config.yaml

# 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.

pipelineSpec:
  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:
            type: DOUBLE
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          num_parallel_trials:
            type: INT
          num_selected_trials:
            type: INT
          project:
            type: STRING
          root_dir:
            type: STRING
          single_run_max_secs:
            type: INT
          worker_pool_specs_override_json:
            type: STRING
      outputDefinitions:
        artifacts:
          tuning_result_output:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
        parameters:
          execution_metrics:
            type: STRING
          gcp_resources:
            type: 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:
            type: DOUBLE
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          num_parallel_trials:
            type: INT
          num_selected_trials:
            type: INT
          project:
            type: STRING
          root_dir:
            type: STRING
          single_run_max_secs:
            type: INT
          worker_pool_specs_override_json:
            type: STRING
      outputDefinitions:
        artifacts:
          tuning_result_output:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
        parameters:
          execution_metrics:
            type: STRING
          gcp_resources:
            type: 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:
            type: STRING
          export_additional_model_without_custom_ops:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: 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:
            type: STRING
          explanation_parameters:
            type: STRING
          gcp_resources:
            type: 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:
            type: STRING
          export_additional_model_without_custom_ops:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: 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:
            type: STRING
          explanation_parameters:
            type: STRING
          gcp_resources:
            type: 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:
            type: STRING
          export_additional_model_without_custom_ops:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: 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:
            type: STRING
          explanation_parameters:
            type: STRING
          gcp_resources:
            type: STRING
    comp-automl-tabular-finalizer:
      executorLabel: exec-automl-tabular-finalizer
      inputDefinitions:
        parameters:
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: STRING
      outputDefinitions:
        parameters:
          gcp_resources:
            type: 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:
            type: DOUBLE
          disable_early_stopping:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          num_parallel_trials:
            type: INT
          num_selected_trials:
            type: INT
          project:
            type: STRING
          reduce_search_space_mode:
            type: STRING
          root_dir:
            type: STRING
          run_distillation:
            type: STRING
          single_run_max_secs:
            type: INT
          study_spec_parameters_override:
            type: STRING
          tune_feature_selection_rate:
            type: STRING
          worker_pool_specs_override_json:
            type: STRING
      outputDefinitions:
        artifacts:
          tuning_result_output:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
        parameters:
          execution_metrics:
            type: STRING
          gcp_resources:
            type: 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:
            type: DOUBLE
          disable_early_stopping:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          num_parallel_trials:
            type: INT
          num_selected_trials:
            type: INT
          project:
            type: STRING
          reduce_search_space_mode:
            type: STRING
          root_dir:
            type: STRING
          run_distillation:
            type: STRING
          single_run_max_secs:
            type: INT
          study_spec_parameters_override:
            type: STRING
          tune_feature_selection_rate:
            type: STRING
          worker_pool_specs_override_json:
            type: STRING
      outputDefinitions:
        artifacts:
          tuning_result_output:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
        parameters:
          execution_metrics:
            type: STRING
          gcp_resources:
            type: 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:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_num_workers:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: 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:
            type: 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:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_num_workers:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: 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:
            type: STRING
    comp-bool-identity:
      executorLabel: exec-bool-identity
      inputDefinitions:
        parameters:
          value:
            type: STRING
      outputDefinitions:
        parameters:
          Output:
            type: STRING
    comp-bool-identity-2:
      executorLabel: exec-bool-identity-2
      inputDefinitions:
        parameters:
          value:
            type: STRING
      outputDefinitions:
        parameters:
          Output:
            type: STRING
    comp-bool-identity-3:
      executorLabel: exec-bool-identity-3
      inputDefinitions:
        parameters:
          value:
            type: STRING
      outputDefinitions:
        parameters:
          Output:
            type: STRING
    comp-calculate-training-parameters:
      executorLabel: exec-calculate-training-parameters
      inputDefinitions:
        parameters:
          fast_testing:
            type: STRING
          is_skip_architecture_search:
            type: STRING
          run_distillation:
            type: STRING
          stage_1_num_parallel_trials:
            type: INT
          stage_2_num_parallel_trials:
            type: INT
          train_budget_milli_node_hours:
            type: DOUBLE
      outputDefinitions:
        parameters:
          distill_stage_1_deadline_hours:
            type: DOUBLE
          reduce_search_space_mode:
            type: STRING
          stage_1_deadline_hours:
            type: DOUBLE
          stage_1_num_selected_trials:
            type: INT
          stage_1_single_run_max_secs:
            type: INT
          stage_2_deadline_hours:
            type: DOUBLE
          stage_2_single_run_max_secs:
            type: INT
    comp-calculate-training-parameters-2:
      executorLabel: exec-calculate-training-parameters-2
      inputDefinitions:
        parameters:
          fast_testing:
            type: STRING
          is_skip_architecture_search:
            type: STRING
          run_distillation:
            type: STRING
          stage_1_num_parallel_trials:
            type: INT
          stage_2_num_parallel_trials:
            type: INT
          train_budget_milli_node_hours:
            type: DOUBLE
      outputDefinitions:
        parameters:
          distill_stage_1_deadline_hours:
            type: DOUBLE
          reduce_search_space_mode:
            type: STRING
          stage_1_deadline_hours:
            type: DOUBLE
          stage_1_num_selected_trials:
            type: INT
          stage_1_single_run_max_secs:
            type: INT
          stage_2_deadline_hours:
            type: DOUBLE
          stage_2_single_run_max_secs:
            type: INT
    comp-condition-is-distill-7:
      dag:
        outputs:
          artifacts:
            feature-attribution-3-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-3-feature_attributions
                producerSubtask: condition-is-evaluation-8
            model-evaluation-3-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-3-evaluation_metrics
                producerSubtask: condition-is-evaluation-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: pipelineparam--tabular-stats-and-example-gen-dataset_schema
                instance_baseline:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-instance_baseline
                metadata:
                  componentInputArtifact: pipelineparam--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: pipelineparam--tabular-stats-and-example-gen-eval_split
              parameters:
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                export_additional_model_without_custom_ops:
                  componentInputParameter: pipelineparam--export_additional_model_without_custom_ops
                location:
                  componentInputParameter: pipelineparam--location
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--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: pipelineparam--tabular-stats-and-example-gen-metadata
                transform_output:
                  taskOutputArtifact:
                    outputArtifactKey: transform_output
                    producerTask: automl-tabular-transform-2
              parameters:
                deadline_hours:
                  componentInputParameter: pipelineparam--calculate-training-parameters-2-distill_stage_1_deadline_hours
                disable_early_stopping:
                  componentInputParameter: pipelineparam--disable_early_stopping
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_1_num_parallel_trials
                num_selected_trials:
                  runtimeValue:
                    constantValue:
                      intValue: '1'
                project:
                  componentInputParameter: pipelineparam--project
                reduce_search_space_mode:
                  componentInputParameter: pipelineparam--calculate-training-parameters-2-reduce_search_space_mode
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
                run_distillation:
                  runtimeValue:
                    constantValue:
                      intValue: '1'
                single_run_max_secs:
                  componentInputParameter: pipelineparam--calculate-training-parameters-2-stage_1_single_run_max_secs
                study_spec_parameters_override:
                  runtimeValue:
                    constantValue:
                      stringValue: '[]'
                tune_feature_selection_rate:
                  runtimeValue:
                    constantValue:
                      stringValue: 'false'
                worker_pool_specs_override_json:
                  componentInputParameter: pipelineparam--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: pipelineparam--tabular-stats-and-example-gen-dataset_schema
                eval_split:
                  taskOutputArtifact:
                    outputArtifactKey: result
                    producerTask: write-bp-result-path-2
                metadata:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-metadata
                test_split:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-test_split
                train_split:
                  taskOutputArtifact:
                    outputArtifactKey: result
                    producerTask: write-bp-result-path
              parameters:
                dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--transform_dataflow_disk_size_gb
                dataflow_machine_type:
                  componentInputParameter: pipelineparam--transform_dataflow_machine_type
                dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--transform_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                dataflow_subnetwork:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                dataflow_use_public_ips:
                  runtimeValue:
                    constantValue:
                      stringValue: 'true'
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
            taskInfo:
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            componentRef:
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            dependentTasks:
            - automl-tabular-ensemble-3
            - model-upload-4
            inputs:
              artifacts:
                pipelineparam--automl-tabular-ensemble-3-explanation_metadata_artifact:
                  taskOutputArtifact:
                    outputArtifactKey: explanation_metadata_artifact
                    producerTask: automl-tabular-ensemble-3
                pipelineparam--automl-tabular-ensemble-3-unmanaged_container_model:
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                    outputArtifactKey: unmanaged_container_model
                    producerTask: automl-tabular-ensemble-3
                pipelineparam--model-upload-4-model:
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                    producerTask: model-upload-4
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                    producerTask: automl-tabular-ensemble-3
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                pipelineparam--bool-identity-3-Output:
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                pipelineparam--dataflow_service_account:
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                pipelineparam--dataflow_subnetwork:
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                pipelineparam--dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                pipelineparam--encryption_spec_key_name:
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                pipelineparam--evaluation_batch_predict_machine_type:
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                pipelineparam--evaluation_batch_predict_max_replica_count:
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                pipelineparam--evaluation_batch_predict_starting_replica_count:
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                pipelineparam--evaluation_dataflow_max_num_workers:
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                pipelineparam--location:
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                pipelineparam--prediction_type:
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                pipelineparam--project:
                  componentInputParameter: pipelineparam--project
                pipelineparam--root_dir:
                  componentInputParameter: pipelineparam--root_dir
                pipelineparam--string-not-empty-Output:
                  componentInputParameter: pipelineparam--string-not-empty-Output
                pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
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                pipelineparam--tabular-stats-and-example-gen-test_split_json:
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            componentRef:
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            dependentTasks:
            - model-upload-3
            - read-input-uri
            inputs:
              artifacts:
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                  taskOutputArtifact:
                    outputArtifactKey: model
                    producerTask: model-upload-3
              parameters:
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                  runtimeValue:
                    constantValue:
                      intValue: '0'
                accelerator_type:
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                    constantValue:
                      stringValue: ''
                bigquery_destination_output_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_source_input_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                encryption_spec_key_name:
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                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
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                    constantValue:
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                      intValue: '0'
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                    constantValue:
                      stringValue: tf-record
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                    constantValue:
                      stringValue: batch-predict-train-split
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                    constantValue:
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                    constantValue:
                      stringValue: '{}'
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                    constantValue:
                      stringValue: tf-record
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            componentRef:
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            dependentTasks:
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            - read-input-uri-2
            inputs:
              artifacts:
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                    producerTask: model-upload-3
              parameters:
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                    constantValue:
                      intValue: '0'
                accelerator_type:
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                    constantValue:
                      stringValue: ''
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                    constantValue:
                      stringValue: ''
                bigquery_source_input_uri:
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                    constantValue:
                      stringValue: ''
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                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
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                    constantValue:
                      stringValue: '{}'
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                instances_format:
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                      stringValue: tf-record
                job_display_name:
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                labels:
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                    constantValue:
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                    constantValue:
                      stringValue: '{}'
                predictions_format:
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                    constantValue:
                      stringValue: tf-record
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            taskInfo:
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            componentRef:
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            dependentTasks:
            - set-model-can-skip-validation
            inputs:
              artifacts:
                explanation_metadata_artifact:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-2-explanation_metadata_artifact
                unmanaged_container_model:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model
              parameters:
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                  runtimeValue:
                    constantValue:
                      stringValue: ''
                display_name:
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                    constantValue:
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                encryption_spec_key_name:
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                explanation_metadata:
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                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
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                labels:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                location:
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                project:
                  componentInputParameter: pipelineparam--project
            taskInfo:
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            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-model-upload-4
            dependentTasks:
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            - automl-tabular-infra-validator-3
            inputs:
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                    producerTask: automl-tabular-ensemble-3
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                    outputArtifactKey: unmanaged_container_model
                    producerTask: automl-tabular-ensemble-3
              parameters:
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                  runtimeValue:
                    constantValue:
                      stringValue: ''
                display_name:
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                    constantValue:
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                explanation_metadata:
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                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
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                    producerTask: automl-tabular-ensemble-3
                labels:
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                    constantValue:
                      stringValue: '{}'
                location:
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                project:
                  componentInputParameter: pipelineparam--project
            taskInfo:
              name: model-upload-4
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              enableCache: true
            componentRef:
              name: comp-read-input-uri
            inputs:
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            taskInfo:
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            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-read-input-uri-2
            inputs:
              artifacts:
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            taskInfo:
              name: read-input-uri-2
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            cachingOptions:
              enableCache: true
            componentRef:
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            inputs:
              artifacts:
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            taskInfo:
              name: set-model-can-skip-validation
          write-bp-result-path:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-write-bp-result-path
            dependentTasks:
            - model-batch-predict-3
            inputs:
              artifacts:
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                  taskOutputArtifact:
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                    producerTask: model-batch-predict-3
            taskInfo:
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          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:
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              schemaVersion: 0.0.1
          pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model:
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              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-dataset_schema:
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              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-eval_split:
            artifactType:
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              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-instance_baseline:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-metadata:
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              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-test_split:
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              schemaTitle: system.Dataset
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-train_split:
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              schemaTitle: system.Dataset
              schemaVersion: 0.0.1
        parameters:
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          pipelineparam--bool-identity-3-Output:
            type: STRING
          pipelineparam--calculate-training-parameters-2-distill_stage_1_deadline_hours:
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          pipelineparam--calculate-training-parameters-2-reduce_search_space_mode:
            type: STRING
          pipelineparam--calculate-training-parameters-2-stage_1_single_run_max_secs:
            type: INT
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--disable_early_stopping:
            type: STRING
          pipelineparam--distill_batch_predict_machine_type:
            type: STRING
          pipelineparam--distill_batch_predict_max_replica_count:
            type: INT
          pipelineparam--distill_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
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          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--export_additional_model_without_custom_ops:
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          pipelineparam--location:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--stage_1_num_parallel_trials:
            type: INT
          pipelineparam--stage_1_tuner_worker_pool_specs_override:
            type: STRING
          pipelineparam--string-not-empty-Output:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-test_split_json:
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          pipelineparam--target_column:
            type: STRING
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            type: INT
          pipelineparam--transform_dataflow_machine_type:
            type: STRING
          pipelineparam--transform_dataflow_max_num_workers:
            type: INT
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          model-evaluation-3-evaluation_metrics:
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              schemaVersion: 0.0.1
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                producerSubtask: feature-attribution
            model-evaluation-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: evaluation_metrics
                producerSubtask: model-evaluation
        tasks:
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            cachingOptions:
              enableCache: true
            componentRef:
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            dependentTasks:
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            inputs:
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                    producerTask: model-batch-explanation
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                dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                dataflow_workers_num:
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                encryption_spec_key_name:
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                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
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                root_dir:
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            taskInfo:
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              enableCache: true
            componentRef:
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            inputs:
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              parameters:
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                    constantValue:
                      intValue: '0'
                accelerator_type:
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                    constantValue:
                      stringValue: ''
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                    constantValue:
                      stringValue: ''
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                    constantValue:
                      stringValue: ''
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                    constantValue:
                      intValue: '1'
                instances_format:
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                    constantValue:
                      stringValue: tf-record
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                labels:
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                    constantValue:
                      stringValue: '{}'
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                max_replica_count:
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                    constantValue:
                      stringValue: '{}'
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
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            taskInfo:
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            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-model-batch-predict
            inputs:
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                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-unmanaged_container_model
              parameters:
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                  runtimeValue:
                    constantValue:
                      intValue: '0'
                accelerator_type:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_destination_output_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_source_input_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                explanation_metadata:
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                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
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                    constantValue:
                      stringValue: '{}'
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                    constantValue:
                      intValue: '0'
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                labels:
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                    constantValue:
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                      intValue: '0'
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                    constantValue:
                      stringValue: '{}'
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
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                starting_replica_count:
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            taskInfo:
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            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-model-evaluation
            dependentTasks:
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            inputs:
              artifacts:
                batch_prediction_job:
                  taskOutputArtifact:
                    outputArtifactKey: batchpredictionjob
                    producerTask: model-batch-predict
              parameters:
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                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                classification_type:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                dataflow_disk_size:
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                dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                dataflow_max_workers_num:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                dataflow_workers_num:
                  runtimeValue:
                    constantValue:
                      intValue: '1'
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
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                  runtimeValue:
                    constantValue:
                      stringValue: ''
                generate_feature_attribution:
                  runtimeValue:
                    constantValue:
                      intValue: '0'
                ground_truth_column:
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                ground_truth_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                ground_truth_gcs_source:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                key_columns:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                location:
                  componentInputParameter: pipelineparam--location
                positive_classes:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                prediction_id_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                prediction_label_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                prediction_score_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                problem_type:
