# Copyright 2023 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.

components:
  comp-automl-tabular-cv-trainer:
    executorLabel: exec-automl-tabular-cv-trainer
    inputDefinitions:
      artifacts:
        materialized_cv_splits:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        tuning_result_input:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        deadline_hours:
          parameterType: NUMBER_DOUBLE
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        num_parallel_trials:
          parameterType: NUMBER_INTEGER
        num_selected_trials:
          parameterType: NUMBER_INTEGER
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
        single_run_max_secs:
          parameterType: NUMBER_INTEGER
        worker_pool_specs_override_json:
          defaultValue: '[]'
          parameterType: LIST
    outputDefinitions:
      artifacts:
        tuning_result_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        execution_metrics:
          parameterType: STRUCT
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-cv-trainer-2:
    executorLabel: exec-automl-tabular-cv-trainer-2
    inputDefinitions:
      artifacts:
        materialized_cv_splits:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        tuning_result_input:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        deadline_hours:
          parameterType: NUMBER_DOUBLE
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        num_parallel_trials:
          parameterType: NUMBER_INTEGER
        num_selected_trials:
          parameterType: NUMBER_INTEGER
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
        single_run_max_secs:
          parameterType: NUMBER_INTEGER
        worker_pool_specs_override_json:
          defaultValue: '[]'
          parameterType: LIST
    outputDefinitions:
      artifacts:
        tuning_result_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        execution_metrics:
          parameterType: STRUCT
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-ensemble:
    executorLabel: exec-automl-tabular-ensemble
    inputDefinitions:
      artifacts:
        dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        instance_baseline:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        tuning_result_input:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        warmup_data:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        export_additional_model_without_custom_ops:
          defaultValue: 'false'
          parameterType: BOOLEAN
        location:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model_architecture:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model_without_custom_ops:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        explanation_metadata:
          parameterType: STRUCT
        explanation_parameters:
          parameterType: STRUCT
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-ensemble-2:
    executorLabel: exec-automl-tabular-ensemble-2
    inputDefinitions:
      artifacts:
        dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        instance_baseline:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        tuning_result_input:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        warmup_data:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        export_additional_model_without_custom_ops:
          defaultValue: 'false'
          parameterType: BOOLEAN
        location:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model_architecture:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model_without_custom_ops:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        explanation_metadata:
          parameterType: STRUCT
        explanation_parameters:
          parameterType: STRUCT
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-ensemble-3:
    executorLabel: exec-automl-tabular-ensemble-3
    inputDefinitions:
      artifacts:
        dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        instance_baseline:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        tuning_result_input:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        warmup_data:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        export_additional_model_without_custom_ops:
          defaultValue: 'false'
          parameterType: BOOLEAN
        location:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model_architecture:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        model_without_custom_ops:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        explanation_metadata:
          parameterType: STRUCT
        explanation_parameters:
          parameterType: STRUCT
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-finalizer:
    executorLabel: exec-automl-tabular-finalizer
    inputDefinitions:
      parameters:
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-infra-validator:
    executorLabel: exec-automl-tabular-infra-validator
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
  comp-automl-tabular-infra-validator-2:
    executorLabel: exec-automl-tabular-infra-validator-2
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
  comp-automl-tabular-infra-validator-3:
    executorLabel: exec-automl-tabular-infra-validator-3
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
  comp-automl-tabular-stage-1-tuner:
    executorLabel: exec-automl-tabular-stage-1-tuner
    inputDefinitions:
      artifacts:
        materialized_eval_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        materialized_train_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        deadline_hours:
          parameterType: NUMBER_DOUBLE
        disable_early_stopping:
          defaultValue: 'false'
          parameterType: BOOLEAN
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        num_parallel_trials:
          parameterType: NUMBER_INTEGER
        num_selected_trials:
          parameterType: NUMBER_INTEGER
        project:
          parameterType: STRING
        reduce_search_space_mode:
          defaultValue: regular
          parameterType: STRING
        root_dir:
          parameterType: STRING
        run_distillation:
          defaultValue: 'false'
          parameterType: BOOLEAN
        single_run_max_secs:
          parameterType: NUMBER_INTEGER
        study_spec_parameters_override:
          defaultValue: '[]'
          parameterType: LIST
        tune_feature_selection_rate:
          defaultValue: 'false'
          parameterType: BOOLEAN
        worker_pool_specs_override_json:
          defaultValue: '[]'
          parameterType: LIST
    outputDefinitions:
      artifacts:
        tuning_result_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        execution_metrics:
          parameterType: STRUCT
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-stage-1-tuner-2:
    executorLabel: exec-automl-tabular-stage-1-tuner-2
    inputDefinitions:
      artifacts:
        materialized_eval_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        materialized_train_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        deadline_hours:
          parameterType: NUMBER_DOUBLE
        disable_early_stopping:
          defaultValue: 'false'
          parameterType: BOOLEAN
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        num_parallel_trials:
          parameterType: NUMBER_INTEGER
        num_selected_trials:
          parameterType: NUMBER_INTEGER
        project:
          parameterType: STRING
        reduce_search_space_mode:
          defaultValue: regular
          parameterType: STRING
        root_dir:
          parameterType: STRING
        run_distillation:
          defaultValue: 'false'
          parameterType: BOOLEAN
        single_run_max_secs:
          parameterType: NUMBER_INTEGER
        study_spec_parameters_override:
          defaultValue: '[]'
          parameterType: LIST
        tune_feature_selection_rate:
          defaultValue: 'false'
          parameterType: BOOLEAN
        worker_pool_specs_override_json:
          defaultValue: '[]'
          parameterType: LIST
    outputDefinitions:
      artifacts:
        tuning_result_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        execution_metrics:
          parameterType: STRUCT
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-transform:
    executorLabel: exec-automl-tabular-transform
    inputDefinitions:
      artifacts:
        dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        eval_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        test_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        train_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size_gb:
          defaultValue: '40'
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-16
          parameterType: STRING
        dataflow_max_num_workers:
          defaultValue: '25'
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        materialized_eval_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        materialized_test_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        materialized_train_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        training_schema_uri:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-automl-tabular-transform-2:
    executorLabel: exec-automl-tabular-transform-2
    inputDefinitions:
      artifacts:
        dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        eval_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        test_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        train_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size_gb:
          defaultValue: '40'
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-16
          parameterType: STRING
        dataflow_max_num_workers:
          defaultValue: '25'
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        materialized_eval_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        materialized_test_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        materialized_train_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        training_schema_uri:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-bool-identity:
    executorLabel: exec-bool-identity
    inputDefinitions:
      parameters:
        value:
          parameterType: BOOLEAN
    outputDefinitions:
      parameters:
        Output:
          parameterType: STRING
  comp-bool-identity-2:
    executorLabel: exec-bool-identity-2
    inputDefinitions:
      parameters:
        value:
          parameterType: BOOLEAN
    outputDefinitions:
      parameters:
        Output:
          parameterType: STRING
  comp-bool-identity-3:
    executorLabel: exec-bool-identity-3
    inputDefinitions:
      parameters:
        value:
          parameterType: BOOLEAN
    outputDefinitions:
      parameters:
        Output:
          parameterType: STRING
  comp-calculate-training-parameters:
    executorLabel: exec-calculate-training-parameters
    inputDefinitions:
      parameters:
        fast_testing:
          defaultValue: 0.0
          parameterType: BOOLEAN
        is_skip_architecture_search:
          defaultValue: 0.0
          parameterType: BOOLEAN
        run_distillation:
          parameterType: BOOLEAN
        stage_1_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        stage_2_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        train_budget_milli_node_hours:
          parameterType: NUMBER_DOUBLE
    outputDefinitions:
      parameters:
        distill_stage_1_deadline_hours:
          parameterType: NUMBER_DOUBLE
        reduce_search_space_mode:
          parameterType: STRING
        stage_1_deadline_hours:
          parameterType: NUMBER_DOUBLE
        stage_1_num_selected_trials:
          parameterType: NUMBER_INTEGER
        stage_1_single_run_max_secs:
          parameterType: NUMBER_INTEGER
        stage_2_deadline_hours:
          parameterType: NUMBER_DOUBLE
        stage_2_single_run_max_secs:
          parameterType: NUMBER_INTEGER
  comp-calculate-training-parameters-2:
    executorLabel: exec-calculate-training-parameters-2
    inputDefinitions:
      parameters:
        fast_testing:
          defaultValue: 0.0
          parameterType: BOOLEAN
        is_skip_architecture_search:
          defaultValue: 0.0
          parameterType: BOOLEAN
        run_distillation:
          parameterType: BOOLEAN
        stage_1_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        stage_2_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        train_budget_milli_node_hours:
          parameterType: NUMBER_DOUBLE
    outputDefinitions:
      parameters:
        distill_stage_1_deadline_hours:
          parameterType: NUMBER_DOUBLE
        reduce_search_space_mode:
          parameterType: STRING
        stage_1_deadline_hours:
          parameterType: NUMBER_DOUBLE
        stage_1_num_selected_trials:
          parameterType: NUMBER_INTEGER
        stage_1_single_run_max_secs:
          parameterType: NUMBER_INTEGER
        stage_2_deadline_hours:
          parameterType: NUMBER_DOUBLE
        stage_2_single_run_max_secs:
          parameterType: NUMBER_INTEGER
  comp-condition-2:
    dag:
      outputs:
        artifacts:
          feature-attribution-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-feature_attributions
              producerSubtask: condition-3
          model-evaluation-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-evaluation_metrics
              producerSubtask: condition-3
      tasks:
        automl-tabular-cv-trainer:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-cv-trainer
          dependentTasks:
          - calculate-training-parameters
          - importer
          inputs:
            artifacts:
              materialized_cv_splits:
                componentInputArtifact: pipelinechannel--merge-materialized-splits-splits
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              transform_output:
                componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output
              tuning_result_input:
                taskOutputArtifact:
                  outputArtifactKey: artifact
                  producerTask: importer
            parameters:
              deadline_hours:
                taskOutputParameter:
                  outputParameterKey: stage_2_deadline_hours
                  producerTask: calculate-training-parameters
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_2_num_parallel_trials
              num_selected_trials:
                componentInputParameter: pipelinechannel--stage_2_num_selected_trials
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
              single_run_max_secs:
                taskOutputParameter:
                  outputParameterKey: stage_2_single_run_max_secs
                  producerTask: calculate-training-parameters
              worker_pool_specs_override_json:
                componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override
          taskInfo:
            name: automl-tabular-cv-trainer
        automl-tabular-ensemble:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-ensemble
          dependentTasks:
          - automl-tabular-cv-trainer
          inputs:
            artifacts:
              dataset_schema:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema
              instance_baseline:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              transform_output:
                componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output
              tuning_result_input:
                taskOutputArtifact:
                  outputArtifactKey: tuning_result_output
                  producerTask: automl-tabular-cv-trainer
              warmup_data:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              export_additional_model_without_custom_ops:
                componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: automl-tabular-ensemble
        automl-tabular-infra-validator:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-infra-validator
          dependentTasks:
          - automl-tabular-ensemble
          inputs:
            artifacts:
              unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble
          taskInfo:
            name: automl-tabular-infra-validator
        bool-identity:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-bool-identity
          inputs:
            parameters:
              value:
                componentInputParameter: pipelinechannel--run_evaluation
          taskInfo:
            name: bool-identity
        calculate-training-parameters:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-calculate-training-parameters
          inputs:
            parameters:
              fast_testing:
                componentInputParameter: pipelinechannel--fast_testing
              is_skip_architecture_search:
                runtimeValue:
                  constant: 1.0
              run_distillation:
                componentInputParameter: pipelinechannel--run_distillation
              stage_1_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_1_num_parallel_trials
              stage_2_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_2_num_parallel_trials
              train_budget_milli_node_hours:
                componentInputParameter: pipelinechannel--train_budget_milli_node_hours
          taskInfo:
            name: calculate-training-parameters
        condition-3:
          componentRef:
            name: comp-condition-3
          dependentTasks:
          - automl-tabular-ensemble
          - bool-identity
          - model-upload
          inputs:
            artifacts:
              pipelinechannel--automl-tabular-ensemble-explanation_metadata_artifact:
                taskOutputArtifact:
                  outputArtifactKey: explanation_metadata_artifact
                  producerTask: automl-tabular-ensemble
              pipelinechannel--automl-tabular-ensemble-unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble
              pipelinechannel--model-upload-model:
                taskOutputArtifact:
                  outputArtifactKey: model
                  producerTask: model-upload
            parameters:
              pipelinechannel--automl-tabular-ensemble-explanation_parameters:
                taskOutputParameter:
                  outputParameterKey: explanation_parameters
                  producerTask: automl-tabular-ensemble
              pipelinechannel--bool-identity-Output:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: bool-identity
              pipelinechannel--dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              pipelinechannel--dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              pipelinechannel--dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              pipelinechannel--encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              pipelinechannel--evaluation_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              pipelinechannel--evaluation_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              pipelinechannel--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
              pipelinechannel--evaluation_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              pipelinechannel--evaluation_dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              pipelinechannel--evaluation_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              pipelinechannel--location:
                componentInputParameter: pipelinechannel--location
              pipelinechannel--prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              pipelinechannel--project:
                componentInputParameter: pipelinechannel--project
              pipelinechannel--root_dir:
                componentInputParameter: pipelinechannel--root_dir
              pipelinechannel--string-not-empty-Output:
                componentInputParameter: pipelinechannel--string-not-empty-Output
              pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              pipelinechannel--tabular-stats-and-example-gen-test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              pipelinechannel--target_column:
                componentInputParameter: pipelinechannel--target_column
          taskInfo:
            name: is-evaluation
          triggerPolicy:
            condition: inputs.parameter_values['pipelinechannel--bool-identity-Output']
              == 'true'
        importer:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-importer
          inputs:
            parameters:
              uri:
                componentInputParameter: pipelinechannel--stage_1_tuning_result_artifact_uri
          taskInfo:
            name: importer
        model-upload:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-upload
          dependentTasks:
          - automl-tabular-ensemble
          inputs:
            artifacts:
              explanation_metadata_artifact:
                taskOutputArtifact:
                  outputArtifactKey: explanation_metadata_artifact
                  producerTask: automl-tabular-ensemble
              unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble
            parameters:
              description:
                componentInputParameter: pipelinechannel--model_description
              display_name:
                componentInputParameter: pipelinechannel--model_display_name
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              explanation_parameters:
                taskOutputParameter:
                  outputParameterKey: explanation_parameters
                  producerTask: automl-tabular-ensemble
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
          taskInfo:
            name: model-upload
    inputDefinitions:
      artifacts:
        pipelinechannel--automl-tabular-transform-transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--merge-materialized-splits-splits:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-eval_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-instance_baseline:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        pipelinechannel--cv_trainer_worker_pool_specs_override:
          parameterType: LIST
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--export_additional_model_without_custom_ops:
          parameterType: BOOLEAN
        pipelinechannel--fast_testing:
          parameterType: BOOLEAN
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--model_description:
          parameterType: STRING
        pipelinechannel--model_display_name:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--run_distillation:
          parameterType: BOOLEAN
        pipelinechannel--run_evaluation:
          parameterType: BOOLEAN
        pipelinechannel--stage_1_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stage_1_tuning_result_artifact_uri:
          parameterType: STRING
        pipelinechannel--stage_2_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stage_2_num_selected_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--string-not-empty-Output:
          parameterType: STRING
        pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-test_split_json:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
        pipelinechannel--train_budget_milli_node_hours:
          parameterType: NUMBER_DOUBLE
    outputDefinitions:
      artifacts:
        feature-attribution-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-condition-3:
    dag:
      outputs:
        artifacts:
          feature-attribution-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature_attributions
              producerSubtask: feature-attribution
          model-evaluation-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: evaluation_metrics
              producerSubtask: model-evaluation
      tasks:
        feature-attribution:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-feature-attribution
          dependentTasks:
          - model-batch-explanation
          inputs:
            artifacts:
              predictions_gcs_source:
                taskOutputArtifact:
                  outputArtifactKey: gcs_output_directory
                  producerTask: model-batch-explanation
            parameters:
              dataflow_disk_size:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              dataflow_max_workers_num:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              dataflow_workers_num:
                runtimeValue:
                  constant: 1.0
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: feature-attribution
        model-batch-explanation:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-explanation
          inputs:
            artifacts:
              explanation_metadata_artifact:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-explanation_metadata_artifact
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              explanation_parameters:
                componentInputParameter: pipelinechannel--automl-tabular-ensemble-explanation_parameters
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              generate_explanation:
                runtimeValue:
                  constant: 1.0
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-explanation
