grpc1.45.2/third_party/googleapis/google/cloud/aiplatform/v1beta1/custom_job.proto

// Copyright 2021 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.aiplatform.v1beta1;

import "google/api/field_behavior.proto";
import "google/api/resource.proto";
import "google/cloud/aiplatform/v1beta1/encryption_spec.proto";
import "google/cloud/aiplatform/v1beta1/env_var.proto";
import "google/cloud/aiplatform/v1beta1/io.proto";
import "google/cloud/aiplatform/v1beta1/job_state.proto";
import "google/cloud/aiplatform/v1beta1/machine_resources.proto";
import "google/protobuf/duration.proto";
import "google/protobuf/timestamp.proto";
import "google/rpc/status.proto";
import "google/api/annotations.proto";

option csharp_namespace = "Google.Cloud.AIPlatform.V1Beta1";
option go_package = "google.golang.org/genproto/googleapis/cloud/aiplatform/v1beta1;aiplatform";
option java_multiple_files = true;
option java_outer_classname = "CustomJobProto";
option java_package = "com.google.cloud.aiplatform.v1beta1";
option php_namespace = "Google\\Cloud\\AIPlatform\\V1beta1";
option ruby_package = "Google::Cloud::AIPlatform::V1beta1";

// Represents a job that runs custom workloads such as a Docker container or a
// Python package. A CustomJob can have multiple worker pools and each worker
// pool can have its own machine and input spec. A CustomJob will be cleaned up
// once the job enters terminal state (failed or succeeded).
message CustomJob {
  option (google.api.resource) = {
    type: "aiplatform.googleapis.com/CustomJob"
    pattern: "projects/{project}/locations/{location}/customJobs/{custom_job}"
  };

  // Output only. Resource name of a CustomJob.
  string name = 1 [(google.api.field_behavior) = OUTPUT_ONLY];

  // Required. The display name of the CustomJob.
  // The name can be up to 128 characters long and can be consist of any UTF-8
  // characters.
  string display_name = 2 [(google.api.field_behavior) = REQUIRED];

  // Required. Job spec.
  CustomJobSpec job_spec = 4 [(google.api.field_behavior) = REQUIRED];

  // Output only. The detailed state of the job.
  JobState state = 5 [(google.api.field_behavior) = OUTPUT_ONLY];

  // Output only. Time when the CustomJob was created.
  google.protobuf.Timestamp create_time = 6 [(google.api.field_behavior) = OUTPUT_ONLY];

  // Output only. Time when the CustomJob for the first time entered the
  // `JOB_STATE_RUNNING` state.
  google.protobuf.Timestamp start_time = 7 [(google.api.field_behavior) = OUTPUT_ONLY];

  // Output only. Time when the CustomJob entered any of the following states:
  // `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
  google.protobuf.Timestamp end_time = 8 [(google.api.field_behavior) = OUTPUT_ONLY];

  // Output only. Time when the CustomJob was most recently updated.
  google.protobuf.Timestamp update_time = 9 [(google.api.field_behavior) = OUTPUT_ONLY];

  // Output only. Only populated when job's state is `JOB_STATE_FAILED` or
  // `JOB_STATE_CANCELLED`.
  google.rpc.Status error = 10 [(google.api.field_behavior) = OUTPUT_ONLY];

  // The labels with user-defined metadata to organize CustomJobs.
  //
  // Label keys and values can be no longer than 64 characters
  // (Unicode codepoints), can only contain lowercase letters, numeric
  // characters, underscores and dashes. International characters are allowed.
  //
  // See https://goo.gl/xmQnxf for more information and examples of labels.
  map<string, string> labels = 11;

  // Customer-managed encryption key options for a CustomJob. If this is set,
  // then all resources created by the CustomJob will be encrypted with the
  // provided encryption key.
  EncryptionSpec encryption_spec = 12;

  // Output only. The web access URIs for the training job.
  // The keys are the node names in the training jobs, e.g. workerpool0-0.
  // The values are the URIs for each node's web portal in the job.
  map<string, string> web_access_uris = 16 [(google.api.field_behavior) = OUTPUT_ONLY];
}

// Represents the spec of a CustomJob.
message CustomJobSpec {
  // Required. The spec of the worker pools including machine type and Docker image.
  // All worker pools except the first one are optional and can be skipped by
  // providing an empty value.
  repeated WorkerPoolSpec worker_pool_specs = 1 [(google.api.field_behavior) = REQUIRED];

  // Scheduling options for a CustomJob.
  Scheduling scheduling = 3;