                  componentInputParameter: pipelineparam--prediction_type
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--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: pipelineparam--model-upload-model
              parameters:
                dataset_path:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                dataset_paths:
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                dataset_type:
                  runtimeValue:
                    constantValue:
                      stringValue: tf-record
                display_name:
                  runtimeValue:
                    constantValue:
                      stringValue: AutoML Tabular
                problem_type:
                  componentInputParameter: pipelineparam--prediction_type
            taskInfo:
              name: model-evaluation-import
      inputDefinitions:
        artifacts:
          pipelineparam--automl-tabular-ensemble-explanation_metadata_artifact:
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              schemaVersion: 0.0.1
          pipelineparam--automl-tabular-ensemble-unmanaged_container_model:
            artifactType:
              schemaTitle: google.UnmanagedContainerModel
              schemaVersion: 0.0.1
          pipelineparam--model-upload-model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          pipelineparam--automl-tabular-ensemble-explanation_parameters:
            type: STRING
          pipelineparam--bool-identity-Output:
            type: STRING
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
            type: STRING
          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--location:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--string-not-empty-Output:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-test_split_json:
            type: STRING
          pipelineparam--target_column:
            type: 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-is-evaluation-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: pipelineparam--evaluation_dataflow_disk_size_gb
                dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                dataflow_max_workers_num:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                dataflow_workers_num:
                  runtimeValue:
                    constantValue:
                      intValue: '1'
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
            taskInfo:
              name: feature-attribution-2
          model-batch-explanation-2:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-model-batch-explanation-2
            inputs:
              artifacts:
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                unmanaged_container_model:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model
              parameters:
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                    constantValue:
                      intValue: '0'
                accelerator_type:
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                    constantValue:
                      stringValue: ''
                bigquery_destination_output_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_source_input_uri:
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                    constantValue:
                      stringValue: ''
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                explanation_metadata:
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                      stringValue: '{}'
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                  componentInputParameter: pipelineparam--automl-tabular-ensemble-2-explanation_parameters
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                gcs_source_uris:
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                    constantValue:
                      intValue: '1'
                instances_format:
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                    constantValue:
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                    constantValue:
                      stringValue: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
                labels:
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                    constantValue:
                      stringValue: '{}'
                location:
                  componentInputParameter: pipelineparam--location
                machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
                manual_batch_tuning_parameters_batch_size:
                  runtimeValue:
                    constantValue:
                      intValue: '0'
                max_replica_count:
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                model_parameters:
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                    constantValue:
                      stringValue: '{}'
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
                  componentInputParameter: pipelineparam--project
                starting_replica_count:
                  componentInputParameter: pipelineparam--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: pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model
              parameters:
                accelerator_count:
                  runtimeValue:
                    constantValue:
                      intValue: '0'
                accelerator_type:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_destination_output_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_source_input_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                explanation_metadata:
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                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                gcs_destination_output_uri_prefix:
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                gcs_source_uris:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-test_split_json
                generate_explanation:
                  runtimeValue:
                    constantValue:
                      intValue: '0'
                instances_format:
                  runtimeValue:
                    constantValue:
                      stringValue: tf-record
                job_display_name:
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                    constantValue:
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                labels:
                  runtimeValue:
                    constantValue:
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                location:
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                machine_type:
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                manual_batch_tuning_parameters_batch_size:
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                    constantValue:
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                max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                model_parameters:
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                    constantValue:
                      stringValue: '{}'
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
                  componentInputParameter: pipelineparam--project
                starting_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_starting_replica_count
            taskInfo:
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          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:
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                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                classification_type:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                dataflow_disk_size:
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                dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                dataflow_max_workers_num:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                dataflow_workers_num:
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                encryption_spec_key_name:
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                  runtimeValue:
                    constantValue:
                      stringValue: ''
                generate_feature_attribution:
                  runtimeValue:
                    constantValue:
                      intValue: '0'
                ground_truth_column:
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                ground_truth_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                ground_truth_gcs_source:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                key_columns:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                location:
                  componentInputParameter: pipelineparam--location
                positive_classes:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                prediction_id_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                prediction_label_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                prediction_score_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                problem_type:
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                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--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: pipelineparam--model-upload-2-model
              parameters:
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                  runtimeValue:
                    constantValue:
                      stringValue: ''
                dataset_paths:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-test_split_json
                dataset_type:
                  runtimeValue:
                    constantValue:
                      stringValue: tf-record
                display_name:
                  runtimeValue:
                    constantValue:
                      stringValue: AutoML Tabular
                problem_type:
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            taskInfo:
              name: model-evaluation-import-2
      inputDefinitions:
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            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model:
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              schemaTitle: google.UnmanagedContainerModel
              schemaVersion: 0.0.1
          pipelineparam--model-upload-2-model:
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              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
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            type: STRING
          pipelineparam--bool-identity-2-Output:
            type: STRING
          pipelineparam--bool-identity-3-Output:
            type: STRING
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
            type: STRING
          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--location:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--string-not-empty-Output:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-test_split_json:
            type: STRING
          pipelineparam--target_column:
            type: STRING
      outputDefinitions:
        artifacts:
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            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
          model-evaluation-2-evaluation_metrics:
            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
    comp-condition-is-evaluation-8:
      dag:
        outputs:
          artifacts:
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              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:
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                  componentInputParameter: pipelineparam--evaluation_dataflow_disk_size_gb
                dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                dataflow_max_workers_num:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                dataflow_workers_num:
                  runtimeValue:
                    constantValue:
                      intValue: '1'
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
            taskInfo:
              name: feature-attribution-3
          model-batch-explanation-3:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-model-batch-explanation-3
            inputs:
              artifacts:
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                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-3-explanation_metadata_artifact
                unmanaged_container_model:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-3-unmanaged_container_model
              parameters:
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                  runtimeValue:
                    constantValue:
                      intValue: '0'
                accelerator_type:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_destination_output_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_source_input_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                explanation_metadata:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
                  componentInputParameter: pipelineparam--automl-tabular-ensemble-3-explanation_parameters
                gcs_destination_output_uri_prefix:
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                gcs_source_uris:
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                generate_explanation:
                  runtimeValue:
                    constantValue:
                      intValue: '1'
                instances_format:
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                    constantValue:
                      stringValue: tf-record
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                    constantValue:
                      stringValue: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
                labels:
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                    constantValue:
                      stringValue: '{}'
                location:
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                machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
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                    constantValue:
                      intValue: '0'
                max_replica_count:
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                model_parameters:
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                    constantValue:
                      stringValue: '{}'
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
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                starting_replica_count:
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            taskInfo:
              name: model-batch-explanation-3
          model-batch-predict-5:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-model-batch-predict-5
            inputs:
              artifacts:
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                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-3-unmanaged_container_model
              parameters:
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                  runtimeValue:
                    constantValue:
                      intValue: '0'
                accelerator_type:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_destination_output_uri:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                bigquery_source_input_uri:
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                    constantValue:
                      stringValue: ''
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                  componentInputParameter: pipelineparam--encryption_spec_key_name
                explanation_metadata:
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                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
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                    constantValue:
                      stringValue: '{}'
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                gcs_source_uris:
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                    constantValue:
                      intValue: '0'
                instances_format:
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                    constantValue:
                      stringValue: tf-record
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                    constantValue:
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                labels:
                  runtimeValue:
                    constantValue:
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                machine_type:
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                manual_batch_tuning_parameters_batch_size:
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                      intValue: '0'
                max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                model_parameters:
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                    constantValue:
                      stringValue: '{}'
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                project:
                  componentInputParameter: pipelineparam--project
                starting_replica_count:
                  componentInputParameter: pipelineparam--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:
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                    outputArtifactKey: batchpredictionjob
                    producerTask: model-batch-predict-5
              parameters:
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                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                classification_type:
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                    constantValue:
                      stringValue: ''
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                dataflow_machine_type:
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                dataflow_max_workers_num:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
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                  componentInputParameter: pipelineparam--dataflow_subnetwork
                dataflow_use_public_ips:
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                    constantValue:
                      intValue: '1'
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
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                    constantValue:
                      stringValue: ''
                generate_feature_attribution:
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                    constantValue:
                      intValue: '0'
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                ground_truth_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                ground_truth_gcs_source:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                key_columns:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                location:
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                positive_classes:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                prediction_id_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                prediction_label_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                prediction_score_column:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                predictions_format:
                  runtimeValue:
                    constantValue:
                      stringValue: jsonl
                problem_type:
                  componentInputParameter: pipelineparam--prediction_type
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--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: pipelineparam--model-upload-4-model
              parameters:
                dataset_path:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                dataset_paths:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-test_split_json
                dataset_type:
                  runtimeValue:
                    constantValue:
                      stringValue: tf-record
                display_name:
                  runtimeValue:
                    constantValue:
                      stringValue: AutoML Tabular
                problem_type:
                  componentInputParameter: pipelineparam--prediction_type
            taskInfo:
              name: model-evaluation-import-3
      inputDefinitions:
        artifacts:
          pipelineparam--automl-tabular-ensemble-3-explanation_metadata_artifact:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--automl-tabular-ensemble-3-unmanaged_container_model:
            artifactType:
              schemaTitle: google.UnmanagedContainerModel
              schemaVersion: 0.0.1
          pipelineparam--model-upload-4-model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          pipelineparam--automl-tabular-ensemble-3-explanation_parameters:
            type: STRING
          pipelineparam--bool-identity-2-Output:
            type: STRING
          pipelineparam--bool-identity-3-Output:
            type: STRING
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
            type: STRING
          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--location:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--string-not-empty-Output:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-test_split_json:
            type: STRING
          pipelineparam--target_column:
            type: 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-condition-no-distill-5:
      dag:
        outputs:
          artifacts:
            feature-attribution-2-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-2-feature_attributions
                producerSubtask: condition-is-evaluation-6
            model-evaluation-2-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-2-evaluation_metrics
                producerSubtask: condition-is-evaluation-6
        tasks:
          condition-is-evaluation-6:
            componentRef:
              name: comp-condition-is-evaluation-6
            dependentTasks:
            - model-upload-2
            inputs:
              artifacts:
                pipelineparam--automl-tabular-ensemble-2-explanation_metadata_artifact:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-2-explanation_metadata_artifact
                pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model
                pipelineparam--model-upload-2-model:
                  taskOutputArtifact:
                    outputArtifactKey: model
                    producerTask: model-upload-2
              parameters:
                pipelineparam--automl-tabular-ensemble-2-explanation_parameters:
                  componentInputParameter: pipelineparam--automl-tabular-ensemble-2-explanation_parameters
                pipelineparam--bool-identity-2-Output:
                  componentInputParameter: pipelineparam--bool-identity-2-Output
                pipelineparam--bool-identity-3-Output:
                  componentInputParameter: pipelineparam--bool-identity-3-Output
                pipelineparam--dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                pipelineparam--dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                pipelineparam--dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                pipelineparam--encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                pipelineparam--evaluation_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
                pipelineparam--evaluation_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                pipelineparam--evaluation_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_starting_replica_count
                pipelineparam--evaluation_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--evaluation_dataflow_disk_size_gb
                pipelineparam--evaluation_dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                pipelineparam--evaluation_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                pipelineparam--location:
                  componentInputParameter: pipelineparam--location
                pipelineparam--prediction_type:
                  componentInputParameter: pipelineparam--prediction_type
                pipelineparam--project:
                  componentInputParameter: pipelineparam--project
                pipelineparam--root_dir:
                  componentInputParameter: pipelineparam--root_dir
                pipelineparam--string-not-empty-Output:
                  componentInputParameter: pipelineparam--string-not-empty-Output
                pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json
                pipelineparam--tabular-stats-and-example-gen-test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-test_split_json
                pipelineparam--target_column:
                  componentInputParameter: pipelineparam--target_column
            taskInfo:
              name: condition-is-evaluation-6
            triggerPolicy:
              condition: inputs.parameters['pipelineparam--bool-identity-2-Output'].string_value
                == 'true'
          model-upload-2:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-model-upload-2
            inputs:
              artifacts:
                explanation_metadata_artifact:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-2-explanation_metadata_artifact
                unmanaged_container_model:
                  componentInputArtifact: pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model
              parameters:
                description:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                display_name:
                  runtimeValue:
                    constantValue:
                      stringValue: automl-tabular-model-upload-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                explanation_metadata:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
                  componentInputParameter: pipelineparam--automl-tabular-ensemble-2-explanation_parameters
                labels:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                location:
                  componentInputParameter: pipelineparam--location
                project:
                  componentInputParameter: pipelineparam--project
            taskInfo:
              name: model-upload-2
      inputDefinitions:
        artifacts:
          pipelineparam--automl-tabular-ensemble-2-explanation_metadata_artifact:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model:
            artifactType:
              schemaTitle: google.UnmanagedContainerModel
              schemaVersion: 0.0.1
        parameters:
          pipelineparam--automl-tabular-ensemble-2-explanation_parameters:
            type: STRING
          pipelineparam--bool-identity-2-Output:
            type: STRING
          pipelineparam--bool-identity-3-Output:
            type: STRING
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
            type: STRING
          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--location:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--string-not-empty-Output:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-test_split_json:
            type: STRING
          pipelineparam--target_column:
            type: 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-stage-1-tuning-result-artifact-uri-empty-4:
      dag:
        outputs:
          artifacts:
            feature-attribution-2-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-2-feature_attributions
                producerSubtask: condition-no-distill-5
            feature-attribution-3-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-3-feature_attributions
                producerSubtask: condition-is-distill-7
            model-evaluation-2-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-2-evaluation_metrics
                producerSubtask: condition-no-distill-5
            model-evaluation-3-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-3-evaluation_metrics
                producerSubtask: condition-is-distill-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: pipelineparam--merge-materialized-splits-splits
                metadata:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-metadata
                transform_output:
                  componentInputArtifact: pipelineparam--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: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_2_num_parallel_trials
                num_selected_trials:
                  componentInputParameter: pipelineparam--stage_2_num_selected_trials
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--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: pipelineparam--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: pipelineparam--tabular-stats-and-example-gen-dataset_schema
                instance_baseline:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-instance_baseline
                metadata:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-metadata
                transform_output:
                  componentInputArtifact: pipelineparam--automl-tabular-transform-transform_output
                tuning_result_input:
                  taskOutputArtifact:
                    outputArtifactKey: tuning_result_output
                    producerTask: automl-tabular-cv-trainer-2
                warmup_data:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-eval_split
              parameters:
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                export_additional_model_without_custom_ops:
                  componentInputParameter: pipelineparam--export_additional_model_without_custom_ops
                location:
                  componentInputParameter: pipelineparam--location
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--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: pipelineparam--automl-tabular-transform-materialized_eval_split
                materialized_train_split:
                  componentInputArtifact: pipelineparam--automl-tabular-transform-materialized_train_split
                metadata:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-metadata
                transform_output:
                  componentInputArtifact: pipelineparam--automl-tabular-transform-transform_output
              parameters:
                deadline_hours:
                  taskOutputParameter:
                    outputParameterKey: stage_1_deadline_hours
                    producerTask: calculate-training-parameters-2
                disable_early_stopping:
                  componentInputParameter: pipelineparam--disable_early_stopping
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_1_num_parallel_trials
                num_selected_trials:
                  taskOutputParameter:
                    outputParameterKey: stage_1_num_selected_trials
                    producerTask: calculate-training-parameters-2
                project:
                  componentInputParameter: pipelineparam--project
                reduce_search_space_mode:
                  taskOutputParameter:
                    outputParameterKey: reduce_search_space_mode
                    producerTask: calculate-training-parameters-2
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
                run_distillation:
                  runtimeValue:
                    constantValue:
                      stringValue: 'false'
                single_run_max_secs:
                  taskOutputParameter:
                    outputParameterKey: stage_1_single_run_max_secs
                    producerTask: calculate-training-parameters-2
                study_spec_parameters_override:
                  componentInputParameter: pipelineparam--study_spec_parameters_override
                tune_feature_selection_rate:
                  runtimeValue:
                    constantValue:
                      stringValue: 'false'
                worker_pool_specs_override_json:
                  componentInputParameter: pipelineparam--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: pipelineparam--run_evaluation
            taskInfo:
              name: bool-identity-2
          bool-identity-3:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-bool-identity-3
            inputs:
              parameters:
                value:
                  componentInputParameter: pipelineparam--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: pipelineparam--fast_testing
                is_skip_architecture_search:
                  runtimeValue:
                    constantValue:
                      intValue: '0'
                run_distillation:
                  componentInputParameter: pipelineparam--run_distillation
                stage_1_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_1_num_parallel_trials