        model-batch-predict:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-predict
          inputs:
            artifacts:
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-predict-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-predict
        model-evaluation:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-evaluation
          dependentTasks:
          - model-batch-predict
          inputs:
            artifacts:
              batch_prediction_job:
                taskOutputArtifact:
                  outputArtifactKey: batchpredictionjob
                  producerTask: model-batch-predict
            parameters:
              dataflow_disk_size:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              dataflow_max_workers_num:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              dataflow_workers_num:
                runtimeValue:
                  constant: 1.0
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              ground_truth_column:
                componentInputParameter: pipelinechannel--target_column
              ground_truth_format:
                runtimeValue:
                  constant: jsonl
              location:
                componentInputParameter: pipelinechannel--location
              prediction_label_column:
                runtimeValue:
                  constant: prediction.classes
              prediction_score_column:
                runtimeValue:
                  constant: prediction.scores
              predictions_format:
                runtimeValue:
                  constant: jsonl
              problem_type:
                componentInputParameter: pipelinechannel--prediction_type
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: model-evaluation
        model-evaluation-import:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-evaluation-import
          dependentTasks:
          - feature-attribution
          - model-evaluation
          inputs:
            artifacts:
              feature_attributions:
                taskOutputArtifact:
                  outputArtifactKey: feature_attributions
                  producerTask: feature-attribution
              metrics:
                taskOutputArtifact:
                  outputArtifactKey: evaluation_metrics
                  producerTask: model-evaluation
              model:
                componentInputArtifact: pipelinechannel--model-upload-model
            parameters:
              dataset_paths:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              dataset_type:
                runtimeValue:
                  constant: tf-record
              display_name:
                runtimeValue:
                  constant: AutoML Tabular
              problem_type:
                componentInputParameter: pipelinechannel--prediction_type
          taskInfo:
            name: model-evaluation-import
    inputDefinitions:
      artifacts:
        pipelinechannel--automl-tabular-ensemble-explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--automl-tabular-ensemble-unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
        pipelinechannel--model-upload-model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        pipelinechannel--automl-tabular-ensemble-explanation_parameters:
          parameterType: STRUCT
        pipelinechannel--bool-identity-Output:
          parameterType: STRING
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--string-not-empty-Output:
          parameterType: STRING
        pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-test_split_json:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature-attribution-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-condition-4:
    dag:
      outputs:
        artifacts:
          feature-attribution-2-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-2-feature_attributions
              producerSubtask: condition-5
          feature-attribution-3-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-3-feature_attributions
              producerSubtask: condition-7
          model-evaluation-2-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-2-evaluation_metrics
              producerSubtask: condition-5
          model-evaluation-3-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-3-evaluation_metrics
              producerSubtask: condition-7
      tasks:
        automl-tabular-cv-trainer-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-cv-trainer-2
          dependentTasks:
          - automl-tabular-stage-1-tuner
          - calculate-training-parameters-2
          inputs:
            artifacts:
              materialized_cv_splits:
                componentInputArtifact: pipelinechannel--merge-materialized-splits-splits
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              transform_output:
                componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output
              tuning_result_input:
                taskOutputArtifact:
                  outputArtifactKey: tuning_result_output
                  producerTask: automl-tabular-stage-1-tuner
            parameters:
              deadline_hours:
                taskOutputParameter:
                  outputParameterKey: stage_2_deadline_hours
                  producerTask: calculate-training-parameters-2
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_2_num_parallel_trials
              num_selected_trials:
                componentInputParameter: pipelinechannel--stage_2_num_selected_trials
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
              single_run_max_secs:
                taskOutputParameter:
                  outputParameterKey: stage_2_single_run_max_secs
                  producerTask: calculate-training-parameters-2
              worker_pool_specs_override_json:
                componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override
          taskInfo:
            name: automl-tabular-cv-trainer-2
        automl-tabular-ensemble-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-ensemble-2
          dependentTasks:
          - automl-tabular-cv-trainer-2
          inputs:
            artifacts:
              dataset_schema:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema
              instance_baseline:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              transform_output:
                componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output
              tuning_result_input:
                taskOutputArtifact:
                  outputArtifactKey: tuning_result_output
                  producerTask: automl-tabular-cv-trainer-2
              warmup_data:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              export_additional_model_without_custom_ops:
                componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: automl-tabular-ensemble-2
        automl-tabular-infra-validator-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-infra-validator-2
          dependentTasks:
          - automl-tabular-ensemble-2
          inputs:
            artifacts:
              unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble-2
          taskInfo:
            name: automl-tabular-infra-validator-2
        automl-tabular-stage-1-tuner:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-stage-1-tuner
          dependentTasks:
          - calculate-training-parameters-2
          inputs:
            artifacts:
              materialized_eval_split:
                componentInputArtifact: pipelinechannel--automl-tabular-transform-materialized_eval_split
              materialized_train_split:
                componentInputArtifact: pipelinechannel--automl-tabular-transform-materialized_train_split
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              transform_output:
                componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output
            parameters:
              deadline_hours:
                taskOutputParameter:
                  outputParameterKey: stage_1_deadline_hours
                  producerTask: calculate-training-parameters-2
              disable_early_stopping:
                componentInputParameter: pipelinechannel--disable_early_stopping
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_1_num_parallel_trials
              num_selected_trials:
                taskOutputParameter:
                  outputParameterKey: stage_1_num_selected_trials
                  producerTask: calculate-training-parameters-2
              project:
                componentInputParameter: pipelinechannel--project
              reduce_search_space_mode:
                taskOutputParameter:
                  outputParameterKey: reduce_search_space_mode
                  producerTask: calculate-training-parameters-2
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
              single_run_max_secs:
                taskOutputParameter:
                  outputParameterKey: stage_1_single_run_max_secs
                  producerTask: calculate-training-parameters-2
              study_spec_parameters_override:
                componentInputParameter: pipelinechannel--study_spec_parameters_override
              worker_pool_specs_override_json:
                componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override
          taskInfo:
            name: automl-tabular-stage-1-tuner
        bool-identity-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-bool-identity-2
          inputs:
            parameters:
              value:
                componentInputParameter: pipelinechannel--run_evaluation
          taskInfo:
            name: bool-identity-2
        bool-identity-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-bool-identity-3
          inputs:
            parameters:
              value:
                componentInputParameter: pipelinechannel--run_distillation
          taskInfo:
            name: bool-identity-3
        calculate-training-parameters-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-calculate-training-parameters-2
          inputs:
            parameters:
              fast_testing:
                componentInputParameter: pipelinechannel--fast_testing
              is_skip_architecture_search:
                runtimeValue:
                  constant: 0.0
              run_distillation:
                componentInputParameter: pipelinechannel--run_distillation
              stage_1_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_1_num_parallel_trials
              stage_2_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_2_num_parallel_trials
              train_budget_milli_node_hours:
                componentInputParameter: pipelinechannel--train_budget_milli_node_hours
          taskInfo:
            name: calculate-training-parameters-2
        condition-5:
          componentRef:
            name: comp-condition-5
          dependentTasks:
          - automl-tabular-ensemble-2
          - bool-identity-2
          - bool-identity-3
          inputs:
            artifacts:
              pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact:
                taskOutputArtifact:
                  outputArtifactKey: explanation_metadata_artifact
                  producerTask: automl-tabular-ensemble-2
              pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble-2
            parameters:
              pipelinechannel--automl-tabular-ensemble-2-explanation_parameters:
                taskOutputParameter:
                  outputParameterKey: explanation_parameters
                  producerTask: automl-tabular-ensemble-2
              pipelinechannel--bool-identity-2-Output:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: bool-identity-2
              pipelinechannel--bool-identity-3-Output:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: bool-identity-3
              pipelinechannel--dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              pipelinechannel--dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              pipelinechannel--dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              pipelinechannel--encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              pipelinechannel--evaluation_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              pipelinechannel--evaluation_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              pipelinechannel--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
              pipelinechannel--evaluation_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              pipelinechannel--evaluation_dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              pipelinechannel--evaluation_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              pipelinechannel--location:
                componentInputParameter: pipelinechannel--location
              pipelinechannel--model_description:
                componentInputParameter: pipelinechannel--model_description
              pipelinechannel--model_display_name:
                componentInputParameter: pipelinechannel--model_display_name
              pipelinechannel--prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              pipelinechannel--project:
                componentInputParameter: pipelinechannel--project
              pipelinechannel--root_dir:
                componentInputParameter: pipelinechannel--root_dir
              pipelinechannel--string-not-empty-Output:
                componentInputParameter: pipelinechannel--string-not-empty-Output
              pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              pipelinechannel--tabular-stats-and-example-gen-test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              pipelinechannel--target_column:
                componentInputParameter: pipelinechannel--target_column
          taskInfo:
            name: no-distill
          triggerPolicy:
            condition: inputs.parameter_values['pipelinechannel--bool-identity-3-Output']
              == 'false'
        condition-7:
          componentRef:
            name: comp-condition-7
          dependentTasks:
          - automl-tabular-ensemble-2
          - bool-identity-2
          - bool-identity-3
          - calculate-training-parameters-2
          inputs:
            artifacts:
              pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble-2
              pipelinechannel--tabular-stats-and-example-gen-dataset_schema:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema
              pipelinechannel--tabular-stats-and-example-gen-eval_split:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split
              pipelinechannel--tabular-stats-and-example-gen-instance_baseline:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline
              pipelinechannel--tabular-stats-and-example-gen-metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              pipelinechannel--tabular-stats-and-example-gen-test_split:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-test_split
              pipelinechannel--tabular-stats-and-example-gen-train_split:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-train_split
            parameters:
              pipelinechannel--bool-identity-2-Output:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: bool-identity-2
              pipelinechannel--bool-identity-3-Output:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: bool-identity-3
              pipelinechannel--calculate-training-parameters-2-distill_stage_1_deadline_hours:
                taskOutputParameter:
                  outputParameterKey: distill_stage_1_deadline_hours
                  producerTask: calculate-training-parameters-2
              pipelinechannel--calculate-training-parameters-2-reduce_search_space_mode:
                taskOutputParameter:
                  outputParameterKey: reduce_search_space_mode
                  producerTask: calculate-training-parameters-2
              pipelinechannel--calculate-training-parameters-2-stage_1_single_run_max_secs:
                taskOutputParameter:
                  outputParameterKey: stage_1_single_run_max_secs
                  producerTask: calculate-training-parameters-2
              pipelinechannel--dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              pipelinechannel--dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              pipelinechannel--dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              pipelinechannel--disable_early_stopping:
                componentInputParameter: pipelinechannel--disable_early_stopping
              pipelinechannel--distill_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--distill_batch_predict_machine_type
              pipelinechannel--distill_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count
              pipelinechannel--distill_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count
              pipelinechannel--encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              pipelinechannel--evaluation_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              pipelinechannel--evaluation_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              pipelinechannel--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
              pipelinechannel--evaluation_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              pipelinechannel--evaluation_dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              pipelinechannel--evaluation_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              pipelinechannel--export_additional_model_without_custom_ops:
                componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops
              pipelinechannel--location:
                componentInputParameter: pipelinechannel--location
              pipelinechannel--prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              pipelinechannel--project:
                componentInputParameter: pipelinechannel--project
              pipelinechannel--root_dir:
                componentInputParameter: pipelinechannel--root_dir
              pipelinechannel--stage_1_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_1_num_parallel_trials
              pipelinechannel--stage_1_tuner_worker_pool_specs_override:
                componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override
              pipelinechannel--string-not-empty-Output:
                componentInputParameter: pipelinechannel--string-not-empty-Output
              pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              pipelinechannel--tabular-stats-and-example-gen-test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              pipelinechannel--target_column:
                componentInputParameter: pipelinechannel--target_column
              pipelinechannel--transform_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb
              pipelinechannel--transform_dataflow_machine_type:
                componentInputParameter: pipelinechannel--transform_dataflow_machine_type
              pipelinechannel--transform_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers
          taskInfo:
            name: is-distill
          triggerPolicy:
            condition: inputs.parameter_values['pipelinechannel--bool-identity-3-Output']
              == 'true'
    inputDefinitions:
      artifacts:
        pipelinechannel--automl-tabular-transform-materialized_eval_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--automl-tabular-transform-materialized_train_split:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--automl-tabular-transform-transform_output:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--merge-materialized-splits-splits:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-eval_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-instance_baseline:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-test_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-train_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        pipelinechannel--cv_trainer_worker_pool_specs_override:
          parameterType: LIST
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--disable_early_stopping:
          parameterType: BOOLEAN
        pipelinechannel--distill_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--distill_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--distill_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--export_additional_model_without_custom_ops:
          parameterType: BOOLEAN
        pipelinechannel--fast_testing:
          parameterType: BOOLEAN
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--model_description:
          parameterType: STRING
        pipelinechannel--model_display_name:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--run_distillation:
          parameterType: BOOLEAN
        pipelinechannel--run_evaluation:
          parameterType: BOOLEAN
        pipelinechannel--stage_1_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stage_1_tuner_worker_pool_specs_override:
          parameterType: LIST
        pipelinechannel--stage_2_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stage_2_num_selected_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--string-not-empty-Output:
          parameterType: STRING
        pipelinechannel--study_spec_parameters_override:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-test_split_json:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
        pipelinechannel--train_budget_milli_node_hours:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--transform_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--transform_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--transform_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        feature-attribution-2-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        feature-attribution-3-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-2-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-3-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-condition-5:
    dag:
      outputs:
        artifacts:
          feature-attribution-2-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-2-feature_attributions
              producerSubtask: condition-6
          model-evaluation-2-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-2-evaluation_metrics
              producerSubtask: condition-6
      tasks:
        condition-6:
          componentRef:
            name: comp-condition-6
          dependentTasks:
          - model-upload-2
          inputs:
            artifacts:
              pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact
              pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model
              pipelinechannel--model-upload-2-model:
                taskOutputArtifact:
                  outputArtifactKey: model
                  producerTask: model-upload-2
            parameters:
              pipelinechannel--automl-tabular-ensemble-2-explanation_parameters:
                componentInputParameter: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters
              pipelinechannel--bool-identity-2-Output:
                componentInputParameter: pipelinechannel--bool-identity-2-Output
              pipelinechannel--bool-identity-3-Output:
                componentInputParameter: pipelinechannel--bool-identity-3-Output
              pipelinechannel--dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              pipelinechannel--dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              pipelinechannel--dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              pipelinechannel--encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              pipelinechannel--evaluation_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              pipelinechannel--evaluation_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              pipelinechannel--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
              pipelinechannel--evaluation_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              pipelinechannel--evaluation_dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              pipelinechannel--evaluation_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              pipelinechannel--location:
                componentInputParameter: pipelinechannel--location
              pipelinechannel--prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              pipelinechannel--project:
                componentInputParameter: pipelinechannel--project
              pipelinechannel--root_dir:
                componentInputParameter: pipelinechannel--root_dir
              pipelinechannel--string-not-empty-Output:
                componentInputParameter: pipelinechannel--string-not-empty-Output
              pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              pipelinechannel--tabular-stats-and-example-gen-test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              pipelinechannel--target_column:
                componentInputParameter: pipelinechannel--target_column
          taskInfo:
            name: is-evaluation
          triggerPolicy:
            condition: inputs.parameter_values['pipelinechannel--bool-identity-2-Output']
              == 'true'
