - - // Run execution on a cluster with Dataproc as a job. - // https://cloud.google.com/dataproc/docs/reference/rest/v1/projects.regions.jobs - DATAPROC = 2; - } - - // Parameters used in Dataproc JobType executions. - message DataprocParameters { - // URI for cluster used to run Dataproc execution. - // Format: `projects/{PROJECT_ID}/regions/{REGION}/clusters/{CLUSTER_NAME}` - string cluster = 1; - } - - // Parameters used in Vertex AI JobType executions. - message VertexAIParameters { - // The full name of the Compute Engine - // [network](/compute/docs/networks-and-firewalls#networks) to which the Job - // should be peered. For example, `projects/12345/global/networks/myVPC`. - // [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert) - // is of the form `projects/{project}/global/networks/{network}`. - // Where {project} is a project number, as in `12345`, and {network} is a - // network name. - // - // Private services access must already be configured for the network. If - // left unspecified, the job is not peered with any network. - string network = 1; - - // Environment variables. - // At most 100 environment variables can be specified and unique. - // Example: GCP_BUCKET=gs://my-bucket/samples/ - map<string, string> env = 2; - } - - // Required. Scale tier of the hardware used for notebook execution. - // DEPRECATED Will be discontinued. As right now only CUSTOM is supported. - ScaleTier scale_tier = 1 [ - deprecated = true, - (google.api.field_behavior) = REQUIRED - ]; - - // 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](https://cloud.google.com/ai-platform/training/docs/using-tpus#configuring_a_custom_tpu_machine). - string master_type = 2; - - // Configuration (count and accelerator type) for hardware running notebook - // execution. - SchedulerAcceleratorConfig accelerator_config = 3; - - // 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. - map<string, string> labels = 4; - - // 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` - string input_notebook_file = 5; - - // 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 - string container_image_uri = 6; - - // 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` - string output_notebook_folder = 7; - - // 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` - string params_yaml_file = 8; - - // Parameters used within the 'input_notebook_file' notebook. - string parameters = 9; - - // 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. - string service_account = 10; - - // The type of Job to be used on this execution. - JobType job_type = 11; - - // Parameters for an execution type. - // NOTE: There are currently no extra parameters for VertexAI jobs. - oneof job_parameters { - // Parameters used in Dataproc JobType executions. - DataprocParameters dataproc_parameters = 12; - - // Parameters used in Vertex AI JobType executions. - VertexAIParameters vertex_ai_parameters = 13; - } - - // 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. - string kernel_spec = 14; - - // The name of a Vertex AI [Tensorboard] resource to which this execution - // will upload Tensorboard logs. - // Format: - // `projects/{project}/locations/{location}/tensorboards/{tensorboard}` - string tensorboard = 15 [(google.api.resource_reference) = { - type: "aiplatform.googleapis.com/Tensorboard" - }]; -} - -// The definition of a single executed notebook. -message Execution { - option (google.api.resource) = { - type: "notebooks.googleapis.com/Execution" - pattern: "projects/{project}/location/{location}/executions/{execution}" - }; - - // Enum description of the state of the underlying AIP job. - enum State { - // The job state is unspecified. - STATE_UNSPECIFIED = 0; - - // The job has been just created and processing has not yet begun. - QUEUED = 1; - - // The service is preparing to execution the job. - PREPARING = 2; - - // The job is in progress. - RUNNING = 3; - - // The job completed successfully. - SUCCEEDED = 4; - - // The job failed. - // `error_message` should contain the details of the failure. - FAILED = 5; - - // The job is being cancelled. - // `error_message` should describe the reason for the cancellation. - CANCELLING = 6; - - // The job has been cancelled. - // `error_message` should describe the reason for the cancellation. - CANCELLED = 7; - - // The job has become expired (relevant to Vertex AI jobs) - // https://cloud.google.com/vertex-ai/docs/reference/rest/v1/JobState - EXPIRED = 9; - - // The Execution is being created. - INITIALIZING = 10; - } - - // execute metadata including name, hardware spec, region, labels, etc. - ExecutionTemplate execution_template = 1; - - // Output only. The resource name of the execute. Format: - // `projects/{project_id}/locations/{location}/executions/{execution_id}` - string name = 2 [(google.api.field_behavior) = OUTPUT_ONLY]; - - // Output only. Name used for UI purposes. - // Name can only contain alphanumeric characters and underscores '_'. - string display_name = 3 [(google.api.field_behavior) = OUTPUT_ONLY]; - - // A brief description of this execution. - string description = 4; - - // Output only. Time the Execution was instantiated. - google.protobuf.Timestamp create_time = 5 [(google.api.field_behavior) = OUTPUT_ONLY]; - - // Output only. Time the Execution was last updated. - google.protobuf.Timestamp update_time = 6 [(google.api.field_behavior) = OUTPUT_ONLY]; - - // Output only. State of the underlying AI Platform job. - State state = 7 [(google.api.field_behavior) = OUTPUT_ONLY]; - - // Output notebook file generated by this execution - string output_notebook_file = 8; - - // Output only. The URI of the external job used to execute the notebook. - string job_uri = 9 [(google.api.field_behavior) = OUTPUT_ONLY]; -} |