                stage_2_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_2_num_parallel_trials
                train_budget_milli_node_hours:
                  componentInputParameter: pipelineparam--train_budget_milli_node_hours
            taskInfo:
              name: calculate-training-parameters-2
          condition-is-distill-7:
            componentRef:
              name: comp-condition-is-distill-7
            dependentTasks:
            - automl-tabular-ensemble-2
            - automl-tabular-infra-validator-2
            - bool-identity-2
            - bool-identity-3
            - calculate-training-parameters-2
            inputs:
              artifacts:
                pipelineparam--automl-tabular-ensemble-2-explanation_metadata_artifact:
                  taskOutputArtifact:
                    outputArtifactKey: explanation_metadata_artifact
                    producerTask: automl-tabular-ensemble-2
                pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model:
                  taskOutputArtifact:
                    outputArtifactKey: unmanaged_container_model
                    producerTask: automl-tabular-ensemble-2
                pipelineparam--tabular-stats-and-example-gen-dataset_schema:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-dataset_schema
                pipelineparam--tabular-stats-and-example-gen-eval_split:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-eval_split
                pipelineparam--tabular-stats-and-example-gen-instance_baseline:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-instance_baseline
                pipelineparam--tabular-stats-and-example-gen-metadata:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-metadata
                pipelineparam--tabular-stats-and-example-gen-test_split:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-test_split
                pipelineparam--tabular-stats-and-example-gen-train_split:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-train_split
              parameters:
                pipelineparam--automl-tabular-ensemble-2-explanation_parameters:
                  taskOutputParameter:
                    outputParameterKey: explanation_parameters
                    producerTask: automl-tabular-ensemble-2
                pipelineparam--bool-identity-2-Output:
                  taskOutputParameter:
                    outputParameterKey: Output
                    producerTask: bool-identity-2
                pipelineparam--bool-identity-3-Output:
                  taskOutputParameter:
                    outputParameterKey: Output
                    producerTask: bool-identity-3
                pipelineparam--calculate-training-parameters-2-distill_stage_1_deadline_hours:
                  taskOutputParameter:
                    outputParameterKey: distill_stage_1_deadline_hours
                    producerTask: calculate-training-parameters-2
                pipelineparam--calculate-training-parameters-2-reduce_search_space_mode:
                  taskOutputParameter:
                    outputParameterKey: reduce_search_space_mode
                    producerTask: calculate-training-parameters-2
                pipelineparam--calculate-training-parameters-2-stage_1_single_run_max_secs:
                  taskOutputParameter:
                    outputParameterKey: stage_1_single_run_max_secs
                    producerTask: calculate-training-parameters-2
                pipelineparam--dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                pipelineparam--dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                pipelineparam--dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                pipelineparam--disable_early_stopping:
                  componentInputParameter: pipelineparam--disable_early_stopping
                pipelineparam--distill_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--distill_batch_predict_machine_type
                pipelineparam--distill_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--distill_batch_predict_max_replica_count
                pipelineparam--distill_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--distill_batch_predict_starting_replica_count
                pipelineparam--encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                pipelineparam--evaluation_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
                pipelineparam--evaluation_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                pipelineparam--evaluation_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_starting_replica_count
                pipelineparam--evaluation_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--evaluation_dataflow_disk_size_gb
                pipelineparam--evaluation_dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                pipelineparam--evaluation_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                pipelineparam--export_additional_model_without_custom_ops:
                  componentInputParameter: pipelineparam--export_additional_model_without_custom_ops
                pipelineparam--location:
                  componentInputParameter: pipelineparam--location
                pipelineparam--prediction_type:
                  componentInputParameter: pipelineparam--prediction_type
                pipelineparam--project:
                  componentInputParameter: pipelineparam--project
                pipelineparam--root_dir:
                  componentInputParameter: pipelineparam--root_dir
                pipelineparam--stage_1_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_1_num_parallel_trials
                pipelineparam--stage_1_tuner_worker_pool_specs_override:
                  componentInputParameter: pipelineparam--stage_1_tuner_worker_pool_specs_override
                pipelineparam--string-not-empty-Output:
                  componentInputParameter: pipelineparam--string-not-empty-Output
                pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json
                pipelineparam--tabular-stats-and-example-gen-test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-test_split_json
                pipelineparam--target_column:
                  componentInputParameter: pipelineparam--target_column
                pipelineparam--transform_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--transform_dataflow_disk_size_gb
                pipelineparam--transform_dataflow_machine_type:
                  componentInputParameter: pipelineparam--transform_dataflow_machine_type
                pipelineparam--transform_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--transform_dataflow_max_num_workers
            taskInfo:
              name: condition-is-distill-7
            triggerPolicy:
              condition: inputs.parameters['pipelineparam--bool-identity-3-Output'].string_value
                == 'true'
          condition-no-distill-5:
            componentRef:
              name: comp-condition-no-distill-5
            dependentTasks:
            - automl-tabular-ensemble-2
            - automl-tabular-infra-validator-2
            - bool-identity-2
            - bool-identity-3
            inputs:
              artifacts:
                pipelineparam--automl-tabular-ensemble-2-explanation_metadata_artifact:
                  taskOutputArtifact:
                    outputArtifactKey: explanation_metadata_artifact
                    producerTask: automl-tabular-ensemble-2
                pipelineparam--automl-tabular-ensemble-2-unmanaged_container_model:
                  taskOutputArtifact:
                    outputArtifactKey: unmanaged_container_model
                    producerTask: automl-tabular-ensemble-2
              parameters:
                pipelineparam--automl-tabular-ensemble-2-explanation_parameters:
                  taskOutputParameter:
                    outputParameterKey: explanation_parameters
                    producerTask: automl-tabular-ensemble-2
                pipelineparam--bool-identity-2-Output:
                  taskOutputParameter:
                    outputParameterKey: Output
                    producerTask: bool-identity-2
                pipelineparam--bool-identity-3-Output:
                  taskOutputParameter:
                    outputParameterKey: Output
                    producerTask: bool-identity-3
                pipelineparam--dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                pipelineparam--dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                pipelineparam--dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                pipelineparam--encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                pipelineparam--evaluation_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
                pipelineparam--evaluation_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                pipelineparam--evaluation_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_starting_replica_count
                pipelineparam--evaluation_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--evaluation_dataflow_disk_size_gb
                pipelineparam--evaluation_dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                pipelineparam--evaluation_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                pipelineparam--location:
                  componentInputParameter: pipelineparam--location
                pipelineparam--prediction_type:
                  componentInputParameter: pipelineparam--prediction_type
                pipelineparam--project:
                  componentInputParameter: pipelineparam--project
                pipelineparam--root_dir:
                  componentInputParameter: pipelineparam--root_dir
                pipelineparam--string-not-empty-Output:
                  componentInputParameter: pipelineparam--string-not-empty-Output
                pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json
                pipelineparam--tabular-stats-and-example-gen-test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-test_split_json
                pipelineparam--target_column:
                  componentInputParameter: pipelineparam--target_column
            taskInfo:
              name: condition-no-distill-5
            triggerPolicy:
              condition: inputs.parameters['pipelineparam--bool-identity-3-Output'].string_value
                == 'false'
      inputDefinitions:
        artifacts:
          pipelineparam--automl-tabular-transform-materialized_eval_split:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--automl-tabular-transform-materialized_train_split:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--automl-tabular-transform-transform_output:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--merge-materialized-splits-splits:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-dataset_schema:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-eval_split:
            artifactType:
              schemaTitle: system.Dataset
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-instance_baseline:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-metadata:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-test_split:
            artifactType:
              schemaTitle: system.Dataset
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-train_split:
            artifactType:
              schemaTitle: system.Dataset
              schemaVersion: 0.0.1
        parameters:
          pipelineparam--cv_trainer_worker_pool_specs_override:
            type: STRING
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--disable_early_stopping:
            type: STRING
          pipelineparam--distill_batch_predict_machine_type:
            type: STRING
          pipelineparam--distill_batch_predict_max_replica_count:
            type: INT
          pipelineparam--distill_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
            type: STRING
          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--export_additional_model_without_custom_ops:
            type: STRING
          pipelineparam--fast_testing:
            type: STRING
          pipelineparam--location:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--run_distillation:
            type: STRING
          pipelineparam--run_evaluation:
            type: STRING
          pipelineparam--stage_1_num_parallel_trials:
            type: INT
          pipelineparam--stage_1_tuner_worker_pool_specs_override:
            type: STRING
          pipelineparam--stage_2_num_parallel_trials:
            type: INT
          pipelineparam--stage_2_num_selected_trials:
            type: INT
          pipelineparam--string-not-empty-Output:
            type: STRING
          pipelineparam--study_spec_parameters_override:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-test_split_json:
            type: STRING
          pipelineparam--target_column:
            type: STRING
          pipelineparam--train_budget_milli_node_hours:
            type: DOUBLE
          pipelineparam--transform_dataflow_disk_size_gb:
            type: INT
          pipelineparam--transform_dataflow_machine_type:
            type: STRING
          pipelineparam--transform_dataflow_max_num_workers:
            type: INT
      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-stage-1-tuning-result-artifact-uri-not-empty-2:
      dag:
        outputs:
          artifacts:
            feature-attribution-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-feature_attributions
                producerSubtask: condition-is-evaluation-3
            model-evaluation-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-evaluation_metrics
                producerSubtask: condition-is-evaluation-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: pipelineparam--merge-materialized-splits-splits
                metadata:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-metadata
                transform_output:
                  componentInputArtifact: pipelineparam--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: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_2_num_parallel_trials
                num_selected_trials:
                  componentInputParameter: pipelineparam--stage_2_num_selected_trials
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
                single_run_max_secs:
                  taskOutputParameter:
                    outputParameterKey: stage_2_single_run_max_secs
                    producerTask: calculate-training-parameters
                worker_pool_specs_override_json:
                  componentInputParameter: pipelineparam--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: pipelineparam--tabular-stats-and-example-gen-dataset_schema
                instance_baseline:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-instance_baseline
                metadata:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-metadata
                transform_output:
                  componentInputArtifact: pipelineparam--automl-tabular-transform-transform_output
                tuning_result_input:
                  taskOutputArtifact:
                    outputArtifactKey: tuning_result_output
                    producerTask: automl-tabular-cv-trainer
                warmup_data:
                  componentInputArtifact: pipelineparam--tabular-stats-and-example-gen-eval_split
              parameters:
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                export_additional_model_without_custom_ops:
                  componentInputParameter: pipelineparam--export_additional_model_without_custom_ops
                location:
                  componentInputParameter: pipelineparam--location
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--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: pipelineparam--run_evaluation
            taskInfo:
              name: bool-identity
          calculate-training-parameters:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-calculate-training-parameters
            inputs:
              parameters:
                fast_testing:
                  componentInputParameter: pipelineparam--fast_testing
                is_skip_architecture_search:
                  runtimeValue:
                    constantValue:
                      intValue: '1'
                run_distillation:
                  componentInputParameter: pipelineparam--run_distillation
                stage_1_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_1_num_parallel_trials