        model-upload-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-upload-2
          inputs:
            artifacts:
              explanation_metadata_artifact:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model
            parameters:
              description:
                componentInputParameter: pipelinechannel--model_description
              display_name:
                componentInputParameter: pipelinechannel--model_display_name
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              explanation_parameters:
                componentInputParameter: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
          taskInfo:
            name: model-upload-2
    inputDefinitions:
      artifacts:
        pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        pipelinechannel--automl-tabular-ensemble-2-explanation_parameters:
          parameterType: STRUCT
        pipelinechannel--bool-identity-2-Output:
          parameterType: STRING
        pipelinechannel--bool-identity-3-Output:
          parameterType: STRING
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--model_description:
          parameterType: STRING
        pipelinechannel--model_display_name:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--string-not-empty-Output:
          parameterType: STRING
        pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-test_split_json:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature-attribution-2-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-2-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-condition-6:
    dag:
      outputs:
        artifacts:
          feature-attribution-2-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature_attributions
              producerSubtask: feature-attribution-2
          model-evaluation-2-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: evaluation_metrics
              producerSubtask: model-evaluation-2
      tasks:
        feature-attribution-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-feature-attribution-2
          dependentTasks:
          - model-batch-explanation-2
          inputs:
            artifacts:
              predictions_gcs_source:
                taskOutputArtifact:
                  outputArtifactKey: gcs_output_directory
                  producerTask: model-batch-explanation-2
            parameters:
              dataflow_disk_size:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              dataflow_max_workers_num:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              dataflow_workers_num:
                runtimeValue:
                  constant: 1.0
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: feature-attribution-2
        model-batch-explanation-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-explanation-2
          inputs:
            artifacts:
              explanation_metadata_artifact:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              explanation_parameters:
                componentInputParameter: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              generate_explanation:
                runtimeValue:
                  constant: 1.0
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-explanation-2
        model-batch-predict-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-predict-2
          inputs:
            artifacts:
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-predict-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-predict-2
        model-evaluation-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-evaluation-2
          dependentTasks:
          - model-batch-predict-2
          inputs:
            artifacts:
              batch_prediction_job:
                taskOutputArtifact:
                  outputArtifactKey: batchpredictionjob
                  producerTask: model-batch-predict-2
            parameters:
              dataflow_disk_size:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              dataflow_max_workers_num:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              dataflow_workers_num:
                runtimeValue:
                  constant: 1.0
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              ground_truth_column:
                componentInputParameter: pipelinechannel--target_column
              ground_truth_format:
                runtimeValue:
                  constant: jsonl
              location:
                componentInputParameter: pipelinechannel--location
              prediction_label_column:
                runtimeValue:
                  constant: prediction.classes
              prediction_score_column:
                runtimeValue:
                  constant: prediction.scores
              predictions_format:
                runtimeValue:
                  constant: jsonl
              problem_type:
                componentInputParameter: pipelinechannel--prediction_type
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: model-evaluation-2
        model-evaluation-import-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-evaluation-import-2
          dependentTasks:
          - feature-attribution-2
          - model-evaluation-2
          inputs:
            artifacts:
              feature_attributions:
                taskOutputArtifact:
                  outputArtifactKey: feature_attributions
                  producerTask: feature-attribution-2
              metrics:
                taskOutputArtifact:
                  outputArtifactKey: evaluation_metrics
                  producerTask: model-evaluation-2
              model:
                componentInputArtifact: pipelinechannel--model-upload-2-model
            parameters:
              dataset_paths:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              dataset_type:
                runtimeValue:
                  constant: tf-record
              display_name:
                runtimeValue:
                  constant: AutoML Tabular
              problem_type:
                componentInputParameter: pipelinechannel--prediction_type
          taskInfo:
            name: model-evaluation-import-2
    inputDefinitions:
      artifacts:
        pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
        pipelinechannel--model-upload-2-model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        pipelinechannel--automl-tabular-ensemble-2-explanation_parameters:
          parameterType: STRUCT
        pipelinechannel--bool-identity-2-Output:
          parameterType: STRING
        pipelinechannel--bool-identity-3-Output:
          parameterType: STRING
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--string-not-empty-Output:
          parameterType: STRING
        pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-test_split_json:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature-attribution-2-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-2-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-condition-7:
    dag:
      outputs:
        artifacts:
          feature-attribution-3-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-3-feature_attributions
              producerSubtask: condition-8
          model-evaluation-3-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-3-evaluation_metrics
              producerSubtask: condition-8
      tasks:
        automl-tabular-ensemble-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-ensemble-3
          dependentTasks:
          - automl-tabular-stage-1-tuner-2
          - automl-tabular-transform-2
          inputs:
            artifacts:
              dataset_schema:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema
              instance_baseline:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              transform_output:
                taskOutputArtifact:
                  outputArtifactKey: transform_output
                  producerTask: automl-tabular-transform-2
              tuning_result_input:
                taskOutputArtifact:
                  outputArtifactKey: tuning_result_output
                  producerTask: automl-tabular-stage-1-tuner-2
              warmup_data:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              export_additional_model_without_custom_ops:
                componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: automl-tabular-ensemble-3
        automl-tabular-infra-validator-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-infra-validator-3
          dependentTasks:
          - automl-tabular-ensemble-3
          inputs:
            artifacts:
              unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble-3
          taskInfo:
            name: automl-tabular-infra-validator-3
        automl-tabular-stage-1-tuner-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-stage-1-tuner-2
          dependentTasks:
          - automl-tabular-transform-2
          inputs:
            artifacts:
              materialized_eval_split:
                taskOutputArtifact:
                  outputArtifactKey: materialized_eval_split
                  producerTask: automl-tabular-transform-2
              materialized_train_split:
                taskOutputArtifact:
                  outputArtifactKey: materialized_train_split
                  producerTask: automl-tabular-transform-2
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              transform_output:
                taskOutputArtifact:
                  outputArtifactKey: transform_output
                  producerTask: automl-tabular-transform-2
            parameters:
              deadline_hours:
                componentInputParameter: pipelinechannel--calculate-training-parameters-2-distill_stage_1_deadline_hours
              disable_early_stopping:
                componentInputParameter: pipelinechannel--disable_early_stopping
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_1_num_parallel_trials
              num_selected_trials:
                runtimeValue:
                  constant: 1.0
              project:
                componentInputParameter: pipelinechannel--project
              reduce_search_space_mode:
                componentInputParameter: pipelinechannel--calculate-training-parameters-2-reduce_search_space_mode
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
              run_distillation:
                runtimeValue:
                  constant: 1.0
              single_run_max_secs:
                componentInputParameter: pipelinechannel--calculate-training-parameters-2-stage_1_single_run_max_secs
              worker_pool_specs_override_json:
                componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override
          taskInfo:
            name: automl-tabular-stage-1-tuner-2
        automl-tabular-transform-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-transform-2
          dependentTasks:
          - write-bp-result-path
          - write-bp-result-path-2
          inputs:
            artifacts:
              dataset_schema:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema
              eval_split:
                taskOutputArtifact:
                  outputArtifactKey: result
                  producerTask: write-bp-result-path-2
              metadata:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata
              test_split:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-test_split
              train_split:
                taskOutputArtifact:
                  outputArtifactKey: result
                  producerTask: write-bp-result-path
            parameters:
              dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--transform_dataflow_machine_type
              dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: automl-tabular-transform-2
        condition-8:
          componentRef:
            name: comp-condition-8
          dependentTasks:
          - automl-tabular-ensemble-3
          - model-upload-3
          inputs:
            artifacts:
              pipelinechannel--automl-tabular-ensemble-3-explanation_metadata_artifact:
                taskOutputArtifact:
                  outputArtifactKey: explanation_metadata_artifact
                  producerTask: automl-tabular-ensemble-3
              pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble-3
              pipelinechannel--model-upload-3-model:
                taskOutputArtifact:
                  outputArtifactKey: model
                  producerTask: model-upload-3
            parameters:
              pipelinechannel--automl-tabular-ensemble-3-explanation_parameters:
                taskOutputParameter:
                  outputParameterKey: explanation_parameters
                  producerTask: automl-tabular-ensemble-3
              pipelinechannel--bool-identity-2-Output:
                componentInputParameter: pipelinechannel--bool-identity-2-Output
              pipelinechannel--bool-identity-3-Output:
                componentInputParameter: pipelinechannel--bool-identity-3-Output
              pipelinechannel--dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              pipelinechannel--dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              pipelinechannel--dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              pipelinechannel--encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              pipelinechannel--evaluation_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              pipelinechannel--evaluation_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              pipelinechannel--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
              pipelinechannel--evaluation_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              pipelinechannel--evaluation_dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              pipelinechannel--evaluation_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              pipelinechannel--location:
                componentInputParameter: pipelinechannel--location
              pipelinechannel--prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              pipelinechannel--project:
                componentInputParameter: pipelinechannel--project
              pipelinechannel--root_dir:
                componentInputParameter: pipelinechannel--root_dir
              pipelinechannel--string-not-empty-Output:
                componentInputParameter: pipelinechannel--string-not-empty-Output
              pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              pipelinechannel--tabular-stats-and-example-gen-test_split_json:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              pipelinechannel--target_column:
                componentInputParameter: pipelinechannel--target_column
          taskInfo:
            name: is-evaluation
          triggerPolicy:
            condition: inputs.parameter_values['pipelinechannel--bool-identity-2-Output']
              == 'true'
        model-batch-predict-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-predict-3
          dependentTasks:
          - read-input-uri
          inputs:
            artifacts:
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: read-input-uri
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-predict-train-split
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--distill_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: tf-record
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-predict-3
        model-batch-predict-4:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-predict-4
          dependentTasks:
          - read-input-uri-2
          inputs:
            artifacts:
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: read-input-uri-2
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-predict-eval-split
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--distill_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: tf-record
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-predict-4
        model-upload-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-upload-3
          dependentTasks:
          - automl-tabular-ensemble-3
          - automl-tabular-infra-validator-3
          inputs:
            artifacts:
              explanation_metadata_artifact:
                taskOutputArtifact:
                  outputArtifactKey: explanation_metadata_artifact
                  producerTask: automl-tabular-ensemble-3
              unmanaged_container_model:
                taskOutputArtifact:
                  outputArtifactKey: unmanaged_container_model
                  producerTask: automl-tabular-ensemble-3
            parameters:
              display_name:
                runtimeValue:
                  constant: automl-tabular-distill-model-upload-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              explanation_parameters:
                taskOutputParameter:
                  outputParameterKey: explanation_parameters
                  producerTask: automl-tabular-ensemble-3
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
          taskInfo:
            name: model-upload-3
        read-input-uri:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-read-input-uri
          inputs:
            artifacts:
              split_uri:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-train_split
          taskInfo:
            name: read-input-uri
        read-input-uri-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-read-input-uri-2
          inputs:
            artifacts:
              split_uri:
                componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split
          taskInfo:
            name: read-input-uri-2
        write-bp-result-path:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-write-bp-result-path
          dependentTasks:
          - model-batch-predict-3
          inputs:
            artifacts:
              bp_job:
                taskOutputArtifact:
                  outputArtifactKey: batchpredictionjob
                  producerTask: model-batch-predict-3
          taskInfo:
            name: write-bp-result-path
        write-bp-result-path-2:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-write-bp-result-path-2
          dependentTasks:
          - model-batch-predict-4
          inputs:
            artifacts:
              bp_job:
                taskOutputArtifact:
                  outputArtifactKey: batchpredictionjob
                  producerTask: model-batch-predict-4
          taskInfo:
            name: write-bp-result-path-2
    inputDefinitions:
      artifacts:
        pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-eval_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-instance_baseline:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-test_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        pipelinechannel--tabular-stats-and-example-gen-train_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        pipelinechannel--bool-identity-2-Output:
          parameterType: STRING
        pipelinechannel--bool-identity-3-Output:
          parameterType: STRING
        pipelinechannel--calculate-training-parameters-2-distill_stage_1_deadline_hours:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--calculate-training-parameters-2-reduce_search_space_mode:
          parameterType: STRING
        pipelinechannel--calculate-training-parameters-2-stage_1_single_run_max_secs:
          parameterType: NUMBER_INTEGER
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--disable_early_stopping:
          parameterType: BOOLEAN
        pipelinechannel--distill_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--distill_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--distill_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--export_additional_model_without_custom_ops:
          parameterType: BOOLEAN
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--stage_1_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stage_1_tuner_worker_pool_specs_override:
          parameterType: LIST
        pipelinechannel--string-not-empty-Output:
          parameterType: STRING
        pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-test_split_json:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
        pipelinechannel--transform_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--transform_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--transform_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        feature-attribution-3-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-3-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-condition-8:
    dag:
      outputs:
        artifacts:
          feature-attribution-3-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature_attributions
              producerSubtask: feature-attribution-3
          model-evaluation-3-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: evaluation_metrics
              producerSubtask: model-evaluation-3
      tasks:
        feature-attribution-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-feature-attribution-3
          dependentTasks:
          - model-batch-explanation-3
          inputs:
            artifacts:
              predictions_gcs_source:
                taskOutputArtifact:
                  outputArtifactKey: gcs_output_directory
                  producerTask: model-batch-explanation-3
            parameters:
              dataflow_disk_size:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              dataflow_max_workers_num:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              dataflow_workers_num:
                runtimeValue:
                  constant: 1.0
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: feature-attribution-3
        model-batch-explanation-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-explanation-3
          inputs:
            artifacts:
              explanation_metadata_artifact:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-3-explanation_metadata_artifact
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              explanation_parameters:
                componentInputParameter: pipelinechannel--automl-tabular-ensemble-3-explanation_parameters
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json
              generate_explanation:
                runtimeValue:
                  constant: 1.0
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-explanation-3
        model-batch-predict-5:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-batch-predict-5
          inputs:
            artifacts:
              unmanaged_container_model:
                componentInputArtifact: pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model
            parameters:
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              gcs_destination_output_uri_prefix:
                componentInputParameter: pipelinechannel--root_dir
              gcs_source_uris:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              instances_format:
                runtimeValue:
                  constant: tf-record
              job_display_name:
                runtimeValue:
                  constant: batch-predict-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
              location:
                componentInputParameter: pipelinechannel--location
              machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              predictions_format:
                runtimeValue:
                  constant: jsonl
              project:
                componentInputParameter: pipelinechannel--project
              starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
          taskInfo:
            name: model-batch-predict-5
        model-evaluation-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-evaluation-3
          dependentTasks:
          - model-batch-predict-5
          inputs:
            artifacts:
              batch_prediction_job:
                taskOutputArtifact:
                  outputArtifactKey: batchpredictionjob
                  producerTask: model-batch-predict-5
            parameters:
              dataflow_disk_size:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              dataflow_max_workers_num:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              dataflow_workers_num:
                runtimeValue:
                  constant: 1.0
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              ground_truth_column:
                componentInputParameter: pipelinechannel--target_column
              ground_truth_format:
                runtimeValue:
                  constant: jsonl
              location:
                componentInputParameter: pipelinechannel--location
              prediction_label_column:
                runtimeValue:
                  constant: prediction.classes
              prediction_score_column:
                runtimeValue:
                  constant: prediction.scores
              predictions_format:
                runtimeValue:
                  constant: jsonl
              problem_type:
                componentInputParameter: pipelinechannel--prediction_type
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: model-evaluation-3
        model-evaluation-import-3:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-model-evaluation-import-3