  // Specifies the service account for workload run-as account.
  // Users submitting jobs must have act-as permission on this run-as account.
  // If unspecified, the [AI Platform Custom Code Service
  // Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)
  // for the CustomJob's project is used.
  string service_account = 4;

  // 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](/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 = 5 [(google.api.resource_reference) = {
                        type: "compute.googleapis.com/Network"
                      }];

  // The Cloud Storage location to store the output of this CustomJob or
  // HyperparameterTuningJob. For HyperparameterTuningJob,
  // the baseOutputDirectory of
  // each child CustomJob backing a Trial is set to a subdirectory of name
  // [id][google.cloud.aiplatform.v1beta1.Trial.id] under its parent HyperparameterTuningJob's
  // baseOutputDirectory.
  //
  // The following Vertex AI environment variables will be passed to
  // containers or python modules when this field is set:
  //
  //   For CustomJob:
  //
  //   * AIP_MODEL_DIR = `<base_output_directory>/model/`
  //   * AIP_CHECKPOINT_DIR = `<base_output_directory>/checkpoints/`
  //   * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/logs/`
  //
  //   For CustomJob backing a Trial of HyperparameterTuningJob:
  //
  //   * AIP_MODEL_DIR = `<base_output_directory>/<trial_id>/model/`
  //   * AIP_CHECKPOINT_DIR = `<base_output_directory>/<trial_id>/checkpoints/`
  //   * AIP_TENSORBOARD_LOG_DIR = `<base_output_directory>/<trial_id>/logs/`
  GcsDestination base_output_directory = 6;

  // Optional. The name of a Vertex AI [Tensorboard][google.cloud.aiplatform.v1beta1.Tensorboard] resource to which this CustomJob
  // will upload Tensorboard logs.
  // Format:
  // `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
  string tensorboard = 7 [
    (google.api.field_behavior) = OPTIONAL,
    (google.api.resource_reference) = {
      type: "aiplatform.googleapis.com/Tensorboard"
    }
  ];

  // Optional. Vertex AI will enable web portal access to the containers. The portals
  // can be accessed on web via the URLs given by [web_access_uris][].
  bool enable_web_access = 10 [(google.api.field_behavior) = OPTIONAL];
}

// Represents the spec of a worker pool in a job.
message WorkerPoolSpec {
  // The custom task to be executed in this worker pool.
  oneof task {
    // The custom container task.
    ContainerSpec container_spec = 6;

    // The Python packaged task.
    PythonPackageSpec python_package_spec = 7;
  }

  // Optional. Immutable. The specification of a single machine.
  MachineSpec machine_spec = 1 [
    (google.api.field_behavior) = OPTIONAL,
    (google.api.field_behavior) = IMMUTABLE
  ];

  // Optional. The number of worker replicas to use for this worker pool.
  int64 replica_count = 2 [(google.api.field_behavior) = OPTIONAL];

  // Disk spec.
  DiskSpec disk_spec = 5;
}

// The spec of a Container.
message ContainerSpec {
  // Required. The URI of a container image in the Container Registry that is to be run on
  // each worker replica.
  string image_uri = 1 [(google.api.field_behavior) = REQUIRED];

  // The command to be invoked when the container is started.
  // It overrides the entrypoint instruction in Dockerfile when provided.
  repeated string command = 2;

  // The arguments to be passed when starting the container.
  repeated string args = 3;
}

// The spec of a Python packaged code.
message PythonPackageSpec {
  // Required. The URI of a container image in Artifact Registry that will run the
  // provided Python package. Vertex AI provides a wide range of executor
  // images with pre-installed packages to meet users' various use cases. See
  // the list of [pre-built containers for
  // training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers).
  // You must use an image from this list.
  string executor_image_uri = 1 [(google.api.field_behavior) = REQUIRED];

  // Required. The Google Cloud Storage location of the Python package files which are
  // the training program and its dependent packages.
  // The maximum number of package URIs is 100.
  repeated string package_uris = 2 [(google.api.field_behavior) = REQUIRED];

  // Required. The Python module name to run after installing the packages.
  string python_module = 3 [(google.api.field_behavior) = REQUIRED];

  // Command line arguments to be passed to the Python task.
  repeated string args = 4;
}

// All parameters related to queuing and scheduling of custom jobs.
message Scheduling {
  // The maximum job running time. The default is 7 days.
  google.protobuf.Duration timeout = 1;

  // Restarts the entire CustomJob if a worker gets restarted.
  // This feature can be used by distributed training jobs that are not
  // resilient to workers leaving and joining a job.
  bool restart_job_on_worker_restart = 3;
}