name: "Sagemaker - TrainingJob"
description: Create TrainingJob
inputs:
  - {
      name: region,
      type: String,
      description: "The region to use for the training job",
    }
  ###########################GENERATED SECTION BELOW############################
  
  - {
      name: algorithm_specification,
      type: JsonObject,
      default: '{}',
      description: "The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode.",
    }
  - {
      name: checkpoint_config,
      type: JsonObject,
      default: '{}',
      description: "Contains information about the output location for managed spot training checkpoint data.",
    }
  - {
      name: debug_hook_config,
      type: JsonObject,
      default: '{}',
      description: "Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths.",
    }
  - {
      name: debug_rule_configurations,
      type: JsonArray,
      default: '[]',
      description: "Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.",
    }
  - {
      name: enable_inter_container_traffic_encryption,
      type: Bool,
      default: False,
      description: "To encrypt all communications between ML compute instances in distributed training, choose True.",
    }
  - {
      name: enable_managed_spot_training,
      type: Bool,
      default: False,
      description: "To train models using managed spot training, choose True.",
    }
  - {
      name: enable_network_isolation,
      type: Bool,
      default: False,
      description: "Isolates the training container.",
    }
  - {
      name: environment,
      type: JsonObject,
      default: '{}',
      description: "The environment variables to set in the Docker container.",
    }
  - {
      name: experiment_config,
      type: JsonObject,
      default: '{}',
      description: "Associates a SageMaker job as a trial component with an experiment and trial.",
    }
  - {
      name: hyper_parameters,
      type: JsonObject,
      default: '{}',
      description: "Algorithm-specific parameters that influence the quality of the model.",
    }
  - {
      name: input_data_config,
      type: JsonArray,
      default: '[]',
      description: "An array of Channel objects.",
    }
  - {
      name: output_data_config,
      type: JsonObject,
      default: '{}',
      description: "Specifies the path to the S3 location where you want to store model artifacts.",
    }
  - {
      name: profiler_config,
      type: JsonObject,
      default: '{}',
      description: "Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.",
    }
  - {
      name: profiler_rule_configurations,
      type: JsonArray,
      default: '[]',
      description: "Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.",
    }
  - {
      name: resource_config,
      type: JsonObject,
      default: '{}',
      description: "The resources, including the ML compute instances and ML storage volumes, to use for model training.",
    }
  - {
      name: retry_strategy,
      type: JsonObject,
      default: '{}',
      description: "The number of times to retry the job when the job fails due to an InternalServerError.",
    }
  - {
      name: role_arn,
      type: String,
      default: '',
      description: "The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.",
    }
  - {
      name: stopping_condition,
      type: JsonObject,
      default: '{}',
      description: "Specifies a limit to how long a model training job can run.",
    }
  - {
      name: tags,
      type: JsonArray,
      default: '[]',
      description: "An array of key-value pairs.",
    }
  - {
      name: tensor_board_output_config,
      type: JsonObject,
      default: '{}',
      description: "Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.",
    }
  - {
      name: training_job_name,
      type: String,
      default: '',
      description: "The name of the training job.",
    }
  - {
      name: vpc_config,
      type: JsonObject,
      default: '{}',
      description: "A VpcConfig object that specifies the VPC that you want your training job to connect to.",
    }
  ###########################GENERATED SECTION ABOVE############################

outputs:
  ###########################GENERATED SECTION BELOW############################
  
  - {
      name: ack_resource_metadata,
      type: JsonObject,
      description: "All CRs managed by ACK have a common `Status.",
    }
  - {
      name: conditions,
      type: JsonArray,
      description: "All CRS managed by ACK have a common `Status.",
    }
  - {
      name: creation_time,
      type: String,
      description: "A timestamp that indicates when the training job was created.",
    }
  - {
      name: debug_rule_evaluation_statuses,
      type: JsonArray,
      description: "Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.",
    }
  - {
      name: failure_reason,
      type: String,
      description: "If the training job failed, the reason it failed.",
    }
  - {
      name: last_modified_time,
      type: String,
      description: "A timestamp that indicates when the status of the training job was last modified.",
    }
  - {
      name: model_artifacts,
      type: JsonObject,
      description: "Information about the Amazon S3 location that is configured for storing model artifacts.",
    }
  - {
      name: profiler_rule_evaluation_statuses,
      type: JsonArray,
      description: "Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.",
    }
  - {
      name: profiling_status,
      type: String,
      description: "Profiling status of a training job.",
    }
  - {
      name: secondary_status,
      type: String,
      description: "Provides detailed information about the state of the training job.",
    }
  - {
      name: training_job_status,
      type: String,
      description: "The status of the training job.",
    }
  - {
      name: warm_pool_status,
      type: JsonObject,
      description: "The status of the warm pool associated with the training job.",
    }
  ###########################GENERATED SECTION ABOVE############################

implementation:
  container:
    image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
    command: [python3]
    args:
      - TrainingJob/src/TrainingJob_component.py
      - --region
      - { inputValue: region }
      ###########################GENERATED SECTION BELOW############################
      - --algorithm_specification
      - { inputValue: algorithm_specification }
      - --checkpoint_config
      - { inputValue: checkpoint_config }
      - --debug_hook_config
      - { inputValue: debug_hook_config }
      - --debug_rule_configurations
      - { inputValue: debug_rule_configurations }
      - --enable_inter_container_traffic_encryption
      - { inputValue: enable_inter_container_traffic_encryption }
      - --enable_managed_spot_training
      - { inputValue: enable_managed_spot_training }
      - --enable_network_isolation
      - { inputValue: enable_network_isolation }
      - --environment
      - { inputValue: environment }
      - --experiment_config
      - { inputValue: experiment_config }
      - --hyper_parameters
      - { inputValue: hyper_parameters }
      - --input_data_config
      - { inputValue: input_data_config }
      - --output_data_config
      - { inputValue: output_data_config }
      - --profiler_config
      - { inputValue: profiler_config }
      - --profiler_rule_configurations
      - { inputValue: profiler_rule_configurations }
      - --resource_config
      - { inputValue: resource_config }
      - --retry_strategy
      - { inputValue: retry_strategy }
      - --role_arn
      - { inputValue: role_arn }
      - --stopping_condition
      - { inputValue: stopping_condition }
      - --tags
      - { inputValue: tags }
      - --tensor_board_output_config
      - { inputValue: tensor_board_output_config }
      - --training_job_name
      - { inputValue: training_job_name }
      - --vpc_config
      - { inputValue: vpc_config }
      
      ###########################GENERATED SECTION ABOVE############################