          dependentTasks:
          - feature-attribution-3
          - model-evaluation-3
          inputs:
            artifacts:
              feature_attributions:
                taskOutputArtifact:
                  outputArtifactKey: feature_attributions
                  producerTask: feature-attribution-3
              metrics:
                taskOutputArtifact:
                  outputArtifactKey: evaluation_metrics
                  producerTask: model-evaluation-3
              model:
                componentInputArtifact: pipelinechannel--model-upload-3-model
            parameters:
              dataset_paths:
                componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json
              dataset_type:
                runtimeValue:
                  constant: tf-record
              display_name:
                runtimeValue:
                  constant: AutoML Tabular
              problem_type:
                componentInputParameter: pipelinechannel--prediction_type
          taskInfo:
            name: model-evaluation-import-3
    inputDefinitions:
      artifacts:
        pipelinechannel--automl-tabular-ensemble-3-explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
        pipelinechannel--model-upload-3-model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        pipelinechannel--automl-tabular-ensemble-3-explanation_parameters:
          parameterType: STRUCT
        pipelinechannel--bool-identity-2-Output:
          parameterType: STRING
        pipelinechannel--bool-identity-3-Output:
          parameterType: STRING
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--string-not-empty-Output:
          parameterType: STRING
        pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
          parameterType: LIST
        pipelinechannel--tabular-stats-and-example-gen-test_split_json:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature-attribution-3-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-3-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-exit-handler-1:
    dag:
      outputs:
        artifacts:
          feature-attribution-2-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-2-feature_attributions
              producerSubtask: condition-4
          feature-attribution-3-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-3-feature_attributions
              producerSubtask: condition-4
          feature-attribution-feature_attributions:
            artifactSelectors:
            - outputArtifactKey: feature-attribution-feature_attributions
              producerSubtask: condition-2
          model-evaluation-2-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-2-evaluation_metrics
              producerSubtask: condition-4
          model-evaluation-3-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-3-evaluation_metrics
              producerSubtask: condition-4
          model-evaluation-evaluation_metrics:
            artifactSelectors:
            - outputArtifactKey: model-evaluation-evaluation_metrics
              producerSubtask: condition-2
      tasks:
        automl-tabular-transform:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-automl-tabular-transform
          dependentTasks:
          - tabular-stats-and-example-gen
          inputs:
            artifacts:
              dataset_schema:
                taskOutputArtifact:
                  outputArtifactKey: dataset_schema
                  producerTask: tabular-stats-and-example-gen
              eval_split:
                taskOutputArtifact:
                  outputArtifactKey: eval_split
                  producerTask: tabular-stats-and-example-gen
              metadata:
                taskOutputArtifact:
                  outputArtifactKey: metadata
                  producerTask: tabular-stats-and-example-gen
              test_split:
                taskOutputArtifact:
                  outputArtifactKey: test_split
                  producerTask: tabular-stats-and-example-gen
              train_split:
                taskOutputArtifact:
                  outputArtifactKey: train_split
                  producerTask: tabular-stats-and-example-gen
            parameters:
              dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--transform_dataflow_machine_type
              dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              project:
                componentInputParameter: pipelinechannel--project
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
          taskInfo:
            name: automl-tabular-transform
        condition-2:
          componentRef:
            name: comp-condition-2
          dependentTasks:
          - automl-tabular-transform
          - merge-materialized-splits
          - string-not-empty
          - tabular-stats-and-example-gen
          inputs:
            artifacts:
              pipelinechannel--automl-tabular-transform-transform_output:
                taskOutputArtifact:
                  outputArtifactKey: transform_output
                  producerTask: automl-tabular-transform
              pipelinechannel--merge-materialized-splits-splits:
                taskOutputArtifact:
                  outputArtifactKey: splits
                  producerTask: merge-materialized-splits
              pipelinechannel--tabular-stats-and-example-gen-dataset_schema:
                taskOutputArtifact:
                  outputArtifactKey: dataset_schema
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-eval_split:
                taskOutputArtifact:
                  outputArtifactKey: eval_split
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-instance_baseline:
                taskOutputArtifact:
                  outputArtifactKey: instance_baseline
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-metadata:
                taskOutputArtifact:
                  outputArtifactKey: metadata
                  producerTask: tabular-stats-and-example-gen
            parameters:
              pipelinechannel--cv_trainer_worker_pool_specs_override:
                componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override
              pipelinechannel--dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              pipelinechannel--dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              pipelinechannel--dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              pipelinechannel--encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              pipelinechannel--evaluation_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              pipelinechannel--evaluation_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              pipelinechannel--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
              pipelinechannel--evaluation_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              pipelinechannel--evaluation_dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              pipelinechannel--evaluation_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              pipelinechannel--export_additional_model_without_custom_ops:
                componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops
              pipelinechannel--fast_testing:
                componentInputParameter: pipelinechannel--fast_testing
              pipelinechannel--location:
                componentInputParameter: pipelinechannel--location
              pipelinechannel--model_description:
                componentInputParameter: pipelinechannel--model_description
              pipelinechannel--model_display_name:
                componentInputParameter: pipelinechannel--model_display_name
              pipelinechannel--prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              pipelinechannel--project:
                componentInputParameter: pipelinechannel--project
              pipelinechannel--root_dir:
                componentInputParameter: pipelinechannel--root_dir
              pipelinechannel--run_distillation:
                componentInputParameter: pipelinechannel--run_distillation
              pipelinechannel--run_evaluation:
                componentInputParameter: pipelinechannel--run_evaluation
              pipelinechannel--stage_1_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_1_num_parallel_trials
              pipelinechannel--stage_1_tuning_result_artifact_uri:
                componentInputParameter: pipelinechannel--stage_1_tuning_result_artifact_uri
              pipelinechannel--stage_2_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_2_num_parallel_trials
              pipelinechannel--stage_2_num_selected_trials:
                componentInputParameter: pipelinechannel--stage_2_num_selected_trials
              pipelinechannel--string-not-empty-Output:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: string-not-empty
              pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
                taskOutputParameter:
                  outputParameterKey: downsampled_test_split_json
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-test_split_json:
                taskOutputParameter:
                  outputParameterKey: test_split_json
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--target_column:
                componentInputParameter: pipelinechannel--target_column
              pipelinechannel--train_budget_milli_node_hours:
                componentInputParameter: pipelinechannel--train_budget_milli_node_hours
          taskInfo:
            name: stage_1_tuning_result_artifact_uri_not_empty
          triggerPolicy:
            condition: inputs.parameter_values['pipelinechannel--string-not-empty-Output']
              == 'true'
        condition-4:
          componentRef:
            name: comp-condition-4
          dependentTasks:
          - automl-tabular-transform
          - merge-materialized-splits
          - string-not-empty
          - tabular-stats-and-example-gen
          inputs:
            artifacts:
              pipelinechannel--automl-tabular-transform-materialized_eval_split:
                taskOutputArtifact:
                  outputArtifactKey: materialized_eval_split
                  producerTask: automl-tabular-transform
              pipelinechannel--automl-tabular-transform-materialized_train_split:
                taskOutputArtifact:
                  outputArtifactKey: materialized_train_split
                  producerTask: automl-tabular-transform
              pipelinechannel--automl-tabular-transform-transform_output:
                taskOutputArtifact:
                  outputArtifactKey: transform_output
                  producerTask: automl-tabular-transform
              pipelinechannel--merge-materialized-splits-splits:
                taskOutputArtifact:
                  outputArtifactKey: splits
                  producerTask: merge-materialized-splits
              pipelinechannel--tabular-stats-and-example-gen-dataset_schema:
                taskOutputArtifact:
                  outputArtifactKey: dataset_schema
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-eval_split:
                taskOutputArtifact:
                  outputArtifactKey: eval_split
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-instance_baseline:
                taskOutputArtifact:
                  outputArtifactKey: instance_baseline
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-metadata:
                taskOutputArtifact:
                  outputArtifactKey: metadata
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-test_split:
                taskOutputArtifact:
                  outputArtifactKey: test_split
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-train_split:
                taskOutputArtifact:
                  outputArtifactKey: train_split
                  producerTask: tabular-stats-and-example-gen
            parameters:
              pipelinechannel--cv_trainer_worker_pool_specs_override:
                componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override
              pipelinechannel--dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              pipelinechannel--dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              pipelinechannel--dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              pipelinechannel--disable_early_stopping:
                componentInputParameter: pipelinechannel--disable_early_stopping
              pipelinechannel--distill_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--distill_batch_predict_machine_type
              pipelinechannel--distill_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count
              pipelinechannel--distill_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count
              pipelinechannel--encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              pipelinechannel--evaluation_batch_predict_machine_type:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type
              pipelinechannel--evaluation_batch_predict_max_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count
              pipelinechannel--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count
              pipelinechannel--evaluation_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb
              pipelinechannel--evaluation_dataflow_machine_type:
                componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type
              pipelinechannel--evaluation_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers
              pipelinechannel--export_additional_model_without_custom_ops:
                componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops
              pipelinechannel--fast_testing:
                componentInputParameter: pipelinechannel--fast_testing
              pipelinechannel--location:
                componentInputParameter: pipelinechannel--location
              pipelinechannel--model_description:
                componentInputParameter: pipelinechannel--model_description
              pipelinechannel--model_display_name:
                componentInputParameter: pipelinechannel--model_display_name
              pipelinechannel--prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              pipelinechannel--project:
                componentInputParameter: pipelinechannel--project
              pipelinechannel--root_dir:
                componentInputParameter: pipelinechannel--root_dir
              pipelinechannel--run_distillation:
                componentInputParameter: pipelinechannel--run_distillation
              pipelinechannel--run_evaluation:
                componentInputParameter: pipelinechannel--run_evaluation
              pipelinechannel--stage_1_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_1_num_parallel_trials
              pipelinechannel--stage_1_tuner_worker_pool_specs_override:
                componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override
              pipelinechannel--stage_2_num_parallel_trials:
                componentInputParameter: pipelinechannel--stage_2_num_parallel_trials
              pipelinechannel--stage_2_num_selected_trials:
                componentInputParameter: pipelinechannel--stage_2_num_selected_trials
              pipelinechannel--string-not-empty-Output:
                taskOutputParameter:
                  outputParameterKey: Output
                  producerTask: string-not-empty
              pipelinechannel--study_spec_parameters_override:
                componentInputParameter: pipelinechannel--study_spec_parameters_override
              pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json:
                taskOutputParameter:
                  outputParameterKey: downsampled_test_split_json
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--tabular-stats-and-example-gen-test_split_json:
                taskOutputParameter:
                  outputParameterKey: test_split_json
                  producerTask: tabular-stats-and-example-gen
              pipelinechannel--target_column:
                componentInputParameter: pipelinechannel--target_column
              pipelinechannel--train_budget_milli_node_hours:
                componentInputParameter: pipelinechannel--train_budget_milli_node_hours
              pipelinechannel--transform_dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb
              pipelinechannel--transform_dataflow_machine_type:
                componentInputParameter: pipelinechannel--transform_dataflow_machine_type
              pipelinechannel--transform_dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers
          taskInfo:
            name: stage_1_tuning_result_artifact_uri_empty
          triggerPolicy:
            condition: inputs.parameter_values['pipelinechannel--string-not-empty-Output']
              == 'false'
        merge-materialized-splits:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-merge-materialized-splits
          dependentTasks:
          - automl-tabular-transform
          inputs:
            artifacts:
              split_0:
                taskOutputArtifact:
                  outputArtifactKey: materialized_train_split
                  producerTask: automl-tabular-transform
              split_1:
                taskOutputArtifact:
                  outputArtifactKey: materialized_eval_split
                  producerTask: automl-tabular-transform
          taskInfo:
            name: merge-materialized-splits
        string-not-empty:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-string-not-empty
          inputs:
            parameters:
              value:
                componentInputParameter: pipelinechannel--stage_1_tuning_result_artifact_uri
          taskInfo:
            name: string-not-empty
        tabular-stats-and-example-gen:
          cachingOptions:
            enableCache: true
          componentRef:
            name: comp-tabular-stats-and-example-gen
          inputs:
            parameters:
              additional_experiments_json:
                componentInputParameter: pipelinechannel--additional_experiments
              data_source_bigquery_table_path:
                componentInputParameter: pipelinechannel--get-data-source-uri-data_source_bigquery_table_path
              data_source_csv_filenames:
                componentInputParameter: pipelinechannel--get-data-source-uri-data_source_csv_filenames
              dataflow_disk_size_gb:
                componentInputParameter: pipelinechannel--stats_and_example_gen_dataflow_disk_size_gb
              dataflow_machine_type:
                componentInputParameter: pipelinechannel--stats_and_example_gen_dataflow_machine_type
              dataflow_max_num_workers:
                componentInputParameter: pipelinechannel--stats_and_example_gen_dataflow_max_num_workers
              dataflow_service_account:
                componentInputParameter: pipelinechannel--dataflow_service_account
              dataflow_subnetwork:
                componentInputParameter: pipelinechannel--dataflow_subnetwork
              dataflow_use_public_ips:
                componentInputParameter: pipelinechannel--dataflow_use_public_ips
              enable_probabilistic_inference:
                componentInputParameter: pipelinechannel--enable_probabilistic_inference
              encryption_spec_key_name:
                componentInputParameter: pipelinechannel--encryption_spec_key_name
              location:
                componentInputParameter: pipelinechannel--location
              optimization_objective:
                componentInputParameter: pipelinechannel--optimization_objective
              optimization_objective_precision_value:
                componentInputParameter: pipelinechannel--optimization_objective_precision_value
              optimization_objective_recall_value:
                componentInputParameter: pipelinechannel--optimization_objective_recall_value
              predefined_split_key:
                componentInputParameter: pipelinechannel--predefined_split_key
              prediction_type:
                componentInputParameter: pipelinechannel--prediction_type
              project:
                componentInputParameter: pipelinechannel--project
              quantiles:
                componentInputParameter: pipelinechannel--quantiles
              root_dir:
                componentInputParameter: pipelinechannel--root_dir
              run_distillation:
                componentInputParameter: pipelinechannel--run_distillation
              stratified_split_key:
                componentInputParameter: pipelinechannel--stratified_split_key
              target_column_name:
                componentInputParameter: pipelinechannel--target_column
              test_fraction:
                componentInputParameter: pipelinechannel--test_fraction
              timestamp_split_key:
                componentInputParameter: pipelinechannel--timestamp_split_key
              training_fraction:
                componentInputParameter: pipelinechannel--training_fraction
              transformations:
                runtimeValue:
                  constant: '[]'
              transformations_path:
                componentInputParameter: pipelinechannel--transformations
              validation_fraction:
                componentInputParameter: pipelinechannel--validation_fraction
              weight_column_name:
                componentInputParameter: pipelinechannel--weight_column
          taskInfo:
            name: tabular-stats-and-example-gen
    inputDefinitions:
      parameters:
        pipelinechannel--additional_experiments:
          parameterType: STRUCT
        pipelinechannel--cv_trainer_worker_pool_specs_override:
          parameterType: LIST
        pipelinechannel--dataflow_service_account:
          parameterType: STRING
        pipelinechannel--dataflow_subnetwork:
          parameterType: STRING
        pipelinechannel--dataflow_use_public_ips:
          parameterType: BOOLEAN
        pipelinechannel--disable_early_stopping:
          parameterType: BOOLEAN
        pipelinechannel--distill_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--distill_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--distill_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--enable_probabilistic_inference:
          parameterType: BOOLEAN
        pipelinechannel--encryption_spec_key_name:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_batch_predict_max_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_batch_predict_starting_replica_count:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--evaluation_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--evaluation_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--export_additional_model_without_custom_ops:
          parameterType: BOOLEAN
        pipelinechannel--fast_testing:
          parameterType: BOOLEAN
        pipelinechannel--get-data-source-uri-data_source_bigquery_table_path:
          parameterType: STRING
        pipelinechannel--get-data-source-uri-data_source_csv_filenames:
          parameterType: STRING
        pipelinechannel--location:
          parameterType: STRING
        pipelinechannel--model_description:
          parameterType: STRING
        pipelinechannel--model_display_name:
          parameterType: STRING
        pipelinechannel--optimization_objective:
          parameterType: STRING
        pipelinechannel--optimization_objective_precision_value:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--optimization_objective_recall_value:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--predefined_split_key:
          parameterType: STRING
        pipelinechannel--prediction_type:
          parameterType: STRING
        pipelinechannel--project:
          parameterType: STRING
        pipelinechannel--quantiles:
          parameterType: LIST
        pipelinechannel--root_dir:
          parameterType: STRING
        pipelinechannel--run_distillation:
          parameterType: BOOLEAN
        pipelinechannel--run_evaluation:
          parameterType: BOOLEAN
        pipelinechannel--stage_1_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stage_1_tuner_worker_pool_specs_override:
          parameterType: LIST
        pipelinechannel--stage_1_tuning_result_artifact_uri:
          parameterType: STRING
        pipelinechannel--stage_2_num_parallel_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stage_2_num_selected_trials:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stats_and_example_gen_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stats_and_example_gen_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--stats_and_example_gen_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--stratified_split_key:
          parameterType: STRING
        pipelinechannel--study_spec_parameters_override:
          parameterType: LIST
        pipelinechannel--target_column:
          parameterType: STRING
        pipelinechannel--test_fraction:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--timestamp_split_key:
          parameterType: STRING
        pipelinechannel--train_budget_milli_node_hours:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--training_fraction:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--transform_dataflow_disk_size_gb:
          parameterType: NUMBER_INTEGER
        pipelinechannel--transform_dataflow_machine_type:
          parameterType: STRING
        pipelinechannel--transform_dataflow_max_num_workers:
          parameterType: NUMBER_INTEGER
        pipelinechannel--transformations:
          parameterType: STRING
        pipelinechannel--validation_fraction:
          parameterType: NUMBER_DOUBLE
        pipelinechannel--weight_column:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature-attribution-2-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        feature-attribution-3-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        feature-attribution-feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-2-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-3-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model-evaluation-evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
  comp-feature-attribution:
    executorLabel: exec-feature-attribution
    inputDefinitions:
      artifacts:
        predictions_gcs_source:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size:
          defaultValue: 50.0
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-4
          parameterType: STRING
        dataflow_max_workers_num:
          defaultValue: 5.0
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        dataflow_workers_num:
          defaultValue: 1.0
          parameterType: NUMBER_INTEGER
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          defaultValue: us-central1
          parameterType: STRING
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-feature-attribution-2:
    executorLabel: exec-feature-attribution-2
    inputDefinitions:
      artifacts:
        predictions_gcs_source:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size:
          defaultValue: 50.0
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-4
          parameterType: STRING
        dataflow_max_workers_num:
          defaultValue: 5.0
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        dataflow_workers_num:
          defaultValue: 1.0
          parameterType: NUMBER_INTEGER
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          defaultValue: us-central1
          parameterType: STRING
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-feature-attribution-3:
    executorLabel: exec-feature-attribution-3
    inputDefinitions:
      artifacts:
        predictions_gcs_source:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size:
          defaultValue: 50.0
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-4
          parameterType: STRING
        dataflow_max_workers_num:
          defaultValue: 5.0
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        dataflow_workers_num:
          defaultValue: 1.0
          parameterType: NUMBER_INTEGER
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          defaultValue: us-central1
          parameterType: STRING
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-get-data-source-uri:
    executorLabel: exec-get-data-source-uri
    inputDefinitions:
      artifacts:
        vertex_dataset:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        data_source_bigquery_table_path:
          parameterType: STRING
        data_source_csv_filenames:
          parameterType: STRING
        location:
          parameterType: STRING
        project:
          parameterType: STRING
    outputDefinitions:
      parameters:
        data_source_bigquery_table_path:
          parameterType: STRING
        data_source_csv_filenames:
          parameterType: STRING
  comp-importer:
    executorLabel: exec-importer
    inputDefinitions:
      parameters:
        uri:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
  comp-merge-materialized-splits:
    executorLabel: exec-merge-materialized-splits
    inputDefinitions:
      artifacts:
        split_0:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        split_1:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
    outputDefinitions:
      artifacts:
        splits:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
  comp-model-batch-explanation:
    executorLabel: exec-model-batch-explanation
    inputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-batch-explanation-2:
    executorLabel: exec-model-batch-explanation-2
    inputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-batch-explanation-3:
    executorLabel: exec-model-batch-explanation-3
    inputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-batch-predict:
    executorLabel: exec-model-batch-predict
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-batch-predict-2:
    executorLabel: exec-model-batch-predict-2
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-batch-predict-3:
    executorLabel: exec-model-batch-predict-3
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-batch-predict-4:
    executorLabel: exec-model-batch-predict-4
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-batch-predict-5:
    executorLabel: exec-model-batch-predict-5
    inputDefinitions:
      artifacts:
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        accelerator_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        accelerator_type:
          defaultValue: ''
          parameterType: STRING
        bigquery_destination_output_uri:
          defaultValue: ''
          parameterType: STRING
        bigquery_source_input_uri:
          defaultValue: ''
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        gcs_destination_output_uri_prefix:
          defaultValue: ''
          parameterType: STRING
        gcs_source_uris:
          defaultValue: '[]'
          parameterType: LIST
        generate_explanation:
          defaultValue: 0.0
          parameterType: BOOLEAN
        instances_format:
          defaultValue: jsonl
          parameterType: STRING
        job_display_name:
          parameterType: STRING
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        machine_type:
          defaultValue: ''
          parameterType: STRING
        manual_batch_tuning_parameters_batch_size:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        max_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
        model_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        project:
          parameterType: STRING
        starting_replica_count:
          defaultValue: 0.0
          parameterType: NUMBER_INTEGER
    outputDefinitions:
      artifacts:
        batchpredictionjob:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
        bigquery_output_table:
          artifactType:
            schemaTitle: google.BQTable
            schemaVersion: 0.0.1
        gcs_output_directory:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-evaluation:
    executorLabel: exec-model-evaluation
    inputDefinitions:
      artifacts:
        batch_prediction_job:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size:
          defaultValue: 50.0
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-4
          parameterType: STRING
        dataflow_max_workers_num:
          defaultValue: 5.0
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        dataflow_workers_num:
          defaultValue: 1.0
          parameterType: NUMBER_INTEGER
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        example_weight_column:
          defaultValue: ''
          parameterType: STRING
        ground_truth_column:
          parameterType: STRING
        ground_truth_format:
          defaultValue: jsonl
          parameterType: STRING
        location:
          defaultValue: us-central1
          parameterType: STRING
        prediction_id_column:
          defaultValue: ''
          parameterType: STRING
        prediction_label_column:
          defaultValue: ''
          parameterType: STRING
        prediction_score_column:
          defaultValue: ''
          parameterType: STRING
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        problem_type:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-evaluation-2:
    executorLabel: exec-model-evaluation-2
    inputDefinitions:
      artifacts:
        batch_prediction_job:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size:
          defaultValue: 50.0
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-4
          parameterType: STRING
        dataflow_max_workers_num:
          defaultValue: 5.0
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        dataflow_workers_num:
          defaultValue: 1.0
          parameterType: NUMBER_INTEGER
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        example_weight_column:
          defaultValue: ''
          parameterType: STRING
        ground_truth_column:
          parameterType: STRING
        ground_truth_format:
          defaultValue: jsonl
          parameterType: STRING
        location:
          defaultValue: us-central1
          parameterType: STRING
        prediction_id_column:
          defaultValue: ''
          parameterType: STRING
        prediction_label_column:
          defaultValue: ''
          parameterType: STRING
        prediction_score_column:
          defaultValue: ''
          parameterType: STRING
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        problem_type:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-evaluation-3:
    executorLabel: exec-model-evaluation-3
    inputDefinitions:
      artifacts:
        batch_prediction_job:
          artifactType:
            schemaTitle: google.VertexBatchPredictionJob
            schemaVersion: 0.0.1
      parameters:
        dataflow_disk_size:
          defaultValue: 50.0
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-4
          parameterType: STRING
        dataflow_max_workers_num:
          defaultValue: 5.0
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        dataflow_workers_num:
          defaultValue: 1.0
          parameterType: NUMBER_INTEGER
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        example_weight_column:
          defaultValue: ''
          parameterType: STRING
        ground_truth_column:
          parameterType: STRING
        ground_truth_format:
          defaultValue: jsonl
          parameterType: STRING
        location:
          defaultValue: us-central1
          parameterType: STRING
        prediction_id_column:
          defaultValue: ''
          parameterType: STRING
        prediction_label_column:
          defaultValue: ''
          parameterType: STRING
        prediction_score_column:
          defaultValue: ''
          parameterType: STRING
        predictions_format:
          defaultValue: jsonl
          parameterType: STRING
        problem_type:
          parameterType: STRING
        project:
          parameterType: STRING
        root_dir:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        evaluation_metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-evaluation-import:
    executorLabel: exec-model-evaluation-import
    inputDefinitions:
      artifacts:
        feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        dataset_paths:
          defaultValue: '[]'
          parameterType: LIST
        dataset_type:
          defaultValue: ''
          parameterType: STRING
        display_name:
          defaultValue: ''
          parameterType: STRING
        problem_type:
          parameterType: STRING
    outputDefinitions:
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-evaluation-import-2:
    executorLabel: exec-model-evaluation-import-2
    inputDefinitions:
      artifacts:
        feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        dataset_paths:
          defaultValue: '[]'
          parameterType: LIST
        dataset_type:
          defaultValue: ''
          parameterType: STRING
        display_name:
          defaultValue: ''
          parameterType: STRING
        problem_type:
          parameterType: STRING
    outputDefinitions:
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-evaluation-import-3:
    executorLabel: exec-model-evaluation-import-3
    inputDefinitions:
      artifacts:
        feature_attributions:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        metrics:
          artifactType:
            schemaTitle: system.Metrics
            schemaVersion: 0.0.1
        model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        dataset_paths:
          defaultValue: '[]'
          parameterType: LIST
        dataset_type:
          defaultValue: ''
          parameterType: STRING
        display_name:
          defaultValue: ''
          parameterType: STRING
        problem_type:
          parameterType: STRING
    outputDefinitions:
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-upload:
    executorLabel: exec-model-upload
    inputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        description:
          defaultValue: ''
          parameterType: STRING
        display_name:
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        project:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-upload-2:
    executorLabel: exec-model-upload-2
    inputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        description:
          defaultValue: ''
          parameterType: STRING
        display_name:
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        project:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-model-upload-3:
    executorLabel: exec-model-upload-3
    inputDefinitions:
      artifacts:
        explanation_metadata_artifact:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        unmanaged_container_model:
          artifactType:
            schemaTitle: google.UnmanagedContainerModel
            schemaVersion: 0.0.1
      parameters:
        description:
          defaultValue: ''
          parameterType: STRING
        display_name:
          parameterType: STRING
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        explanation_metadata:
          defaultValue: '{}'
          parameterType: STRUCT
        explanation_parameters:
          defaultValue: '{}'
          parameterType: STRUCT
        labels:
          defaultValue: '{}'
          parameterType: STRUCT
        location:
          defaultValue: us-central1
          parameterType: STRING
        project:
          parameterType: STRING
    outputDefinitions:
      artifacts:
        model:
          artifactType:
            schemaTitle: google.VertexModel
            schemaVersion: 0.0.1
      parameters:
        gcp_resources:
          parameterType: STRING
  comp-read-input-uri:
    executorLabel: exec-read-input-uri
    inputDefinitions:
      artifacts:
        split_uri:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
    outputDefinitions:
      parameters:
        Output:
          parameterType: LIST
  comp-read-input-uri-2:
    executorLabel: exec-read-input-uri-2
    inputDefinitions:
      artifacts:
        split_uri:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
    outputDefinitions:
      parameters:
        Output:
          parameterType: LIST
  comp-string-not-empty:
    executorLabel: exec-string-not-empty
    inputDefinitions:
      parameters:
        value:
          parameterType: STRING
    outputDefinitions:
      parameters:
        Output:
          parameterType: STRING
  comp-tabular-stats-and-example-gen:
    executorLabel: exec-tabular-stats-and-example-gen
    inputDefinitions:
      parameters:
        additional_experiments:
          defaultValue: ''
          parameterType: STRING
        additional_experiments_json:
          defaultValue: '{}'
          parameterType: STRUCT
        data_source_bigquery_table_path:
          defaultValue: ''
          parameterType: STRING
        data_source_csv_filenames:
          defaultValue: ''
          parameterType: STRING
        dataflow_disk_size_gb:
          defaultValue: '40'
          parameterType: NUMBER_INTEGER
        dataflow_machine_type:
          defaultValue: n1-standard-16
          parameterType: STRING
        dataflow_max_num_workers:
          defaultValue: '25'
          parameterType: NUMBER_INTEGER
        dataflow_service_account:
          defaultValue: ''
          parameterType: STRING
        dataflow_subnetwork:
          defaultValue: ''
          parameterType: STRING
        dataflow_use_public_ips:
          defaultValue: 'true'
          parameterType: BOOLEAN
        enable_probabilistic_inference:
          defaultValue: 'false'
          parameterType: BOOLEAN
        encryption_spec_key_name:
          defaultValue: ''
          parameterType: STRING
        location:
          parameterType: STRING
        optimization_objective:
          defaultValue: ''
          parameterType: STRING
        optimization_objective_precision_value:
          defaultValue: '-1'
          parameterType: NUMBER_DOUBLE
        optimization_objective_recall_value:
          defaultValue: '-1'
          parameterType: NUMBER_DOUBLE
        predefined_split_key:
          defaultValue: ''
          parameterType: STRING
        prediction_type:
          parameterType: STRING
        project:
          parameterType: STRING
        quantiles:
          defaultValue: '[]'
          parameterType: LIST
        request_type:
          defaultValue: COLUMN_STATS_ONLY
          parameterType: STRING
        root_dir:
          parameterType: STRING
        run_distillation:
          defaultValue: 'false'
          parameterType: BOOLEAN
        stratified_split_key:
          defaultValue: ''
          parameterType: STRING
        target_column_name:
          parameterType: STRING
        test_fraction:
          defaultValue: '-1'
          parameterType: NUMBER_DOUBLE
        timestamp_split_key:
          defaultValue: ''
          parameterType: STRING
        training_fraction:
          defaultValue: '-1'
          parameterType: NUMBER_DOUBLE
        transformations:
          parameterType: STRING
        transformations_path:
          defaultValue: ''
          parameterType: STRING
        validation_fraction:
          defaultValue: '-1'
          parameterType: NUMBER_DOUBLE
        weight_column_name:
          defaultValue: ''
          parameterType: STRING
    outputDefinitions:
      artifacts:
        dataset_schema:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        dataset_stats:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        eval_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        instance_baseline:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        metadata:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
        test_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
        train_split:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
      parameters:
        downsampled_test_split_json:
          parameterType: LIST
        gcp_resources:
          parameterType: STRING
        test_split_json:
          parameterType: LIST
  comp-write-bp-result-path:
    executorLabel: exec-write-bp-result-path
    inputDefinitions:
      artifacts:
        bp_job:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
    outputDefinitions:
      artifacts:
        result:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
  comp-write-bp-result-path-2:
    executorLabel: exec-write-bp-result-path-2
    inputDefinitions:
      artifacts:
        bp_job:
          artifactType:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
    outputDefinitions:
      artifacts:
        result:
          artifactType:
            schemaTitle: system.Dataset
            schemaVersion: 0.0.1
deploymentSpec:
  executors:
    exec-automl-tabular-cv-trainer:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-cv-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"l2l_cv_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}",
          "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev",
          "\", \"--component_id={{$.pipeline_task_uuid}}\", \"--training_base_dir=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/train\",
          \"--num_parallel_trial=", "{{$.inputs.parameters[''num_parallel_trials'']}}",
          "\", \"--single_run_max_secs=", "{{$.inputs.parameters[''single_run_max_secs'']}}",
          "\", \"--deadline_hours=", "{{$.inputs.parameters[''deadline_hours'']}}",
          "\", \"--valid_trials_completed_threshold=0.7\", \"--num_selected_trials=",
          "{{$.inputs.parameters[''num_selected_trials'']}}", "\", \"--lro_job_info=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\",
          \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_cv_splits=",
          "{{$.inputs.artifacts[''materialized_cv_splits''].uri}}", "\", \"--tuning_result_input_path=",
          "{{$.inputs.artifacts[''tuning_result_input''].uri}}", "\", \"--tuning_result_output_path=",
          "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=",
          "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=",
          "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=",
          "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_custom_job=true\",
          \"--use_json=true\", \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-cv-trainer-2:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-cv-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"l2l_cv_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}",
          "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev",
          "\", \"--component_id={{$.pipeline_task_uuid}}\", \"--training_base_dir=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/train\",
          \"--num_parallel_trial=", "{{$.inputs.parameters[''num_parallel_trials'']}}",
          "\", \"--single_run_max_secs=", "{{$.inputs.parameters[''single_run_max_secs'']}}",
          "\", \"--deadline_hours=", "{{$.inputs.parameters[''deadline_hours'']}}",
          "\", \"--valid_trials_completed_threshold=0.7\", \"--num_selected_trials=",
          "{{$.inputs.parameters[''num_selected_trials'']}}", "\", \"--lro_job_info=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\",
          \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_cv_splits=",
          "{{$.inputs.artifacts[''materialized_cv_splits''].uri}}", "\", \"--tuning_result_input_path=",
          "{{$.inputs.artifacts[''tuning_result_input''].uri}}", "\", \"--tuning_result_output_path=",
          "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=",
          "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=",
          "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=",
          "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_custom_job=true\",
          \"--use_json=true\", \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-ensemble:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-ensemble-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-highmem-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"ensemble\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}",
          "\", \"--model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/model\",
          \"--custom_model_output_path=", "{{$.inputs.parameters[''root_dir'']}}",
          "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/custom_model\", \"--error_file_path=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--export_custom_model=", "{{$.inputs.parameters[''export_additional_model_without_custom_ops'']}}",
          "\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\",
          \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}",
          "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}",
          "\", \"--instance_baseline_path=", "{{$.inputs.artifacts[''instance_baseline''].uri}}",
          "\", \"--warmup_data=", "{{$.inputs.artifacts[''warmup_data''].uri}}", "\",
          \"--prediction_docker_uri=", "us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev",
          "\", \"--model_path=", "{{$.outputs.artifacts[''model''].uri}}", "\", \"--custom_model_path=",
          "{{$.outputs.artifacts[''model_without_custom_ops''].uri}}", "\", \"--explanation_metadata_path=",
          "{{$.outputs.parameters[''explanation_metadata''].output_file}}", ",", "{{$.outputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\", \"--explanation_parameters_path=", "{{$.outputs.parameters[''explanation_parameters''].output_file}}",
          "\", \"--model_architecture_path=", "{{$.outputs.artifacts[''model_architecture''].uri}}",
          "\", \"--use_json=true\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-ensemble-2:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-ensemble-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-highmem-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"ensemble\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}",
          "\", \"--model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/model\",
          \"--custom_model_output_path=", "{{$.inputs.parameters[''root_dir'']}}",
          "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/custom_model\", \"--error_file_path=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--export_custom_model=", "{{$.inputs.parameters[''export_additional_model_without_custom_ops'']}}",
          "\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\",
          \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}",