                stage_2_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_2_num_parallel_trials
                train_budget_milli_node_hours:
                  componentInputParameter: pipelineparam--train_budget_milli_node_hours
            taskInfo:
              name: calculate-training-parameters
          condition-is-evaluation-3:
            componentRef:
              name: comp-condition-is-evaluation-3
            dependentTasks:
            - automl-tabular-ensemble
            - bool-identity
            - model-upload
            inputs:
              artifacts:
                pipelineparam--automl-tabular-ensemble-explanation_metadata_artifact:
                  taskOutputArtifact:
                    outputArtifactKey: explanation_metadata_artifact
                    producerTask: automl-tabular-ensemble
                pipelineparam--automl-tabular-ensemble-unmanaged_container_model:
                  taskOutputArtifact:
                    outputArtifactKey: unmanaged_container_model
                    producerTask: automl-tabular-ensemble
                pipelineparam--model-upload-model:
                  taskOutputArtifact:
                    outputArtifactKey: model
                    producerTask: model-upload
              parameters:
                pipelineparam--automl-tabular-ensemble-explanation_parameters:
                  taskOutputParameter:
                    outputParameterKey: explanation_parameters
                    producerTask: automl-tabular-ensemble
                pipelineparam--bool-identity-Output:
                  taskOutputParameter:
                    outputParameterKey: Output
                    producerTask: bool-identity
                pipelineparam--dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                pipelineparam--dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                pipelineparam--dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                pipelineparam--encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                pipelineparam--evaluation_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
                pipelineparam--evaluation_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                pipelineparam--evaluation_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_starting_replica_count
                pipelineparam--evaluation_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--evaluation_dataflow_disk_size_gb
                pipelineparam--evaluation_dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                pipelineparam--evaluation_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                pipelineparam--location:
                  componentInputParameter: pipelineparam--location
                pipelineparam--prediction_type:
                  componentInputParameter: pipelineparam--prediction_type
                pipelineparam--project:
                  componentInputParameter: pipelineparam--project
                pipelineparam--root_dir:
                  componentInputParameter: pipelineparam--root_dir
                pipelineparam--string-not-empty-Output:
                  componentInputParameter: pipelineparam--string-not-empty-Output
                pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json
                pipelineparam--tabular-stats-and-example-gen-test_split_json:
                  componentInputParameter: pipelineparam--tabular-stats-and-example-gen-test_split_json
                pipelineparam--target_column:
                  componentInputParameter: pipelineparam--target_column
            taskInfo:
              name: condition-is-evaluation-3
            triggerPolicy:
              condition: inputs.parameters['pipelineparam--bool-identity-Output'].string_value
                == 'true'
          importer:
            cachingOptions:
              enableCache: true
            componentRef:
              name: comp-importer
            inputs:
              parameters:
                uri:
                  componentInputParameter: pipelineparam--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:
                unmanaged_container_model:
                  taskOutputArtifact:
                    outputArtifactKey: unmanaged_container_model
                    producerTask: automl-tabular-ensemble
              parameters:
                description:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                display_name:
                  runtimeValue:
                    constantValue:
                      stringValue: automl-tabular-model-upload-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                explanation_metadata:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                explanation_parameters:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                labels:
                  runtimeValue:
                    constantValue:
                      stringValue: '{}'
                location:
                  componentInputParameter: pipelineparam--location
                project:
                  componentInputParameter: pipelineparam--project
            taskInfo:
              name: model-upload
      inputDefinitions:
        artifacts:
          pipelineparam--automl-tabular-transform-transform_output:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--merge-materialized-splits-splits:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-dataset_schema:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-eval_split:
            artifactType:
              schemaTitle: system.Dataset
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-instance_baseline:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
          pipelineparam--tabular-stats-and-example-gen-metadata:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
        parameters:
          pipelineparam--cv_trainer_worker_pool_specs_override:
            type: STRING
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
            type: STRING
          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--export_additional_model_without_custom_ops:
            type: STRING
          pipelineparam--fast_testing:
            type: STRING
          pipelineparam--location:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--run_distillation:
            type: STRING
          pipelineparam--run_evaluation:
            type: STRING
          pipelineparam--stage_1_num_parallel_trials:
            type: INT
          pipelineparam--stage_1_tuning_result_artifact_uri:
            type: STRING
          pipelineparam--stage_2_num_parallel_trials:
            type: INT
          pipelineparam--stage_2_num_selected_trials:
            type: INT
          pipelineparam--string-not-empty-Output:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
            type: STRING
          pipelineparam--tabular-stats-and-example-gen-test_split_json:
            type: STRING
          pipelineparam--target_column:
            type: STRING
          pipelineparam--train_budget_milli_node_hours:
            type: 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-exit-handler-1:
      dag:
        outputs:
          artifacts:
            feature-attribution-2-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-2-feature_attributions
                producerSubtask: condition-stage-1-tuning-result-artifact-uri-empty-4
            feature-attribution-3-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-3-feature_attributions
                producerSubtask: condition-stage-1-tuning-result-artifact-uri-empty-4
            feature-attribution-feature_attributions:
              artifactSelectors:
              - outputArtifactKey: feature-attribution-feature_attributions
                producerSubtask: condition-stage-1-tuning-result-artifact-uri-not-empty-2
            model-evaluation-2-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-2-evaluation_metrics
                producerSubtask: condition-stage-1-tuning-result-artifact-uri-empty-4
            model-evaluation-3-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-3-evaluation_metrics
                producerSubtask: condition-stage-1-tuning-result-artifact-uri-empty-4
            model-evaluation-evaluation_metrics:
              artifactSelectors:
              - outputArtifactKey: model-evaluation-evaluation_metrics
                producerSubtask: condition-stage-1-tuning-result-artifact-uri-not-empty-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: pipelineparam--transform_dataflow_disk_size_gb
                dataflow_machine_type:
                  componentInputParameter: pipelineparam--transform_dataflow_machine_type
                dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--transform_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                project:
                  componentInputParameter: pipelineparam--project
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
            taskInfo:
              name: automl-tabular-transform
          condition-stage-1-tuning-result-artifact-uri-empty-4:
            componentRef:
              name: comp-condition-stage-1-tuning-result-artifact-uri-empty-4
            dependentTasks:
            - automl-tabular-transform
            - merge-materialized-splits
            - string-not-empty
            - tabular-stats-and-example-gen
            inputs:
              artifacts:
                pipelineparam--automl-tabular-transform-materialized_eval_split:
                  taskOutputArtifact:
                    outputArtifactKey: materialized_eval_split
                    producerTask: automl-tabular-transform
                pipelineparam--automl-tabular-transform-materialized_train_split:
                  taskOutputArtifact:
                    outputArtifactKey: materialized_train_split
                    producerTask: automl-tabular-transform
                pipelineparam--automl-tabular-transform-transform_output:
                  taskOutputArtifact:
                    outputArtifactKey: transform_output
                    producerTask: automl-tabular-transform
                pipelineparam--merge-materialized-splits-splits:
                  taskOutputArtifact:
                    outputArtifactKey: splits
                    producerTask: merge-materialized-splits
                pipelineparam--tabular-stats-and-example-gen-dataset_schema:
                  taskOutputArtifact:
                    outputArtifactKey: dataset_schema
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-eval_split:
                  taskOutputArtifact:
                    outputArtifactKey: eval_split
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-instance_baseline:
                  taskOutputArtifact:
                    outputArtifactKey: instance_baseline
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-metadata:
                  taskOutputArtifact:
                    outputArtifactKey: metadata
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-test_split:
                  taskOutputArtifact:
                    outputArtifactKey: test_split
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-train_split:
                  taskOutputArtifact:
                    outputArtifactKey: train_split
                    producerTask: tabular-stats-and-example-gen
              parameters:
                pipelineparam--cv_trainer_worker_pool_specs_override:
                  componentInputParameter: pipelineparam--cv_trainer_worker_pool_specs_override
                pipelineparam--dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                pipelineparam--dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                pipelineparam--dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                pipelineparam--disable_early_stopping:
                  componentInputParameter: pipelineparam--disable_early_stopping
                pipelineparam--distill_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--distill_batch_predict_machine_type
                pipelineparam--distill_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--distill_batch_predict_max_replica_count
                pipelineparam--distill_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--distill_batch_predict_starting_replica_count
                pipelineparam--encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                pipelineparam--evaluation_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
                pipelineparam--evaluation_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                pipelineparam--evaluation_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_starting_replica_count
                pipelineparam--evaluation_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--evaluation_dataflow_disk_size_gb
                pipelineparam--evaluation_dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                pipelineparam--evaluation_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                pipelineparam--export_additional_model_without_custom_ops:
                  componentInputParameter: pipelineparam--export_additional_model_without_custom_ops
                pipelineparam--fast_testing:
                  componentInputParameter: pipelineparam--fast_testing
                pipelineparam--location:
                  componentInputParameter: pipelineparam--location
                pipelineparam--prediction_type:
                  componentInputParameter: pipelineparam--prediction_type
                pipelineparam--project:
                  componentInputParameter: pipelineparam--project
                pipelineparam--root_dir:
                  componentInputParameter: pipelineparam--root_dir
                pipelineparam--run_distillation:
                  componentInputParameter: pipelineparam--run_distillation
                pipelineparam--run_evaluation:
                  componentInputParameter: pipelineparam--run_evaluation
                pipelineparam--stage_1_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_1_num_parallel_trials
                pipelineparam--stage_1_tuner_worker_pool_specs_override:
                  componentInputParameter: pipelineparam--stage_1_tuner_worker_pool_specs_override
                pipelineparam--stage_2_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_2_num_parallel_trials
                pipelineparam--stage_2_num_selected_trials:
                  componentInputParameter: pipelineparam--stage_2_num_selected_trials
                pipelineparam--string-not-empty-Output:
                  taskOutputParameter:
                    outputParameterKey: Output
                    producerTask: string-not-empty
                pipelineparam--study_spec_parameters_override:
                  componentInputParameter: pipelineparam--study_spec_parameters_override
                pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
                  taskOutputParameter:
                    outputParameterKey: downsampled_test_split_json
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-test_split_json:
                  taskOutputParameter:
                    outputParameterKey: test_split_json
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--target_column:
                  componentInputParameter: pipelineparam--target_column
                pipelineparam--train_budget_milli_node_hours:
                  componentInputParameter: pipelineparam--train_budget_milli_node_hours
                pipelineparam--transform_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--transform_dataflow_disk_size_gb
                pipelineparam--transform_dataflow_machine_type:
                  componentInputParameter: pipelineparam--transform_dataflow_machine_type
                pipelineparam--transform_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--transform_dataflow_max_num_workers
            taskInfo:
              name: condition-stage-1-tuning-result-artifact-uri-empty-4
            triggerPolicy:
              condition: inputs.parameters['pipelineparam--string-not-empty-Output'].string_value
                == 'false'
          condition-stage-1-tuning-result-artifact-uri-not-empty-2:
            componentRef:
              name: comp-condition-stage-1-tuning-result-artifact-uri-not-empty-2
            dependentTasks:
            - automl-tabular-transform
            - merge-materialized-splits
            - string-not-empty
            - tabular-stats-and-example-gen
            inputs:
              artifacts:
                pipelineparam--automl-tabular-transform-transform_output:
                  taskOutputArtifact:
                    outputArtifactKey: transform_output
                    producerTask: automl-tabular-transform
                pipelineparam--merge-materialized-splits-splits:
                  taskOutputArtifact:
                    outputArtifactKey: splits
                    producerTask: merge-materialized-splits
                pipelineparam--tabular-stats-and-example-gen-dataset_schema:
                  taskOutputArtifact:
                    outputArtifactKey: dataset_schema
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-eval_split:
                  taskOutputArtifact:
                    outputArtifactKey: eval_split
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-instance_baseline:
                  taskOutputArtifact:
                    outputArtifactKey: instance_baseline
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-metadata:
                  taskOutputArtifact:
                    outputArtifactKey: metadata
                    producerTask: tabular-stats-and-example-gen
              parameters:
                pipelineparam--cv_trainer_worker_pool_specs_override:
                  componentInputParameter: pipelineparam--cv_trainer_worker_pool_specs_override
                pipelineparam--dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                pipelineparam--dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                pipelineparam--dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                pipelineparam--encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                pipelineparam--evaluation_batch_predict_machine_type:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_machine_type
                pipelineparam--evaluation_batch_predict_max_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_max_replica_count
                pipelineparam--evaluation_batch_predict_starting_replica_count:
                  componentInputParameter: pipelineparam--evaluation_batch_predict_starting_replica_count
                pipelineparam--evaluation_dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--evaluation_dataflow_disk_size_gb
                pipelineparam--evaluation_dataflow_machine_type:
                  componentInputParameter: pipelineparam--evaluation_dataflow_machine_type
                pipelineparam--evaluation_dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--evaluation_dataflow_max_num_workers
                pipelineparam--export_additional_model_without_custom_ops:
                  componentInputParameter: pipelineparam--export_additional_model_without_custom_ops
                pipelineparam--fast_testing:
                  componentInputParameter: pipelineparam--fast_testing
                pipelineparam--location:
                  componentInputParameter: pipelineparam--location
                pipelineparam--prediction_type:
                  componentInputParameter: pipelineparam--prediction_type
                pipelineparam--project:
                  componentInputParameter: pipelineparam--project
                pipelineparam--root_dir:
                  componentInputParameter: pipelineparam--root_dir
                pipelineparam--run_distillation:
                  componentInputParameter: pipelineparam--run_distillation
                pipelineparam--run_evaluation:
                  componentInputParameter: pipelineparam--run_evaluation
                pipelineparam--stage_1_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_1_num_parallel_trials
                pipelineparam--stage_1_tuning_result_artifact_uri:
                  componentInputParameter: pipelineparam--stage_1_tuning_result_artifact_uri
                pipelineparam--stage_2_num_parallel_trials:
                  componentInputParameter: pipelineparam--stage_2_num_parallel_trials
                pipelineparam--stage_2_num_selected_trials:
                  componentInputParameter: pipelineparam--stage_2_num_selected_trials
                pipelineparam--string-not-empty-Output:
                  taskOutputParameter:
                    outputParameterKey: Output
                    producerTask: string-not-empty
                pipelineparam--tabular-stats-and-example-gen-downsampled_test_split_json:
                  taskOutputParameter:
                    outputParameterKey: downsampled_test_split_json
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--tabular-stats-and-example-gen-test_split_json:
                  taskOutputParameter:
                    outputParameterKey: test_split_json
                    producerTask: tabular-stats-and-example-gen
                pipelineparam--target_column:
                  componentInputParameter: pipelineparam--target_column
                pipelineparam--train_budget_milli_node_hours:
                  componentInputParameter: pipelineparam--train_budget_milli_node_hours
            taskInfo:
              name: condition-stage-1-tuning-result-artifact-uri-not-empty-2
            triggerPolicy:
              condition: inputs.parameters['pipelineparam--string-not-empty-Output'].string_value
                == 'true'
          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: pipelineparam--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:
                  runtimeValue:
                    constantValue:
                      stringValue: ''
                additional_experiments_json:
                  componentInputParameter: pipelineparam--additional_experiments
                data_source_bigquery_table_path:
                  componentInputParameter: pipelineparam--data_source_bigquery_table_path
                data_source_csv_filenames:
                  componentInputParameter: pipelineparam--data_source_csv_filenames
                dataflow_disk_size_gb:
                  componentInputParameter: pipelineparam--stats_and_example_gen_dataflow_disk_size_gb
                dataflow_machine_type:
                  componentInputParameter: pipelineparam--stats_and_example_gen_dataflow_machine_type
                dataflow_max_num_workers:
                  componentInputParameter: pipelineparam--stats_and_example_gen_dataflow_max_num_workers
                dataflow_service_account:
                  componentInputParameter: pipelineparam--dataflow_service_account
                dataflow_subnetwork:
                  componentInputParameter: pipelineparam--dataflow_subnetwork
                dataflow_use_public_ips:
                  componentInputParameter: pipelineparam--dataflow_use_public_ips
                enable_probabilistic_inference:
                  componentInputParameter: pipelineparam--enable_probabilistic_inference
                encryption_spec_key_name:
                  componentInputParameter: pipelineparam--encryption_spec_key_name
                location:
                  componentInputParameter: pipelineparam--location
                optimization_objective:
                  componentInputParameter: pipelineparam--optimization_objective
                optimization_objective_precision_value:
                  componentInputParameter: pipelineparam--optimization_objective_precision_value
                optimization_objective_recall_value:
                  componentInputParameter: pipelineparam--optimization_objective_recall_value
                predefined_split_key:
                  componentInputParameter: pipelineparam--predefined_split_key
                prediction_type:
                  componentInputParameter: pipelineparam--prediction_type
                project:
                  componentInputParameter: pipelineparam--project
                quantiles:
                  componentInputParameter: pipelineparam--quantiles
                request_type:
                  runtimeValue:
                    constantValue:
                      stringValue: COLUMN_STATS_ONLY
                root_dir:
                  componentInputParameter: pipelineparam--root_dir
                run_distillation:
                  componentInputParameter: pipelineparam--run_distillation
                stratified_split_key:
                  componentInputParameter: pipelineparam--stratified_split_key
                target_column_name:
                  componentInputParameter: pipelineparam--target_column
                test_fraction:
                  componentInputParameter: pipelineparam--test_fraction
                timestamp_split_key:
                  componentInputParameter: pipelineparam--timestamp_split_key
                training_fraction:
                  componentInputParameter: pipelineparam--training_fraction
                transformations:
                  runtimeValue:
                    constantValue:
                      stringValue: '[]'
                transformations_path:
                  componentInputParameter: pipelineparam--transformations
                validation_fraction:
                  componentInputParameter: pipelineparam--validation_fraction
                weight_column_name:
                  componentInputParameter: pipelineparam--weight_column
            taskInfo:
              name: tabular-stats-and-example-gen
      inputDefinitions:
        parameters:
          pipelineparam--additional_experiments:
            type: STRING
          pipelineparam--cv_trainer_worker_pool_specs_override:
            type: STRING
          pipelineparam--data_source_bigquery_table_path:
            type: STRING
          pipelineparam--data_source_csv_filenames:
            type: STRING
          pipelineparam--dataflow_service_account:
            type: STRING
          pipelineparam--dataflow_subnetwork:
            type: STRING
          pipelineparam--dataflow_use_public_ips:
            type: STRING
          pipelineparam--disable_early_stopping:
            type: STRING
          pipelineparam--distill_batch_predict_machine_type:
            type: STRING
          pipelineparam--distill_batch_predict_max_replica_count:
            type: INT
          pipelineparam--distill_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--enable_probabilistic_inference:
            type: STRING
          pipelineparam--encryption_spec_key_name:
            type: STRING
          pipelineparam--evaluation_batch_predict_machine_type:
            type: STRING
          pipelineparam--evaluation_batch_predict_max_replica_count:
            type: INT
          pipelineparam--evaluation_batch_predict_starting_replica_count:
            type: INT
          pipelineparam--evaluation_dataflow_disk_size_gb:
            type: INT
          pipelineparam--evaluation_dataflow_machine_type:
            type: STRING
          pipelineparam--evaluation_dataflow_max_num_workers:
            type: INT
          pipelineparam--export_additional_model_without_custom_ops:
            type: STRING
          pipelineparam--fast_testing:
            type: STRING
          pipelineparam--location:
            type: STRING
          pipelineparam--optimization_objective:
            type: STRING
          pipelineparam--optimization_objective_precision_value:
            type: DOUBLE
          pipelineparam--optimization_objective_recall_value:
            type: DOUBLE
          pipelineparam--predefined_split_key:
            type: STRING
          pipelineparam--prediction_type:
            type: STRING
          pipelineparam--project:
            type: STRING
          pipelineparam--quantiles:
            type: STRING
          pipelineparam--root_dir:
            type: STRING
          pipelineparam--run_distillation:
            type: STRING
          pipelineparam--run_evaluation:
            type: STRING
          pipelineparam--stage_1_num_parallel_trials:
            type: INT
          pipelineparam--stage_1_tuner_worker_pool_specs_override:
            type: STRING
          pipelineparam--stage_1_tuning_result_artifact_uri:
            type: STRING
          pipelineparam--stage_2_num_parallel_trials:
            type: INT
          pipelineparam--stage_2_num_selected_trials:
            type: INT
          pipelineparam--stats_and_example_gen_dataflow_disk_size_gb:
            type: INT
          pipelineparam--stats_and_example_gen_dataflow_machine_type:
            type: STRING
          pipelineparam--stats_and_example_gen_dataflow_max_num_workers:
            type: INT
          pipelineparam--stratified_split_key:
            type: STRING
          pipelineparam--study_spec_parameters_override:
            type: STRING
          pipelineparam--target_column:
            type: STRING
          pipelineparam--test_fraction:
            type: DOUBLE
          pipelineparam--timestamp_split_key:
            type: STRING
          pipelineparam--train_budget_milli_node_hours:
            type: DOUBLE
          pipelineparam--training_fraction:
            type: DOUBLE
          pipelineparam--transform_dataflow_disk_size_gb:
            type: INT
          pipelineparam--transform_dataflow_machine_type:
            type: STRING
          pipelineparam--transform_dataflow_max_num_workers:
            type: INT
          pipelineparam--transformations:
            type: STRING
          pipelineparam--validation_fraction:
            type: DOUBLE
          pipelineparam--weight_column:
            type: 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:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_workers_num:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          dataflow_workers_num:
            type: INT
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: STRING
      outputDefinitions:
        artifacts:
          feature_attributions:
            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: 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:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_workers_num:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          dataflow_workers_num:
            type: INT
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: STRING
      outputDefinitions:
        artifacts:
          feature_attributions:
            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: 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:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_workers_num:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          dataflow_workers_num:
            type: INT
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: STRING
      outputDefinitions:
        artifacts:
          feature_attributions:
            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: STRING
    comp-importer:
      executorLabel: exec-importer
      inputDefinitions:
        parameters:
          uri:
            type: 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:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: 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:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: 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:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: 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:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: 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:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: STRING
    comp-model-batch-predict-3:
      executorLabel: exec-model-batch-predict-3
      inputDefinitions:
        artifacts:
          model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          accelerator_count:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: STRING
    comp-model-batch-predict-4:
      executorLabel: exec-model-batch-predict-4
      inputDefinitions:
        artifacts:
          model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          accelerator_count:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: 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:
            type: INT
          accelerator_type:
            type: STRING
          bigquery_destination_output_uri:
            type: STRING
          bigquery_source_input_uri:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          gcs_destination_output_uri_prefix:
            type: STRING
          gcs_source_uris:
            type: STRING
          generate_explanation:
            type: STRING
          instances_format:
            type: STRING
          job_display_name:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          machine_type:
            type: STRING
          manual_batch_tuning_parameters_batch_size:
            type: INT
          max_replica_count:
            type: INT
          model_parameters:
            type: STRING
