Amazon Neptune · Schema

CreateModelTrainingJobRequest

CreateModelTrainingJobRequest schema from Neptune

DatabaseGraph DatabaseGremlinNeptuneProperty GraphRDFSPARQL

Properties

Name Type Description
id string Unique identifier for the job.
dataProcessingJobId string Job ID of the completed data processing job.
trainModelS3Location string S3 location for model artifacts output.
previousModelTrainingJobId string Job ID of a previous training job for incremental training.
sagemakerIamRoleArn string
neptuneIamRoleArn string
modelName string The model type to train: rgcn (relational graph convolutional network), transe, distmult, rotate, or custom.
baseProcessingInstanceType string ML instance type for data preparation step.
trainingInstanceType string ML instance type for the training step.
trainingInstanceVolumeSizeInGB integer Disk volume size for training instance in GB.
trainingTimeOutInSeconds integer Training job timeout in seconds.
maxHPONumberOfTrainingJobs integer Maximum total training jobs for hyperparameter tuning. Minimum 10 recommended for meaningful results.
maxHPOParallelTrainingJobs integer Maximum parallel training jobs.
subnets array
securityGroupIds array
volumeEncryptionKMSKey string
s3OutputEncryptionKMSKey string
enableInterContainerTrafficEncryption boolean
enableManagedSpotTraining boolean Whether to use EC2 spot instances for training.
customModelTrainingParameters object Custom model training configuration.
View JSON Schema on GitHub

JSON Schema

ml-create-model-training-job-request-schema.json Raw ↑ 
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://raw.githubusercontent.com/api-evangelist/amazon-neptune/refs/heads/main/json-schema/ml-create-model-training-job-request-schema.json",
  "title": "CreateModelTrainingJobRequest",
  "description": "CreateModelTrainingJobRequest schema from Neptune",
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Unique identifier for the job."
    },
    "dataProcessingJobId": {
      "type": "string",
      "description": "Job ID of the completed data processing job."
    },
    "trainModelS3Location": {
      "type": "string",
      "description": "S3 location for model artifacts output."
    },
    "previousModelTrainingJobId": {
      "type": "string",
      "description": "Job ID of a previous training job for incremental training."
    },
    "sagemakerIamRoleArn": {
      "type": "string"
    },
    "neptuneIamRoleArn": {
      "type": "string"
    },
    "modelName": {
      "type": "string",
      "description": "The model type to train: rgcn (relational graph convolutional network), transe, distmult, rotate, or custom.",
      "enum": [
        "rgcn",
        "transe",
        "distmult",
        "rotate",
        "custom"
      ]
    },
    "baseProcessingInstanceType": {
      "type": "string",
      "description": "ML instance type for data preparation step."
    },
    "trainingInstanceType": {
      "type": "string",
      "description": "ML instance type for the training step.",
      "default": "ml.p3.2xlarge"
    },
    "trainingInstanceVolumeSizeInGB": {
      "type": "integer",
      "description": "Disk volume size for training instance in GB."
    },
    "trainingTimeOutInSeconds": {
      "type": "integer",
      "description": "Training job timeout in seconds.",
      "default": 86400
    },
    "maxHPONumberOfTrainingJobs": {
      "type": "integer",
      "description": "Maximum total training jobs for hyperparameter tuning. Minimum 10 recommended for meaningful results.",
      "default": 2
    },
    "maxHPOParallelTrainingJobs": {
      "type": "integer",
      "description": "Maximum parallel training jobs.",
      "default": 2
    },
    "subnets": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "securityGroupIds": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "volumeEncryptionKMSKey": {
      "type": "string"
    },
    "s3OutputEncryptionKMSKey": {
      "type": "string"
    },
    "enableInterContainerTrafficEncryption": {
      "type": "boolean",
      "default": true
    },
    "enableManagedSpotTraining": {
      "type": "boolean",
      "description": "Whether to use EC2 spot instances for training.",
      "default": false
    },
    "customModelTrainingParameters": {
      "type": "object",
      "description": "Custom model training configuration.",
      "properties": {
        "sourceS3DirectoryPath": {
          "type": "string",
          "description": "S3 path to the custom training script directory."
        },
        "trainingEntryPointScript": {
          "type": "string",
          "description": "Name of the training entry point script."
        },
        "transformEntryPointScript": {
          "type": "string",
          "description": "Name of the transform entry point script."
        }
      }
    }
  },
  "required": [
    "dataProcessingJobId",
    "trainModelS3Location"
  ]
}