          "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}",
          "\", \"--instance_baseline_path=", "{{$.inputs.artifacts[''instance_baseline''].uri}}",
          "\", \"--warmup_data=", "{{$.inputs.artifacts[''warmup_data''].uri}}", "\",
          \"--prediction_docker_uri=", "us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev",
          "\", \"--model_path=", "{{$.outputs.artifacts[''model''].uri}}", "\", \"--custom_model_path=",
          "{{$.outputs.artifacts[''model_without_custom_ops''].uri}}", "\", \"--explanation_metadata_path=",
          "{{$.outputs.parameters[''explanation_metadata''].output_file}}", ",", "{{$.outputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\", \"--explanation_parameters_path=", "{{$.outputs.parameters[''explanation_parameters''].output_file}}",
          "\", \"--model_architecture_path=", "{{$.outputs.artifacts[''model_architecture''].uri}}",
          "\", \"--use_json=true\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-ensemble-3:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-ensemble-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-highmem-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"ensemble\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}",
          "\", \"--model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/model\",
          \"--custom_model_output_path=", "{{$.inputs.parameters[''root_dir'']}}",
          "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/custom_model\", \"--error_file_path=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--export_custom_model=", "{{$.inputs.parameters[''export_additional_model_without_custom_ops'']}}",
          "\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\",
          \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}",
          "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}",
          "\", \"--instance_baseline_path=", "{{$.inputs.artifacts[''instance_baseline''].uri}}",
          "\", \"--warmup_data=", "{{$.inputs.artifacts[''warmup_data''].uri}}", "\",
          \"--prediction_docker_uri=", "us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev",
          "\", \"--model_path=", "{{$.outputs.artifacts[''model''].uri}}", "\", \"--custom_model_path=",
          "{{$.outputs.artifacts[''model_without_custom_ops''].uri}}", "\", \"--explanation_metadata_path=",
          "{{$.outputs.parameters[''explanation_metadata''].output_file}}", ",", "{{$.outputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\", \"--explanation_parameters_path=", "{{$.outputs.parameters[''explanation_parameters''].output_file}}",
          "\", \"--model_architecture_path=", "{{$.outputs.artifacts[''model_architecture''].uri}}",
          "\", \"--use_json=true\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-finalizer:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-finalizer-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"cancel_l2l_tuner\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}",
          "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--cleanup_lro_job_infos=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-infra-validator:
      container:
        args:
        - --executor_input
        - '{{$}}'
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev
        resources:
          cpuLimit: 8.0
          memoryLimit: 52.0
    exec-automl-tabular-infra-validator-2:
      container:
        args:
        - --executor_input
        - '{{$}}'
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev
        resources:
          cpuLimit: 8.0
          memoryLimit: 52.0
    exec-automl-tabular-infra-validator-3:
      container:
        args:
        - --executor_input
        - '{{$}}'
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev
        resources:
          cpuLimit: 8.0
          memoryLimit: 52.0
    exec-automl-tabular-stage-1-tuner:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-stage-1-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"l2l_stage_1_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}",
          "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev",
          "\", ", {"IfPresent": {"InputName": "feature_ranking", "Then": ["concat"]}},
          "\"--disable_early_stopping=", "{{$.inputs.parameters[''disable_early_stopping'']}}",
          "\", \"--tune_feature_selection_rate=", "{{$.inputs.parameters[''tune_feature_selection_rate'']}}",
          "\", \"--reduce_search_space_mode=", "{{$.inputs.parameters[''reduce_search_space_mode'']}}",
          "\", \"--component_id={{$.pipeline_task_uuid}}\", \"--training_base_dir=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/train\",
          \"--num_parallel_trial=", "{{$.inputs.parameters[''num_parallel_trials'']}}",
          "\", \"--single_run_max_secs=", "{{$.inputs.parameters[''single_run_max_secs'']}}",
          "\", \"--deadline_hours=", "{{$.inputs.parameters[''deadline_hours'']}}",
          "\", \"--num_selected_trials=", "{{$.inputs.parameters[''num_selected_trials'']}}",
          "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\",
          \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_train_split=",
          "{{$.inputs.artifacts[''materialized_train_split''].uri}}", "\", \"--materialized_eval_split=",
          "{{$.inputs.artifacts[''materialized_eval_split''].uri}}", "\", \"--is_distill=",
          "{{$.inputs.parameters[''run_distillation'']}}", "\", \"--tuning_result_output_path=",
          "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=",
          "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=",
          "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=",
          "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_json=true\",
          \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-stage-1-tuner-2:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-stage-1-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"l2l_stage_1_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}",
          "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev",
          "\", ", {"IfPresent": {"InputName": "feature_ranking", "Then": ["concat"]}},
          "\"--disable_early_stopping=", "{{$.inputs.parameters[''disable_early_stopping'']}}",
          "\", \"--tune_feature_selection_rate=", "{{$.inputs.parameters[''tune_feature_selection_rate'']}}",
          "\", \"--reduce_search_space_mode=", "{{$.inputs.parameters[''reduce_search_space_mode'']}}",
          "\", \"--component_id={{$.pipeline_task_uuid}}\", \"--training_base_dir=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/train\",
          \"--num_parallel_trial=", "{{$.inputs.parameters[''num_parallel_trials'']}}",
          "\", \"--single_run_max_secs=", "{{$.inputs.parameters[''single_run_max_secs'']}}",
          "\", \"--deadline_hours=", "{{$.inputs.parameters[''deadline_hours'']}}",
          "\", \"--num_selected_trials=", "{{$.inputs.parameters[''num_selected_trials'']}}",
          "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\",
          \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_train_split=",
          "{{$.inputs.artifacts[''materialized_train_split''].uri}}", "\", \"--materialized_eval_split=",
          "{{$.inputs.artifacts[''materialized_eval_split''].uri}}", "\", \"--is_distill=",
          "{{$.inputs.parameters[''run_distillation'']}}", "\", \"--tuning_result_output_path=",
          "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=",
          "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=",
          "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=",
          "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_json=true\",
          \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-transform:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"transform\", \"--transform_output_artifact_path=", "{{$.outputs.artifacts[''transform_output''].uri}}",
          "\", \"--transform_output_path=", "{{$.inputs.parameters[''root_dir'']}}",
          "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform\", \"--materialized_splits_output_path=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform_materialized\",
          \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--dataset_schema_path=",
          "{{$.inputs.artifacts[''dataset_schema''].uri}}", "\", \"--train_split=",
          "{{$.inputs.artifacts[''train_split''].uri}}", "\", \"--eval_split=", "{{$.inputs.artifacts[''eval_split''].uri}}",
          "\", \"--test_split=", "{{$.inputs.artifacts[''test_split''].uri}}", "\",
          \"--materialized_train_split=", "{{$.outputs.artifacts[''materialized_train_split''].uri}}",
          "\", \"--materialized_eval_split=", "{{$.outputs.artifacts[''materialized_eval_split''].uri}}",
          "\", \"--materialized_test_split=", "{{$.outputs.artifacts[''materialized_test_split''].uri}}",
          "\", \"--training_schema_path=", "{{$.outputs.artifacts[''training_schema_uri''].uri}}",
          "\", \"--job_name=automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
          "\", \"--dataflow_project=", "{{$.inputs.parameters[''project'']}}", "\",
          \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--dataflow_staging_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_staging\",
          \"--dataflow_tmp_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_tmp\",
          \"--dataflow_max_num_workers=", "{{$.inputs.parameters[''dataflow_max_num_workers'']}}",
          "\", \"--dataflow_machine_type=", "{{$.inputs.parameters[''dataflow_machine_type'']}}",
          "\", \"--dataflow_worker_container_image=", "us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:dev",
          "\", \"--dataflow_disk_size_gb=", "{{$.inputs.parameters[''dataflow_disk_size_gb'']}}",
          "\", \"--dataflow_subnetwork_fully_qualified=", "{{$.inputs.parameters[''dataflow_subnetwork'']}}",
          "\", \"--dataflow_use_public_ips=", "{{$.inputs.parameters[''dataflow_use_public_ips'']}}",
          "\", \"--dataflow_kms_key=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\", \"--dataflow_service_account=", "{{$.inputs.parameters[''dataflow_service_account'']}}",
          "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\",
          \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}",
          "\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-automl-tabular-transform-2:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"transform\", \"--transform_output_artifact_path=", "{{$.outputs.artifacts[''transform_output''].uri}}",
          "\", \"--transform_output_path=", "{{$.inputs.parameters[''root_dir'']}}",
          "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform\", \"--materialized_splits_output_path=",
          "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform_materialized\",
          \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--dataset_schema_path=",
          "{{$.inputs.artifacts[''dataset_schema''].uri}}", "\", \"--train_split=",
          "{{$.inputs.artifacts[''train_split''].uri}}", "\", \"--eval_split=", "{{$.inputs.artifacts[''eval_split''].uri}}",
          "\", \"--test_split=", "{{$.inputs.artifacts[''test_split''].uri}}", "\",
          \"--materialized_train_split=", "{{$.outputs.artifacts[''materialized_train_split''].uri}}",
          "\", \"--materialized_eval_split=", "{{$.outputs.artifacts[''materialized_eval_split''].uri}}",
          "\", \"--materialized_test_split=", "{{$.outputs.artifacts[''materialized_test_split''].uri}}",
          "\", \"--training_schema_path=", "{{$.outputs.artifacts[''training_schema_uri''].uri}}",
          "\", \"--job_name=automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
          "\", \"--dataflow_project=", "{{$.inputs.parameters[''project'']}}", "\",
          \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--dataflow_staging_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_staging\",
          \"--dataflow_tmp_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_tmp\",
          \"--dataflow_max_num_workers=", "{{$.inputs.parameters[''dataflow_max_num_workers'']}}",
          "\", \"--dataflow_machine_type=", "{{$.inputs.parameters[''dataflow_machine_type'']}}",
          "\", \"--dataflow_worker_container_image=", "us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:dev",
          "\", \"--dataflow_disk_size_gb=", "{{$.inputs.parameters[''dataflow_disk_size_gb'']}}",
          "\", \"--dataflow_subnetwork_fully_qualified=", "{{$.inputs.parameters[''dataflow_subnetwork'']}}",
          "\", \"--dataflow_use_public_ips=", "{{$.inputs.parameters[''dataflow_use_public_ips'']}}",
          "\", \"--dataflow_kms_key=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\", \"--dataflow_service_account=", "{{$.inputs.parameters[''dataflow_service_account'']}}",
          "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\",
          \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}",
          "\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-bool-identity:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _bool_identity
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _bool_identity(value: bool) -> str:\n  \"\"\"Returns boolean\
          \ value.\n\n  Args:\n    value: Boolean value to return\n\n  Returns:\n\
          \    Boolean value.\n  \"\"\"\n  return 'true' if value else 'false'\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-bool-identity-2:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _bool_identity
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _bool_identity(value: bool) -> str:\n  \"\"\"Returns boolean\
          \ value.\n\n  Args:\n    value: Boolean value to return\n\n  Returns:\n\
          \    Boolean value.\n  \"\"\"\n  return 'true' if value else 'false'\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-bool-identity-3:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _bool_identity
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _bool_identity(value: bool) -> str:\n  \"\"\"Returns boolean\
          \ value.\n\n  Args:\n    value: Boolean value to return\n\n  Returns:\n\
          \    Boolean value.\n  \"\"\"\n  return 'true' if value else 'false'\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-calculate-training-parameters:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _calculate_training_parameters
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _calculate_training_parameters(\n    stage_1_num_parallel_trials:\
          \ int,\n    train_budget_milli_node_hours: float,\n    stage_2_num_parallel_trials:\
          \ int,\n    run_distillation: bool,\n    is_skip_architecture_search: bool\
          \ = False,\n    fast_testing: bool = False,\n) -> NamedTuple('Outputs',\
          \ [\n    ('stage_1_deadline_hours', float), ('stage_1_num_selected_trials',\
          \ int),\n    ('stage_1_single_run_max_secs', int), ('stage_2_deadline_hours',\
          \ float),\n    ('stage_2_single_run_max_secs', int),\n    ('distill_stage_1_deadline_hours',\
          \ float), ('reduce_search_space_mode', str)\n]):\n  \"\"\"Calculates training\
          \ parameters.\n\n  Args:\n    stage_1_num_parallel_trials: Number of parallel\
          \ trails for stage 1.\n    train_budget_milli_node_hours: The train budget\
          \ of creating this model,\n      expressed in milli node hours i.e. 1,000\
          \ value in this field means 1 node\n      hour.\n    stage_2_num_parallel_trials:\
          \ Number of parallel trails for stage 2.\n    run_distillation: Whether\
          \ to run distill in the training pipeline.\n    is_skip_architecture_search:\
          \ If component is being called in the\n      skip_architecture_search pipeline.\n\
          \    fast_testing: Internal flag used for presubmit tests.\n\n  Returns:\n\
          \      stage_1_deadline_hours: Maximum number of hours to run stage 1.\n\
          \      stage_1_num_selected_trials: Number of selected trails for stage\
          \ 1.\n      stage_1_single_run_max_secs: Maximum number seconds to for a\
          \ single stage\n      1\n        training trial.\n      stage_2_deadline_hours:\
          \ Maximum number of hours to run stage 2.\n      stage_2_single_run_max_secs:\
          \ Maximum number seconds to for a single stage\n      2\n      training\
          \ trial.\n      distill_stage_1_deadline_hours: Maximum number of hours\
          \ to run stage 1 for\n      the model distillation.\n      reduce_search_space_mode:\
          \ The reduce search space mode. Possible values:\n      minimal, regular,\
          \ full.\n  \"\"\"\n  # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\
          \  import collections\n  import math\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\
          \  num_folds = 5\n  distill_total_trials = 100\n\n  stage_1_deadline_hours\
          \ = -1.0\n  stage_1_num_selected_trials = -1\n  stage_1_single_run_max_secs\
          \ = -1\n  stage_2_deadline_hours = -1.0\n  stage_2_single_run_max_secs =\
          \ -1\n  distill_stage_1_deadline_hours = 1.0\n  reduce_search_space_mode\
          \ = 'regular'\n\n  if is_skip_architecture_search:\n    stage_2_deadline_hours\
          \ = train_budget_milli_node_hours / 1000.0\n    stage_2_single_run_max_secs\
          \ = int(stage_2_deadline_hours * 3600.0 / 1.3)\n  else:\n    hours = float(train_budget_milli_node_hours)\
          \ / 1000.0\n    multiplier = stage_1_num_parallel_trials * hours / 500.0\n\
          \    stage_1_single_run_max_secs = int(math.sqrt(multiplier) * 2400.0)\n\
          \    phase_2_rounds = int(\n        math.sqrt(multiplier) * 100 / stage_2_num_parallel_trials\
          \ + 0.5)\n    if phase_2_rounds < 1:\n      phase_2_rounds = 1\n\n    #\
          \ All of magic number \"1.3\" above is because the trial doesn't\n    #\
          \ always finish in time_per_trial. 1.3 is an empirical safety margin here.\n\
          \    stage_1_deadline_secs = int(hours * 3600.0 - 1.3 *\n              \
          \                  stage_1_single_run_max_secs * phase_2_rounds)\n\n   \
          \ if stage_1_deadline_secs < hours * 3600.0 * 0.5:\n      stage_1_deadline_secs\
          \ = int(hours * 3600.0 * 0.5)\n      # Phase 1 deadline is the same as phase\
          \ 2 deadline in this case. Phase 2\n      # can't finish in time after the\
          \ deadline is cut, so adjust the time per\n      # trial to meet the deadline.\n\
          \      stage_1_single_run_max_secs = int(stage_1_deadline_secs /\n     \
          \                                   (1.3 * phase_2_rounds))\n\n    reduce_search_space_mode\
          \ = 'minimal'\n    if multiplier > 2:\n      reduce_search_space_mode =\
          \ 'regular'\n    if multiplier > 4:\n      reduce_search_space_mode = 'full'\n\
          \n    # Stage 2 number of trials is stage_1_num_selected_trials *\n    #\
          \ num_folds, which should be equal to phase_2_rounds *\n    # stage_2_num_parallel_trials.\
          \ Use this information to calculate\n    # stage_1_num_selected_trials:\n\
          \    stage_1_num_selected_trials = int(phase_2_rounds *\n              \
          \                        stage_2_num_parallel_trials / num_folds)\n    stage_1_deadline_hours\
          \ = stage_1_deadline_secs / 3600.0\n\n    stage_2_deadline_hours = hours\
          \ - stage_1_deadline_hours\n    stage_2_single_run_max_secs = stage_1_single_run_max_secs\n\
          \n    if run_distillation:\n      # All of magic number \"1.3\" above is\
          \ because the trial doesn't always\n      # finish in time_per_trial. 1.3\
          \ is an empirical safety margin here.\n      distill_stage_1_deadline_hours\
          \ = math.ceil(\n          float(distill_total_trials) / stage_1_num_parallel_trials\n\
          \      ) * stage_1_single_run_max_secs * 1.3 / 3600.0\n\n  if fast_testing:\n\
          \    distill_stage_1_deadline_hours = 0.2\n    stage_1_deadline_hours =\
          \ 0.2\n    stage_1_single_run_max_secs = 1\n    stage_2_deadline_hours =\
          \ 0.2\n    stage_2_single_run_max_secs = 1\n\n  return collections.namedtuple('Outputs',\
          \ [\n      'stage_1_deadline_hours', 'stage_1_num_selected_trials',\n  \
          \    'stage_1_single_run_max_secs', 'stage_2_deadline_hours',\n      'stage_2_single_run_max_secs',\
          \ 'distill_stage_1_deadline_hours',\n      'reduce_search_space_mode'\n\
          \  ])(stage_1_deadline_hours, stage_1_num_selected_trials,\n     stage_1_single_run_max_secs,\
          \ stage_2_deadline_hours,\n     stage_2_single_run_max_secs, distill_stage_1_deadline_hours,\n\
          \     reduce_search_space_mode)\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-calculate-training-parameters-2:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _calculate_training_parameters
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _calculate_training_parameters(\n    stage_1_num_parallel_trials:\
          \ int,\n    train_budget_milli_node_hours: float,\n    stage_2_num_parallel_trials:\
          \ int,\n    run_distillation: bool,\n    is_skip_architecture_search: bool\
          \ = False,\n    fast_testing: bool = False,\n) -> NamedTuple('Outputs',\
          \ [\n    ('stage_1_deadline_hours', float), ('stage_1_num_selected_trials',\
          \ int),\n    ('stage_1_single_run_max_secs', int), ('stage_2_deadline_hours',\
          \ float),\n    ('stage_2_single_run_max_secs', int),\n    ('distill_stage_1_deadline_hours',\
          \ float), ('reduce_search_space_mode', str)\n]):\n  \"\"\"Calculates training\
          \ parameters.\n\n  Args:\n    stage_1_num_parallel_trials: Number of parallel\
          \ trails for stage 1.\n    train_budget_milli_node_hours: The train budget\
          \ of creating this model,\n      expressed in milli node hours i.e. 1,000\
          \ value in this field means 1 node\n      hour.\n    stage_2_num_parallel_trials:\
          \ Number of parallel trails for stage 2.\n    run_distillation: Whether\
          \ to run distill in the training pipeline.\n    is_skip_architecture_search:\
          \ If component is being called in the\n      skip_architecture_search pipeline.\n\
          \    fast_testing: Internal flag used for presubmit tests.\n\n  Returns:\n\
          \      stage_1_deadline_hours: Maximum number of hours to run stage 1.\n\
          \      stage_1_num_selected_trials: Number of selected trails for stage\
          \ 1.\n      stage_1_single_run_max_secs: Maximum number seconds to for a\
          \ single stage\n      1\n        training trial.\n      stage_2_deadline_hours:\
          \ Maximum number of hours to run stage 2.\n      stage_2_single_run_max_secs:\
          \ Maximum number seconds to for a single stage\n      2\n      training\
          \ trial.\n      distill_stage_1_deadline_hours: Maximum number of hours\
          \ to run stage 1 for\n      the model distillation.\n      reduce_search_space_mode:\
          \ The reduce search space mode. Possible values:\n      minimal, regular,\
          \ full.\n  \"\"\"\n  # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\
          \  import collections\n  import math\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\
          \  num_folds = 5\n  distill_total_trials = 100\n\n  stage_1_deadline_hours\
          \ = -1.0\n  stage_1_num_selected_trials = -1\n  stage_1_single_run_max_secs\
          \ = -1\n  stage_2_deadline_hours = -1.0\n  stage_2_single_run_max_secs =\
          \ -1\n  distill_stage_1_deadline_hours = 1.0\n  reduce_search_space_mode\
          \ = 'regular'\n\n  if is_skip_architecture_search:\n    stage_2_deadline_hours\
          \ = train_budget_milli_node_hours / 1000.0\n    stage_2_single_run_max_secs\
          \ = int(stage_2_deadline_hours * 3600.0 / 1.3)\n  else:\n    hours = float(train_budget_milli_node_hours)\
          \ / 1000.0\n    multiplier = stage_1_num_parallel_trials * hours / 500.0\n\
          \    stage_1_single_run_max_secs = int(math.sqrt(multiplier) * 2400.0)\n\
          \    phase_2_rounds = int(\n        math.sqrt(multiplier) * 100 / stage_2_num_parallel_trials\
          \ + 0.5)\n    if phase_2_rounds < 1:\n      phase_2_rounds = 1\n\n    #\
          \ All of magic number \"1.3\" above is because the trial doesn't\n    #\
          \ always finish in time_per_trial. 1.3 is an empirical safety margin here.\n\
          \    stage_1_deadline_secs = int(hours * 3600.0 - 1.3 *\n              \
          \                  stage_1_single_run_max_secs * phase_2_rounds)\n\n   \
          \ if stage_1_deadline_secs < hours * 3600.0 * 0.5:\n      stage_1_deadline_secs\
          \ = int(hours * 3600.0 * 0.5)\n      # Phase 1 deadline is the same as phase\
          \ 2 deadline in this case. Phase 2\n      # can't finish in time after the\
          \ deadline is cut, so adjust the time per\n      # trial to meet the deadline.\n\
          \      stage_1_single_run_max_secs = int(stage_1_deadline_secs /\n     \
          \                                   (1.3 * phase_2_rounds))\n\n    reduce_search_space_mode\
          \ = 'minimal'\n    if multiplier > 2:\n      reduce_search_space_mode =\
          \ 'regular'\n    if multiplier > 4:\n      reduce_search_space_mode = 'full'\n\
          \n    # Stage 2 number of trials is stage_1_num_selected_trials *\n    #\
          \ num_folds, which should be equal to phase_2_rounds *\n    # stage_2_num_parallel_trials.\
          \ Use this information to calculate\n    # stage_1_num_selected_trials:\n\
          \    stage_1_num_selected_trials = int(phase_2_rounds *\n              \
          \                        stage_2_num_parallel_trials / num_folds)\n    stage_1_deadline_hours\
          \ = stage_1_deadline_secs / 3600.0\n\n    stage_2_deadline_hours = hours\
          \ - stage_1_deadline_hours\n    stage_2_single_run_max_secs = stage_1_single_run_max_secs\n\
          \n    if run_distillation:\n      # All of magic number \"1.3\" above is\
          \ because the trial doesn't always\n      # finish in time_per_trial. 1.3\
          \ is an empirical safety margin here.\n      distill_stage_1_deadline_hours\
          \ = math.ceil(\n          float(distill_total_trials) / stage_1_num_parallel_trials\n\
          \      ) * stage_1_single_run_max_secs * 1.3 / 3600.0\n\n  if fast_testing:\n\
          \    distill_stage_1_deadline_hours = 0.2\n    stage_1_deadline_hours =\
          \ 0.2\n    stage_1_single_run_max_secs = 1\n    stage_2_deadline_hours =\
          \ 0.2\n    stage_2_single_run_max_secs = 1\n\n  return collections.namedtuple('Outputs',\
          \ [\n      'stage_1_deadline_hours', 'stage_1_num_selected_trials',\n  \
          \    'stage_1_single_run_max_secs', 'stage_2_deadline_hours',\n      'stage_2_single_run_max_secs',\
          \ 'distill_stage_1_deadline_hours',\n      'reduce_search_space_mode'\n\
          \  ])(stage_1_deadline_hours, stage_1_num_selected_trials,\n     stage_1_single_run_max_secs,\
          \ stage_2_deadline_hours,\n     stage_2_single_run_max_secs, distill_stage_1_deadline_hours,\n\
          \     reduce_search_space_mode)\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-feature-attribution:
      container:
        args:
        - --task
        - explanation
        - --setup_file
        - /setup.py
        - --project_id
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --batch_prediction_gcs_source
        - '{{$.inputs.artifacts[''predictions_gcs_source''].uri}}'
        - --batch_prediction_format
        - '{{$.inputs.parameters[''predictions_format'']}}'
        - --root_dir
        - '{"Concat": ["{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}"]}'
        - --dataflow_job_prefix
        - evaluation-feautre-attribution-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
        - --dataflow_service_account
        - '{{$.inputs.parameters[''dataflow_service_account'']}}'
        - --dataflow_disk_size
        - '{{$.inputs.parameters[''dataflow_disk_size'']}}'
        - --dataflow_machine_type
        - '{{$.inputs.parameters[''dataflow_machine_type'']}}'
        - --dataflow_workers_num
        - '{{$.inputs.parameters[''dataflow_workers_num'']}}'
        - --dataflow_max_workers_num
        - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}'
        - --dataflow_subnetwork
        - '{{$.inputs.parameters[''dataflow_subnetwork'']}}'
        - --dataflow_use_public_ips
        - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}'
        - --kms_key_name
        - '{{$.inputs.parameters[''encryption_spec_key_name'']}}'
        - --gcs_output_path
        - '{{$.outputs.artifacts[''feature_attributions''].uri}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python
        - /main.py
        image: gcr.io/ml-pipeline/model-evaluation:v0.7
    exec-feature-attribution-2:
      container:
        args:
        - --task
        - explanation
        - --setup_file
        - /setup.py
        - --project_id
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --batch_prediction_gcs_source
        - '{{$.inputs.artifacts[''predictions_gcs_source''].uri}}'
        - --batch_prediction_format
        - '{{$.inputs.parameters[''predictions_format'']}}'
        - --root_dir
        - '{"Concat": ["{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}"]}'
        - --dataflow_job_prefix
        - evaluation-feautre-attribution-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
        - --dataflow_service_account
        - '{{$.inputs.parameters[''dataflow_service_account'']}}'
        - --dataflow_disk_size
        - '{{$.inputs.parameters[''dataflow_disk_size'']}}'
        - --dataflow_machine_type
        - '{{$.inputs.parameters[''dataflow_machine_type'']}}'
        - --dataflow_workers_num
        - '{{$.inputs.parameters[''dataflow_workers_num'']}}'
        - --dataflow_max_workers_num
        - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}'
        - --dataflow_subnetwork
        - '{{$.inputs.parameters[''dataflow_subnetwork'']}}'
        - --dataflow_use_public_ips
        - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}'
        - --kms_key_name
        - '{{$.inputs.parameters[''encryption_spec_key_name'']}}'
        - --gcs_output_path
        - '{{$.outputs.artifacts[''feature_attributions''].uri}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python
        - /main.py
        image: gcr.io/ml-pipeline/model-evaluation:v0.7
    exec-feature-attribution-3:
      container:
        args:
        - --task
        - explanation
        - --setup_file
        - /setup.py
        - --project_id
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --batch_prediction_gcs_source
        - '{{$.inputs.artifacts[''predictions_gcs_source''].uri}}'
        - --batch_prediction_format
        - '{{$.inputs.parameters[''predictions_format'']}}'
        - --root_dir
        - '{"Concat": ["{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}"]}'
        - --dataflow_job_prefix
        - evaluation-feautre-attribution-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
        - --dataflow_service_account
        - '{{$.inputs.parameters[''dataflow_service_account'']}}'
        - --dataflow_disk_size
        - '{{$.inputs.parameters[''dataflow_disk_size'']}}'
        - --dataflow_machine_type
        - '{{$.inputs.parameters[''dataflow_machine_type'']}}'
        - --dataflow_workers_num
        - '{{$.inputs.parameters[''dataflow_workers_num'']}}'
        - --dataflow_max_workers_num
        - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}'
        - --dataflow_subnetwork
        - '{{$.inputs.parameters[''dataflow_subnetwork'']}}'
        - --dataflow_use_public_ips
        - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}'
        - --kms_key_name
        - '{{$.inputs.parameters[''encryption_spec_key_name'']}}'
        - --gcs_output_path
        - '{{$.outputs.artifacts[''feature_attributions''].uri}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python
        - /main.py
        image: gcr.io/ml-pipeline/model-evaluation:v0.7
    exec-get-data-source-uri:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _get_data_source_uri
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _get_data_source_uri(\n    project: str,\n    location: str,\n\
          \    data_source_csv_filenames: str,\n    data_source_bigquery_table_path:\
          \ str,\n    vertex_dataset: Input[dsl.Artifact],\n) -> NamedTuple('Outputs',\
          \ [\n    ('data_source_csv_filenames', str),\n    ('data_source_bigquery_table_path',\
          \ str),\n]):\n  \"\"\"Get the data source URI.\n\n  Args:\n    project:\
          \ The GCP project that runs the pipeline components.\n    location: The\
          \ GCP region that runs the pipeline components.\n    data_source_csv_filenames:\
          \ The CSV GCS path when data source is CSV.\n    data_source_bigquery_table_path:\
          \ The BigQuery table when data source is BQ.\n    vertex_dataset: The Vertex\
          \ dataset when data source is Vertex dataset.\n\n  Returns:\n    A named\
          \ tuple of CSV or BQ URI.\n  \"\"\"\n  # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\
          \  import collections\n  from google.cloud import aiplatform\n  from google.cloud\
          \ import aiplatform_v1beta1 as aip\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\
          \n  if vertex_dataset is not None:\n    # of format\n    # projects/294348452381/locations/us-central1/datasets/7104764862735056896\n\
          \    dataset_name = vertex_dataset.metadata['resourceName']\n\n    aiplatform.init(project=project,\
          \ location=location)\n    client = aip.DatasetServiceClient(client_options={\n\
          \        'api_endpoint': f'{location}-aiplatform.googleapis.com'\n    })\n\
          \    dataset = client.get_dataset(name=dataset_name)\n    input_config =\
          \ dataset.metadata['inputConfig']\n    print(input_config)\n    if 'gcsSource'\
          \ in input_config:\n      data_source_csv_filenames = ','.join(input_config['gcsSource']['uri'])\n\
          \    elif 'bigquerySource' in input_config:\n      data_source_bigquery_table_path\
          \ = input_config['bigquerySource']['uri']\n  elif data_source_csv_filenames:\n\
          \    pass\n  elif data_source_bigquery_table_path:\n    pass\n  else:\n\
          \    raise ValueError(\n        'One of vertex_dataset, data_source_csv_filenames,'\n\
          \        ' data_source_bigquery_table_path must be specified'\n    )\n\n\
          \  return collections.namedtuple(\n      'Outputs',\n      ['data_source_csv_filenames',\
          \ 'data_source_bigquery_table_path'])(\n          data_source_csv_filenames,\
          \ data_source_bigquery_table_path)\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-importer:
      importer:
        artifactUri:
          runtimeParameter: uri
        typeSchema:
          schemaTitle: system.Artifact
          schemaVersion: 0.0.1
    exec-merge-materialized-splits:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _merge_materialized_splits
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _merge_materialized_splits(\n    split_0: dsl.InputPath('MaterializedSplit'),\n\
          \    split_1: dsl.InputPath('MaterializedSplit'),\n    splits: dsl.OutputPath('MaterializedSplit'),\n\
          ):\n  \"\"\"Merge two materialized splits.\n\n  Args:\n    split_0: The\
          \ first materialized split.\n    split_1: The second materialized split.\n\
          \    splits: The merged materialized split.\n  \"\"\"\n  with open(split_0,\
          \ 'r') as f:\n    split_0_content = f.read()\n  with open(split_1, 'r')\
          \ as f:\n    split_1_content = f.read()\n  with open(splits, 'w') as f:\n\
          \    f.write(','.join([split_0_content, split_1_content]))\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-model-batch-explanation:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\"", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - launcher
        image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
    exec-model-batch-explanation-2:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\"", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - launcher
        image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
    exec-model-batch-explanation-3:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\"", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - launcher
        image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
    exec-model-batch-predict:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-batch-predict-2:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-batch-predict-3:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-batch-predict-4:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-batch-predict-5:
      container:
        args:
        - --type
        - BatchPredictionJob
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}",
          "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}",
          "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}",
          "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}",
          "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}",
          ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}",
          "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}",
          "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}",
          "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\":
          \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\":
          \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\":
          ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\":
          ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\":
          ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\":
          {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}",
          "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}",
          ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\":
          {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-evaluation:
      container:
        args:
        - --setup_file
        - /setup.py
        - --json_mode
        - 'true'
        - --project_id
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --problem_type
        - '{{$.inputs.parameters[''problem_type'']}}'
        - --batch_prediction_format
        - '{{$.inputs.parameters[''predictions_format'']}}'
        - --batch_prediction_gcs_source
        - '{{$.inputs.artifacts[''batch_prediction_job''].metadata[''gcsOutputDirectory'']}}'
        - --ground_truth_format
        - '{{$.inputs.parameters[''ground_truth_format'']}}'
        - --key_prefix_in_prediction_dataset
        - instance
        - --root_dir
        - '{"Concat": ["{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}"]}'
        - --classification_type
        - multiclass
        - --ground_truth_column
        - instance.{{$.inputs.parameters['ground_truth_column']}}
        - --prediction_score_column
        - '{{$.inputs.parameters[''prediction_score_column'']}}'
        - --prediction_label_column
        - '{{$.inputs.parameters[''prediction_label_column'']}}'
        - --prediction_id_column
        - ''
        - --example_weight_column
        - ''
        - --generate_feature_attribution
        - 'false'
        - --dataflow_job_prefix
        - evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
        - --dataflow_service_account
        - '{{$.inputs.parameters[''dataflow_service_account'']}}'
        - --dataflow_disk_size
        - '{{$.inputs.parameters[''dataflow_disk_size'']}}'
        - --dataflow_machine_type
        - '{{$.inputs.parameters[''dataflow_machine_type'']}}'
        - --dataflow_workers_num
        - '{{$.inputs.parameters[''dataflow_workers_num'']}}'
        - --dataflow_max_workers_num
        - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}'
        - --dataflow_subnetwork
        - '{{$.inputs.parameters[''dataflow_subnetwork'']}}'
        - --dataflow_use_public_ips
        - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}'
        - --kms_key_name
        - '{{$.inputs.parameters[''encryption_spec_key_name'']}}'
        - --output_metrics_gcs_path
        - '{{$.outputs.artifacts[''evaluation_metrics''].uri}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python
        - /main.py
        image: gcr.io/ml-pipeline/model-evaluation:v0.4
    exec-model-evaluation-2:
      container:
        args:
        - --setup_file
        - /setup.py
        - --json_mode
        - 'true'
        - --project_id
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --problem_type
        - '{{$.inputs.parameters[''problem_type'']}}'
        - --batch_prediction_format
        - '{{$.inputs.parameters[''predictions_format'']}}'
        - --batch_prediction_gcs_source
        - '{{$.inputs.artifacts[''batch_prediction_job''].metadata[''gcsOutputDirectory'']}}'
        - --ground_truth_format
        - '{{$.inputs.parameters[''ground_truth_format'']}}'
        - --key_prefix_in_prediction_dataset
        - instance
        - --root_dir
        - '{"Concat": ["{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}"]}'
        - --classification_type
        - multiclass
        - --ground_truth_column
        - instance.{{$.inputs.parameters['ground_truth_column']}}
        - --prediction_score_column
        - '{{$.inputs.parameters[''prediction_score_column'']}}'
        - --prediction_label_column
        - '{{$.inputs.parameters[''prediction_label_column'']}}'
        - --prediction_id_column
        - ''
        - --example_weight_column
        - ''
        - --generate_feature_attribution
        - 'false'
        - --dataflow_job_prefix
        - evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
        - --dataflow_service_account
        - '{{$.inputs.parameters[''dataflow_service_account'']}}'
        - --dataflow_disk_size
        - '{{$.inputs.parameters[''dataflow_disk_size'']}}'
        - --dataflow_machine_type
        - '{{$.inputs.parameters[''dataflow_machine_type'']}}'
        - --dataflow_workers_num
        - '{{$.inputs.parameters[''dataflow_workers_num'']}}'
        - --dataflow_max_workers_num
        - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}'
        - --dataflow_subnetwork
        - '{{$.inputs.parameters[''dataflow_subnetwork'']}}'
        - --dataflow_use_public_ips
        - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}'
        - --kms_key_name
        - '{{$.inputs.parameters[''encryption_spec_key_name'']}}'
        - --output_metrics_gcs_path
        - '{{$.outputs.artifacts[''evaluation_metrics''].uri}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python
        - /main.py
        image: gcr.io/ml-pipeline/model-evaluation:v0.4
    exec-model-evaluation-3:
      container:
        args:
        - --setup_file
        - /setup.py
        - --json_mode
        - 'true'
        - --project_id
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --problem_type
        - '{{$.inputs.parameters[''problem_type'']}}'
        - --batch_prediction_format
        - '{{$.inputs.parameters[''predictions_format'']}}'
        - --batch_prediction_gcs_source
        - '{{$.inputs.artifacts[''batch_prediction_job''].metadata[''gcsOutputDirectory'']}}'
        - --ground_truth_format
        - '{{$.inputs.parameters[''ground_truth_format'']}}'
        - --key_prefix_in_prediction_dataset
        - instance
        - --root_dir
        - '{"Concat": ["{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}"]}'
        - --classification_type
        - multiclass
        - --ground_truth_column
        - instance.{{$.inputs.parameters['ground_truth_column']}}
        - --prediction_score_column
        - '{{$.inputs.parameters[''prediction_score_column'']}}'
        - --prediction_label_column
        - '{{$.inputs.parameters[''prediction_label_column'']}}'
        - --prediction_id_column
        - ''
        - --example_weight_column
        - ''
        - --generate_feature_attribution
        - 'false'
        - --dataflow_job_prefix
        - evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
        - --dataflow_service_account
        - '{{$.inputs.parameters[''dataflow_service_account'']}}'
        - --dataflow_disk_size
        - '{{$.inputs.parameters[''dataflow_disk_size'']}}'
        - --dataflow_machine_type
        - '{{$.inputs.parameters[''dataflow_machine_type'']}}'
        - --dataflow_workers_num
        - '{{$.inputs.parameters[''dataflow_workers_num'']}}'
        - --dataflow_max_workers_num
        - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}'
        - --dataflow_subnetwork
        - '{{$.inputs.parameters[''dataflow_subnetwork'']}}'
        - --dataflow_use_public_ips
        - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}'
        - --kms_key_name
        - '{{$.inputs.parameters[''encryption_spec_key_name'']}}'
        - --output_metrics_gcs_path
        - '{{$.outputs.artifacts[''evaluation_metrics''].uri}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python
        - /main.py
        image: gcr.io/ml-pipeline/model-evaluation:v0.4
    exec-model-evaluation-import:
      container:
        args:
        - --metrics
        - '{{$.inputs.artifacts[''metrics''].uri}}'
        - --metrics_explanation
        - '{{$.inputs.artifacts[''metrics''].metadata[''explanation_gcs_path'']}}'
        - --feature_attributions
        - '{{$.inputs.artifacts[''feature_attributions''].uri}}'
        - --problem_type
        - '{{$.inputs.parameters[''problem_type'']}}'
        - --display_name
        - '{{$.inputs.parameters[''display_name'']}}'
        - --dataset_paths
        - '{{$.inputs.parameters[''dataset_paths'']}}'
        - --dataset_type
        - '{{$.inputs.parameters[''dataset_type'']}}'
        - --pipeline_job_id
        - '{{$.pipeline_job_uuid}}'
        - --pipeline_job_resource_name
        - '{{$.pipeline_job_resource_name}}'
        - --model_name
        - '{{$.inputs.artifacts[''model''].metadata[''resourceName'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.experimental.evaluation.import_model_evaluation
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-evaluation-import-2:
      container:
        args:
        - --metrics
        - '{{$.inputs.artifacts[''metrics''].uri}}'
        - --metrics_explanation
        - '{{$.inputs.artifacts[''metrics''].metadata[''explanation_gcs_path'']}}'
        - --feature_attributions
        - '{{$.inputs.artifacts[''feature_attributions''].uri}}'
        - --problem_type
        - '{{$.inputs.parameters[''problem_type'']}}'
        - --display_name
        - '{{$.inputs.parameters[''display_name'']}}'
        - --dataset_paths
        - '{{$.inputs.parameters[''dataset_paths'']}}'
        - --dataset_type
        - '{{$.inputs.parameters[''dataset_type'']}}'
        - --pipeline_job_id
        - '{{$.pipeline_job_uuid}}'
        - --pipeline_job_resource_name
        - '{{$.pipeline_job_resource_name}}'
        - --model_name
        - '{{$.inputs.artifacts[''model''].metadata[''resourceName'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.experimental.evaluation.import_model_evaluation
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-evaluation-import-3:
      container:
        args:
        - --metrics
        - '{{$.inputs.artifacts[''metrics''].uri}}'
        - --metrics_explanation
        - '{{$.inputs.artifacts[''metrics''].metadata[''explanation_gcs_path'']}}'
        - --feature_attributions
        - '{{$.inputs.artifacts[''feature_attributions''].uri}}'
        - --problem_type
        - '{{$.inputs.parameters[''problem_type'']}}'
        - --display_name
        - '{{$.inputs.parameters[''display_name'']}}'
        - --dataset_paths
        - '{{$.inputs.parameters[''dataset_paths'']}}'
        - --dataset_type
        - '{{$.inputs.parameters[''dataset_type'']}}'
        - --pipeline_job_id
        - '{{$.pipeline_job_uuid}}'
        - --pipeline_job_resource_name
        - '{{$.pipeline_job_resource_name}}'
        - --model_name
        - '{{$.inputs.artifacts[''model''].metadata[''resourceName'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.experimental.evaluation.import_model_evaluation
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-model-upload:
      container:
        args:
        - --type
        - UploadModel
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''display_name'']}}",
          "\"", ", \"description\": \"", "{{$.inputs.parameters[''description'']}}",
          "\"", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\"", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - launcher
        image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
    exec-model-upload-2:
      container:
        args:
        - --type
        - UploadModel
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''display_name'']}}",
          "\"", ", \"description\": \"", "{{$.inputs.parameters[''description'']}}",
          "\"", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\"", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - launcher
        image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
    exec-model-upload-3:
      container:
        args:
        - --type
        - UploadModel
        - --payload
        - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''display_name'']}}",
          "\"", ", \"description\": \"", "{{$.inputs.parameters[''description'']}}",
          "\"", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}",
          ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}",
          "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}",
          "\"", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", "}"]}'
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --executor_input
        - '{{$}}'
        command:
        - python3
        - -u
        - -m
        - launcher
        image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
    exec-read-input-uri:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _read_input_uri
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _read_input_uri(split_uri: dsl.InputPath('Dataset')) -> list:\
          \  # Required by KFP; pylint:disable=g-bare-generic\n  \"\"\"Construct Dataset\
          \ based on the batch prediction job.\n\n  Args:\n    split_uri: Tbe path\
          \ to the file that contains Dataset data.\n\n  Returns:\n    The list of\
          \ string that represents the batch prediction input files.\n  \"\"\"\n \
          \ # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  import json\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  with open(split_uri, 'r') as f:\n    data_source = json.loads(f.read())\n\
          \    return data_source['tf_record_data_source']['file_patterns']\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-read-input-uri-2:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _read_input_uri
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _read_input_uri(split_uri: dsl.InputPath('Dataset')) -> list:\
          \  # Required by KFP; pylint:disable=g-bare-generic\n  \"\"\"Construct Dataset\
          \ based on the batch prediction job.\n\n  Args:\n    split_uri: Tbe path\
          \ to the file that contains Dataset data.\n\n  Returns:\n    The list of\
          \ string that represents the batch prediction input files.\n  \"\"\"\n \
          \ # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  import json\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  with open(split_uri, 'r') as f:\n    data_source = json.loads(f.read())\n\
          \    return data_source['tf_record_data_source']['file_patterns']\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-string-not-empty:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _string_not_empty
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _string_not_empty(value: str) -> str:\n  \"\"\"Check if the input\
          \ string value is not empty.\n\n  Args:\n    value: String value to be checked.\n\
          \n  Returns:\n    Boolean value. -> 'true' if empty, 'false' if not empty.\
          \ We need to use str\n    instead of bool due to a limitation in KFP compiler.\n\
          \  \"\"\"\n  return 'true' if value else 'false'\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-tabular-stats-and-example-gen:
      container:
        args:
        - --type
        - CustomJob
        - --project
        - '{{$.inputs.parameters[''project'']}}'
        - --location
        - '{{$.inputs.parameters[''location'']}}'
        - --gcp_resources
        - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
        - --payload
        - '{"Concat": ["{\"display_name\": \"tabular-stats-and-example-gen-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\",
          \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\":
          {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"",
          "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\",
          \"args\": [\"stats_generator\",", "\"--train_spec={\\\"prediction_type\\\":
          \\\"", "{{$.inputs.parameters[''prediction_type'']}}", "\\\", \\\"target_column\\\":
          \\\"", "{{$.inputs.parameters[''target_column_name'']}}", "\\\", \\\"optimization_objective\\\":
          \\\"", "{{$.inputs.parameters[''optimization_objective'']}}", "\\\", \\\"weight_column_name\\\":
          \\\"", "{{$.inputs.parameters[''weight_column_name'']}}", "\\\", \\\"transformations\\\":
          ", "{{$.inputs.parameters[''transformations'']}}", ", \\\"quantiles\\\":
          ", "{{$.inputs.parameters[''quantiles'']}}", ", \\\"enable_probabilistic_inference\\\":
          ", "{{$.inputs.parameters[''enable_probabilistic_inference'']}}", "}\",
          \"--transformations_override_path=", "{{$.inputs.parameters[''transformations_path'']}}",
          "\", \"--data_source_csv_filenames=", "{{$.inputs.parameters[''data_source_csv_filenames'']}}",
          "\", \"--data_source_bigquery_table_path=", "{{$.inputs.parameters[''data_source_bigquery_table_path'']}}",
          "\", \"--predefined_split_key=", "{{$.inputs.parameters[''predefined_split_key'']}}",
          "\", \"--timestamp_split_key=", "{{$.inputs.parameters[''timestamp_split_key'']}}",
          "\", \"--stratified_split_key=", "{{$.inputs.parameters[''stratified_split_key'']}}",
          "\", \"--training_fraction=", "{{$.inputs.parameters[''training_fraction'']}}",
          "\", \"--validation_fraction=", "{{$.inputs.parameters[''validation_fraction'']}}",
          "\", \"--test_fraction=", "{{$.inputs.parameters[''test_fraction'']}}",
          "\", \"--target_column=", "{{$.inputs.parameters[''target_column_name'']}}",
          "\", \"--request_type=", "{{$.inputs.parameters[''request_type'']}}", "\",
          \"--optimization_objective_recall_value=", "{{$.inputs.parameters[''optimization_objective_recall_value'']}}",
          "\", \"--optimization_objective_precision_value=", "{{$.inputs.parameters[''optimization_objective_precision_value'']}}",
          "\", \"--example_gen_gcs_output_prefix=", "{{$.inputs.parameters[''root_dir'']}}",
          "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/example_gen_output\",
          \"--dataset_stats_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/stats/\",
          \"--stats_result_path=", "{{$.outputs.artifacts[''dataset_stats''].uri}}",
          "\", \"--dataset_schema_path=", "{{$.outputs.artifacts[''dataset_schema''].uri}}",
          "\", \"--job_name=tabular-stats-and-example-gen-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
          "\", \"--dataflow_project=", "{{$.inputs.parameters[''project'']}}", "\",
          \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\",
          \"--dataflow_staging_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_staging\",
          \"--dataflow_tmp_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_tmp\",
          \"--dataflow_max_num_workers=", "{{$.inputs.parameters[''dataflow_max_num_workers'']}}",
          "\", \"--dataflow_worker_container_image=", "us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:dev",
          "\", \"--dataflow_machine_type=", "{{$.inputs.parameters[''dataflow_machine_type'']}}",
          "\", \"--dataflow_disk_size_gb=", "{{$.inputs.parameters[''dataflow_disk_size_gb'']}}",
          "\", \"--dataflow_kms_key=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}",
          "\", \"--dataflow_subnetwork_fully_qualified=", "{{$.inputs.parameters[''dataflow_subnetwork'']}}",
          "\", \"--dataflow_use_public_ips=", "{{$.inputs.parameters[''dataflow_use_public_ips'']}}",
          "\", \"--dataflow_service_account=", "{{$.inputs.parameters[''dataflow_service_account'']}}",
          "\", \"--is_distill=", "{{$.inputs.parameters[''run_distillation'']}}",
          "\", \"--additional_experiments=", "{{$.inputs.parameters[''additional_experiments'']}}",
          "\", \"--metadata_path=", "{{$.outputs.artifacts[''metadata''].uri}}", "\",
          \"--train_split=", "{{$.outputs.artifacts[''train_split''].uri}}", "\",
          \"--eval_split=", "{{$.outputs.artifacts[''eval_split''].uri}}", "\", \"--test_split=",
          "{{$.outputs.artifacts[''test_split''].uri}}", "\", \"--test_split_for_batch_prediction_component=",
          "{{$.outputs.parameters[''test_split_json''].output_file}}", "\", \"--downsampled_test_split_for_batch_prediction_component=",
          "{{$.outputs.parameters[''downsampled_test_split_json''].output_file}}",
          "\", \"--instance_baseline_path=", "{{$.outputs.artifacts[''instance_baseline''].uri}}",
          "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\",
          \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}",
          "\", \"--parse_json=true\", \"--generate_additional_downsample_test_split=true\",
          \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}'
        command:
        - python3
        - -u
        - -m
        - google_cloud_pipeline_components.container.v1.custom_job.launcher
        image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
    exec-write-bp-result-path:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _write_bp_result_path
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _write_bp_result_path(\n    bp_job: Input[Artifact],\n    result:\
          \ OutputPath('Dataset'),\n):\n  \"\"\"Construct Dataset based on the batch\
          \ prediction job.\n\n  Args:\n    bp_job: The batch prediction job artifact.\n\
          \    result: Tbe path to the file that contains Dataset data.\n  \"\"\"\n\
          \  # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  import json\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  directory = bp_job.metadata['gcsOutputDirectory']\n  data_source = {\n\
          \      'tf_record_data_source': {\n          'file_patterns': [f'{directory}/prediction.results-*',],\n\
          \          'coder': 'PROTO_VALUE',\n      },\n  }\n  with open(result, 'w')\
          \ as f:\n    f.write(json.dumps(data_source))\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
    exec-write-bp-result-path-2:
      container:
        args:
        - --executor_input
        - '{{$}}'
        - --function_to_execute
        - _write_bp_result_path
        command:
        - sh
        - -ec
        - 'program_path=$(mktemp -d)

          printf "%s" "$0" > "$program_path/ephemeral_component.py"

          python3 -m kfp.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

          '
        - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\
          \ *\n\ndef _write_bp_result_path(\n    bp_job: Input[Artifact],\n    result:\
          \ OutputPath('Dataset'),\n):\n  \"\"\"Construct Dataset based on the batch\
          \ prediction job.\n\n  Args:\n    bp_job: The batch prediction job artifact.\n\
          \    result: Tbe path to the file that contains Dataset data.\n  \"\"\"\n\
          \  # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  import json\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
          \  directory = bp_job.metadata['gcsOutputDirectory']\n  data_source = {\n\
          \      'tf_record_data_source': {\n          'file_patterns': [f'{directory}/prediction.results-*',],\n\
          \          'coder': 'PROTO_VALUE',\n      },\n  }\n  with open(result, 'w')\
          \ as f:\n    f.write(json.dumps(data_source))\n\n"
        image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev
pipelineInfo:
  name: automl-tabular
root:
  dag:
    outputs:
      artifacts:
        feature-attribution-2-feature_attributions:
          artifactSelectors:
          - outputArtifactKey: feature-attribution-2-feature_attributions
            producerSubtask: exit-handler-1
        feature-attribution-3-feature_attributions:
          artifactSelectors:
          - outputArtifactKey: feature-attribution-3-feature_attributions
            producerSubtask: exit-handler-1
        feature-attribution-feature_attributions:
          artifactSelectors:
          - outputArtifactKey: feature-attribution-feature_attributions
            producerSubtask: exit-handler-1
        model-evaluation-2-evaluation_metrics:
          artifactSelectors:
          - outputArtifactKey: model-evaluation-2-evaluation_metrics
            producerSubtask: exit-handler-1
        model-evaluation-3-evaluation_metrics:
          artifactSelectors:
          - outputArtifactKey: model-evaluation-3-evaluation_metrics
            producerSubtask: exit-handler-1
        model-evaluation-evaluation_metrics:
          artifactSelectors:
          - outputArtifactKey: model-evaluation-evaluation_metrics
            producerSubtask: exit-handler-1
    tasks:
      automl-tabular-finalizer:
        cachingOptions:
          enableCache: true
        componentRef:
          name: comp-automl-tabular-finalizer
        dependentTasks:
        - exit-handler-1
        inputs:
          parameters:
            location:
              componentInputParameter: location
            project:
              componentInputParameter: project
            root_dir:
              componentInputParameter: root_dir
        taskInfo:
          name: automl-tabular-finalizer
        triggerPolicy:
          strategy: ALL_UPSTREAM_TASKS_COMPLETED
      exit-handler-1:
        componentRef:
          name: comp-exit-handler-1
        dependentTasks:
        - get-data-source-uri
        inputs:
          parameters:
            pipelinechannel--additional_experiments:
              componentInputParameter: additional_experiments
            pipelinechannel--cv_trainer_worker_pool_specs_override:
              componentInputParameter: cv_trainer_worker_pool_specs_override
            pipelinechannel--dataflow_service_account:
              componentInputParameter: dataflow_service_account
            pipelinechannel--dataflow_subnetwork:
              componentInputParameter: dataflow_subnetwork
            pipelinechannel--dataflow_use_public_ips:
              componentInputParameter: dataflow_use_public_ips
            pipelinechannel--disable_early_stopping:
              componentInputParameter: disable_early_stopping
            pipelinechannel--distill_batch_predict_machine_type:
              componentInputParameter: distill_batch_predict_machine_type
            pipelinechannel--distill_batch_predict_max_replica_count:
              componentInputParameter: distill_batch_predict_max_replica_count
            pipelinechannel--distill_batch_predict_starting_replica_count:
              componentInputParameter: distill_batch_predict_starting_replica_count
            pipelinechannel--enable_probabilistic_inference:
              componentInputParameter: enable_probabilistic_inference
            pipelinechannel--encryption_spec_key_name:
              componentInputParameter: encryption_spec_key_name
            pipelinechannel--evaluation_batch_predict_machine_type:
              componentInputParameter: evaluation_batch_predict_machine_type
            pipelinechannel--evaluation_batch_predict_max_replica_count:
              componentInputParameter: evaluation_batch_predict_max_replica_count
            pipelinechannel--evaluation_batch_predict_starting_replica_count:
              componentInputParameter: evaluation_batch_predict_starting_replica_count
            pipelinechannel--evaluation_dataflow_disk_size_gb:
              componentInputParameter: evaluation_dataflow_disk_size_gb
            pipelinechannel--evaluation_dataflow_machine_type:
              componentInputParameter: evaluation_dataflow_machine_type
            pipelinechannel--evaluation_dataflow_max_num_workers:
              componentInputParameter: evaluation_dataflow_max_num_workers
            pipelinechannel--export_additional_model_without_custom_ops:
              componentInputParameter: export_additional_model_without_custom_ops
            pipelinechannel--fast_testing:
              componentInputParameter: fast_testing
            pipelinechannel--get-data-source-uri-data_source_bigquery_table_path:
              taskOutputParameter:
                outputParameterKey: data_source_bigquery_table_path
                producerTask: get-data-source-uri
            pipelinechannel--get-data-source-uri-data_source_csv_filenames:
              taskOutputParameter:
                outputParameterKey: data_source_csv_filenames
                producerTask: get-data-source-uri
            pipelinechannel--location:
              componentInputParameter: location
            pipelinechannel--model_description:
              componentInputParameter: model_description
            pipelinechannel--model_display_name:
              componentInputParameter: model_display_name
            pipelinechannel--optimization_objective:
              componentInputParameter: optimization_objective
            pipelinechannel--optimization_objective_precision_value:
              componentInputParameter: optimization_objective_precision_value
            pipelinechannel--optimization_objective_recall_value:
              componentInputParameter: optimization_objective_recall_value
            pipelinechannel--predefined_split_key:
              componentInputParameter: predefined_split_key
            pipelinechannel--prediction_type:
              componentInputParameter: prediction_type
            pipelinechannel--project:
              componentInputParameter: project
            pipelinechannel--quantiles:
              componentInputParameter: quantiles
            pipelinechannel--root_dir:
              componentInputParameter: root_dir
            pipelinechannel--run_distillation:
              componentInputParameter: run_distillation
            pipelinechannel--run_evaluation:
              componentInputParameter: run_evaluation
            pipelinechannel--stage_1_num_parallel_trials:
              componentInputParameter: stage_1_num_parallel_trials
            pipelinechannel--stage_1_tuner_worker_pool_specs_override:
              componentInputParameter: stage_1_tuner_worker_pool_specs_override
            pipelinechannel--stage_1_tuning_result_artifact_uri:
              componentInputParameter: stage_1_tuning_result_artifact_uri
            pipelinechannel--stage_2_num_parallel_trials:
              componentInputParameter: stage_2_num_parallel_trials
            pipelinechannel--stage_2_num_selected_trials:
              componentInputParameter: stage_2_num_selected_trials
            pipelinechannel--stats_and_example_gen_dataflow_disk_size_gb:
              componentInputParameter: stats_and_example_gen_dataflow_disk_size_gb
            pipelinechannel--stats_and_example_gen_dataflow_machine_type:
              componentInputParameter: stats_and_example_gen_dataflow_machine_type
            pipelinechannel--stats_and_example_gen_dataflow_max_num_workers:
              componentInputParameter: stats_and_example_gen_dataflow_max_num_workers
            pipelinechannel--stratified_split_key:
              componentInputParameter: stratified_split_key
            pipelinechannel--study_spec_parameters_override:
              componentInputParameter: study_spec_parameters_override
            pipelinechannel--target_column:
              componentInputParameter: target_column
            pipelinechannel--test_fraction:
              componentInputParameter: test_fraction
            pipelinechannel--timestamp_split_key:
              componentInputParameter: timestamp_split_key
            pipelinechannel--train_budget_milli_node_hours:
              componentInputParameter: train_budget_milli_node_hours
            pipelinechannel--training_fraction:
              componentInputParameter: training_fraction
            pipelinechannel--transform_dataflow_disk_size_gb:
              componentInputParameter: transform_dataflow_disk_size_gb
            pipelinechannel--transform_dataflow_machine_type:
              componentInputParameter: transform_dataflow_machine_type
            pipelinechannel--transform_dataflow_max_num_workers:
              componentInputParameter: transform_dataflow_max_num_workers
            pipelinechannel--transformations:
              componentInputParameter: transformations
            pipelinechannel--validation_fraction:
              componentInputParameter: validation_fraction
            pipelinechannel--weight_column:
              componentInputParameter: weight_column
        taskInfo:
          name: exit-handler-1
      get-data-source-uri:
        cachingOptions:
          enableCache: true
        componentRef:
          name: comp-get-data-source-uri
        inputs:
          artifacts:
            vertex_dataset:
              componentInputArtifact: vertex_dataset
          parameters:
            data_source_bigquery_table_path:
              componentInputParameter: data_source_bigquery_table_path
            data_source_csv_filenames:
              componentInputParameter: data_source_csv_filenames
            location:
              componentInputParameter: location
            project:
              componentInputParameter: project
        taskInfo:
          name: get-data-source-uri
  inputDefinitions:
    artifacts:
      vertex_dataset:
        artifactType:
          schemaTitle: system.Artifact
          schemaVersion: 0.0.1
    parameters:
      additional_experiments:
        parameterType: STRUCT
      cv_trainer_worker_pool_specs_override:
        parameterType: LIST
      data_source_bigquery_table_path:
        defaultValue: ''
        parameterType: STRING
      data_source_csv_filenames:
        defaultValue: ''
        parameterType: STRING
      dataflow_service_account:
        defaultValue: ''
        parameterType: STRING
      dataflow_subnetwork:
        defaultValue: ''
        parameterType: STRING
      dataflow_use_public_ips:
        defaultValue: 1.0
        parameterType: BOOLEAN
      disable_early_stopping:
        defaultValue: 0.0
        parameterType: BOOLEAN
      distill_batch_predict_machine_type:
        defaultValue: n1-standard-16
        parameterType: STRING
      distill_batch_predict_max_replica_count:
        defaultValue: 25.0
        parameterType: NUMBER_INTEGER
      distill_batch_predict_starting_replica_count:
        defaultValue: 25.0
        parameterType: NUMBER_INTEGER
      enable_probabilistic_inference:
        defaultValue: 0.0
        parameterType: BOOLEAN
      encryption_spec_key_name:
        defaultValue: ''
        parameterType: STRING
      evaluation_batch_predict_machine_type:
        defaultValue: n1-standard-16
        parameterType: STRING
      evaluation_batch_predict_max_replica_count:
        defaultValue: 25.0
        parameterType: NUMBER_INTEGER
      evaluation_batch_predict_starting_replica_count:
        defaultValue: 25.0
        parameterType: NUMBER_INTEGER
      evaluation_dataflow_disk_size_gb:
        defaultValue: 50.0
        parameterType: NUMBER_INTEGER
      evaluation_dataflow_machine_type:
        defaultValue: n1-standard-4
        parameterType: STRING
      evaluation_dataflow_max_num_workers:
        defaultValue: 25.0
        parameterType: NUMBER_INTEGER
      export_additional_model_without_custom_ops:
        defaultValue: 0.0
        parameterType: BOOLEAN
      fast_testing:
        defaultValue: 0.0
        parameterType: BOOLEAN
      location:
        parameterType: STRING
      model_description:
        defaultValue: ''
        parameterType: STRING
      model_display_name:
        defaultValue: ''
        parameterType: STRING
      optimization_objective:
        parameterType: STRING
      optimization_objective_precision_value:
        defaultValue: -1.0
        parameterType: NUMBER_DOUBLE
      optimization_objective_recall_value:
        defaultValue: -1.0
        parameterType: NUMBER_DOUBLE
      predefined_split_key:
        defaultValue: ''
        parameterType: STRING
      prediction_type:
        parameterType: STRING
      project:
        parameterType: STRING
      quantiles:
        parameterType: LIST
      root_dir:
        parameterType: STRING
      run_distillation:
        defaultValue: 0.0
        parameterType: BOOLEAN
      run_evaluation:
        defaultValue: 0.0
        parameterType: BOOLEAN
      stage_1_num_parallel_trials:
        defaultValue: 35.0
        parameterType: NUMBER_INTEGER
      stage_1_tuner_worker_pool_specs_override:
        parameterType: LIST
      stage_1_tuning_result_artifact_uri:
        defaultValue: ''
        parameterType: STRING
      stage_2_num_parallel_trials:
        defaultValue: 35.0
        parameterType: NUMBER_INTEGER
      stage_2_num_selected_trials:
        defaultValue: 5.0
        parameterType: NUMBER_INTEGER
      stats_and_example_gen_dataflow_disk_size_gb:
        defaultValue: 40.0
        parameterType: NUMBER_INTEGER
      stats_and_example_gen_dataflow_machine_type:
        defaultValue: n1-standard-16
        parameterType: STRING
      stats_and_example_gen_dataflow_max_num_workers:
        defaultValue: 25.0
        parameterType: NUMBER_INTEGER
      stratified_split_key:
        defaultValue: ''
        parameterType: STRING
      study_spec_parameters_override:
        parameterType: LIST
      target_column:
        parameterType: STRING
      test_fraction:
        defaultValue: -1.0
        parameterType: NUMBER_DOUBLE
      timestamp_split_key:
        defaultValue: ''
        parameterType: STRING
      train_budget_milli_node_hours:
        parameterType: NUMBER_DOUBLE
      training_fraction:
        defaultValue: -1.0
        parameterType: NUMBER_DOUBLE
      transform_dataflow_disk_size_gb:
        defaultValue: 40.0
        parameterType: NUMBER_INTEGER
      transform_dataflow_machine_type:
        defaultValue: n1-standard-16
        parameterType: STRING
      transform_dataflow_max_num_workers:
        defaultValue: 25.0
        parameterType: NUMBER_INTEGER
      transformations:
        parameterType: STRING
      validation_fraction:
        defaultValue: -1.0
        parameterType: NUMBER_DOUBLE
      weight_column:
        defaultValue: ''
        parameterType: STRING
  outputDefinitions:
    artifacts:
      feature-attribution-2-feature_attributions:
        artifactType:
          schemaTitle: system.Metrics
          schemaVersion: 0.0.1
      feature-attribution-3-feature_attributions:
        artifactType:
          schemaTitle: system.Metrics
          schemaVersion: 0.0.1
      feature-attribution-feature_attributions:
        artifactType:
          schemaTitle: system.Metrics
          schemaVersion: 0.0.1
      model-evaluation-2-evaluation_metrics:
        artifactType:
          schemaTitle: system.Metrics
          schemaVersion: 0.0.1
      model-evaluation-3-evaluation_metrics:
        artifactType:
          schemaTitle: system.Metrics
          schemaVersion: 0.0.1
      model-evaluation-evaluation_metrics:
        artifactType:
          schemaTitle: system.Metrics
          schemaVersion: 0.0.1
schemaVersion: 2.1.0
sdkVersion: kfp-2.0.0-beta.4