          predictions_format:
            type: STRING
          project:
            type: STRING
          starting_replica_count:
            type: INT
      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:
            type: STRING
    comp-model-evaluation:
      executorLabel: exec-model-evaluation
      inputDefinitions:
        artifacts:
          batch_prediction_job:
            artifactType:
              schemaTitle: google.VertexBatchPredictionJob
              schemaVersion: 0.0.1
        parameters:
          class_names:
            type: STRING
          classification_type:
            type: STRING
          dataflow_disk_size:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_workers_num:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          dataflow_workers_num:
            type: INT
          encryption_spec_key_name:
            type: STRING
          example_weight_column:
            type: STRING
          generate_feature_attribution:
            type: STRING
          ground_truth_column:
            type: STRING
          ground_truth_format:
            type: STRING
          ground_truth_gcs_source:
            type: STRING
          key_columns:
            type: STRING
          location:
            type: STRING
          positive_classes:
            type: STRING
          prediction_id_column:
            type: STRING
          prediction_label_column:
            type: STRING
          prediction_score_column:
            type: STRING
          predictions_format:
            type: STRING
          problem_type:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: STRING
      outputDefinitions:
        artifacts:
          evaluation_metrics:
            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: STRING
    comp-model-evaluation-2:
      executorLabel: exec-model-evaluation-2
      inputDefinitions:
        artifacts:
          batch_prediction_job:
            artifactType:
              schemaTitle: google.VertexBatchPredictionJob
              schemaVersion: 0.0.1
        parameters:
          class_names:
            type: STRING
          classification_type:
            type: STRING
          dataflow_disk_size:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_workers_num:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          dataflow_workers_num:
            type: INT
          encryption_spec_key_name:
            type: STRING
          example_weight_column:
            type: STRING
          generate_feature_attribution:
            type: STRING
          ground_truth_column:
            type: STRING
          ground_truth_format:
            type: STRING
          ground_truth_gcs_source:
            type: STRING
          key_columns:
            type: STRING
          location:
            type: STRING
          positive_classes:
            type: STRING
          prediction_id_column:
            type: STRING
          prediction_label_column:
            type: STRING
          prediction_score_column:
            type: STRING
          predictions_format:
            type: STRING
          problem_type:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: STRING
      outputDefinitions:
        artifacts:
          evaluation_metrics:
            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: STRING
    comp-model-evaluation-3:
      executorLabel: exec-model-evaluation-3
      inputDefinitions:
        artifacts:
          batch_prediction_job:
            artifactType:
              schemaTitle: google.VertexBatchPredictionJob
              schemaVersion: 0.0.1
        parameters:
          class_names:
            type: STRING
          classification_type:
            type: STRING
          dataflow_disk_size:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_workers_num:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          dataflow_workers_num:
            type: INT
          encryption_spec_key_name:
            type: STRING
          example_weight_column:
            type: STRING
          generate_feature_attribution:
            type: STRING
          ground_truth_column:
            type: STRING
          ground_truth_format:
            type: STRING
          ground_truth_gcs_source:
            type: STRING
          key_columns:
            type: STRING
          location:
            type: STRING
          positive_classes:
            type: STRING
          prediction_id_column:
            type: STRING
          prediction_label_column:
            type: STRING
          prediction_score_column:
            type: STRING
          predictions_format:
            type: STRING
          problem_type:
            type: STRING
          project:
            type: STRING
          root_dir:
            type: STRING
      outputDefinitions:
        artifacts:
          evaluation_metrics:
            artifactType:
              schemaTitle: system.Metrics
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: 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_path:
            type: STRING
          dataset_paths:
            type: STRING
          dataset_type:
            type: STRING
          display_name:
            type: STRING
          problem_type:
            type: STRING
      outputDefinitions:
        parameters:
          gcp_resources:
            type: 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_path:
            type: STRING
          dataset_paths:
            type: STRING
          dataset_type:
            type: STRING
          display_name:
            type: STRING
          problem_type:
            type: STRING
      outputDefinitions:
        parameters:
          gcp_resources:
            type: 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_path:
            type: STRING
          dataset_paths:
            type: STRING
          dataset_type:
            type: STRING
          display_name:
            type: STRING
          problem_type:
            type: STRING
      outputDefinitions:
        parameters:
          gcp_resources:
            type: STRING
    comp-model-upload:
      executorLabel: exec-model-upload
      inputDefinitions:
        artifacts:
          unmanaged_container_model:
            artifactType:
              schemaTitle: google.UnmanagedContainerModel
              schemaVersion: 0.0.1
        parameters:
          description:
            type: STRING
          display_name:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
      outputDefinitions:
        artifacts:
          model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: 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:
            type: STRING
          display_name:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
      outputDefinitions:
        artifacts:
          model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: 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:
            type: STRING
          display_name:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
      outputDefinitions:
        artifacts:
          model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: STRING
    comp-model-upload-4:
      executorLabel: exec-model-upload-4
      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:
            type: STRING
          display_name:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          explanation_metadata:
            type: STRING
          explanation_parameters:
            type: STRING
          labels:
            type: STRING
          location:
            type: STRING
          project:
            type: STRING
      outputDefinitions:
        artifacts:
          model:
            artifactType:
              schemaTitle: google.VertexModel
              schemaVersion: 0.0.1
        parameters:
          gcp_resources:
            type: 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:
            type: STRING
    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:
            type: STRING
    comp-set-model-can-skip-validation:
      executorLabel: exec-set-model-can-skip-validation
      inputDefinitions:
        artifacts:
          model:
            artifactType:
              schemaTitle: system.Artifact
              schemaVersion: 0.0.1
    comp-string-not-empty:
      executorLabel: exec-string-not-empty
      inputDefinitions:
        parameters:
          value:
            type: STRING
      outputDefinitions:
        parameters:
          Output:
            type: STRING
    comp-tabular-stats-and-example-gen:
      executorLabel: exec-tabular-stats-and-example-gen
      inputDefinitions:
        parameters:
          additional_experiments:
            type: STRING
          additional_experiments_json:
            type: STRING
          data_source_bigquery_table_path:
            type: STRING
          data_source_csv_filenames:
            type: STRING
          dataflow_disk_size_gb:
            type: INT
          dataflow_machine_type:
            type: STRING
          dataflow_max_num_workers:
            type: INT
          dataflow_service_account:
            type: STRING
          dataflow_subnetwork:
            type: STRING
          dataflow_use_public_ips:
            type: STRING
          enable_probabilistic_inference:
            type: STRING
          encryption_spec_key_name:
            type: STRING
          location:
            type: STRING
          optimization_objective:
            type: STRING
          optimization_objective_precision_value:
            type: DOUBLE
          optimization_objective_recall_value:
            type: DOUBLE
          predefined_split_key:
            type: STRING
          prediction_type:
            type: STRING
          project:
            type: STRING
          quantiles:
            type: STRING
          request_type:
            type: STRING
          root_dir:
            type: STRING
          run_distillation:
            type: STRING
          stratified_split_key:
            type: STRING
          target_column_name:
            type: STRING
          test_fraction:
            type: DOUBLE
          timestamp_split_key:
            type: STRING
          training_fraction:
            type: DOUBLE
          transformations:
            type: STRING
          transformations_path:
            type: STRING
          validation_fraction:
            type: DOUBLE
          weight_column_name:
            type: 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:
            type: STRING
          gcp_resources:
            type: STRING
          test_split_json:
            type: STRING
    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
          - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
          - --payload
          - '{"display_name": "automl-tabular-cv-tuner-{{$.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:20230110_1125_RC00",
            "args": ["l2l_cv_tuner", "--transform_output_path={{$.inputs.artifacts[''transform_output''].uri}}",
            "--training_docker_uri=us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "--component_id={{$.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
          - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
          - --payload
          - '{"display_name": "automl-tabular-cv-tuner-{{$.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:20230110_1125_RC00",
            "args": ["l2l_cv_tuner", "--transform_output_path={{$.inputs.artifacts[''transform_output''].uri}}",
            "--training_docker_uri=us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "--component_id={{$.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
          - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
          - --payload
          - '{"display_name": "automl-tabular-ensemble-{{$.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:20230110_1125_RC00",
            "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:20230110_1125_RC00",
            "--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
          - '{"display_name": "automl-tabular-ensemble-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
            "encryption_spec": {"kms_key_name":"{{$.inputs.parameters[''encryption_spec_key_name'']}}"},
            "job_spec": {"worker_pool_specs": [{"replica_count": 1, "machine_spec":
            {"machine_type": "n1-highmem-8"}, "container_spec": {"image_uri":"us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "args": ["ensemble", "--transform_output_path={{$.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={{$.inputs.artifacts[''warmup_data''].uri}}", "--prediction_docker_uri=us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:20230110_1125_RC00",
            "--model_path={{$.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
          - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
          - --payload
          - '{"display_name": "automl-tabular-ensemble-{{$.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:20230110_1125_RC00",
            "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:20230110_1125_RC00",
            "--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
          - '{"display_name": "automl-tabular-finalizer-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
            "encryption_spec": {"kms_key_name":"{{$.inputs.parameters[''encryption_spec_key_name'']}}"},
            "job_spec": {"worker_pool_specs": [{"replica_count": 1, "machine_spec":
            {"machine_type": "n1-standard-8"}, "container_spec": {"image_uri":"us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "args": ["cancel_l2l_tuner", "--error_file_path={{$.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
          - '{{$}}'
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:20230110_1125_RC00
          resources:
            cpuLimit: 8.0
            memoryLimit: 52.0
      exec-automl-tabular-infra-validator-2:
        container:
          args:
          - --executor_input
          - '{{$}}'
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:20230110_1125_RC00
          resources:
            cpuLimit: 8.0
            memoryLimit: 52.0
      exec-automl-tabular-infra-validator-3:
        container:
          args:
          - --executor_input
          - '{{$}}'
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:20230110_1125_RC00
          resources:
            cpuLimit: 8.0
            memoryLimit: 52.0
      exec-automl-tabular-stage-1-tuner:
        container:
          args:
          - --type
          - CustomJob
          - --project
          - '{{$.inputs.parameters[''project'']}}'
          - --location
          - '{{$.inputs.parameters[''location'']}}'
          - --gcp_resources
          - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
          - --payload
          - '{"display_name": "automl-tabular-stage-1-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
            "encryption_spec": {"kms_key_name":"{{$.inputs.parameters[''encryption_spec_key_name'']}}"},
            "job_spec": {"worker_pool_specs": [{"replica_count": 1, "machine_spec":
            {"machine_type": "n1-standard-8"}, "container_spec": {"image_uri":"us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "args": ["l2l_stage_1_tuner", "--transform_output_path={{$.inputs.artifacts[''transform_output''].uri}}",
            "--training_docker_uri=us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "--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
          - '{"display_name": "automl-tabular-stage-1-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
            "encryption_spec": {"kms_key_name":"{{$.inputs.parameters[''encryption_spec_key_name'']}}"},
            "job_spec": {"worker_pool_specs": [{"replica_count": 1, "machine_spec":
            {"machine_type": "n1-standard-8"}, "container_spec": {"image_uri":"us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "args": ["l2l_stage_1_tuner", "--transform_output_path={{$.inputs.artifacts[''transform_output''].uri}}",
            "--training_docker_uri=us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "--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
          - '{"display_name": "automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
            "encryption_spec": {"kms_key_name":"{{$.inputs.parameters[''encryption_spec_key_name'']}}"},
            "job_spec": {"worker_pool_specs": [{"replica_count": 1, "machine_spec":
            {"machine_type": "n1-standard-8"}, "container_spec": {"image_uri":"us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "args": ["transform", "--transform_output_artifact_path={{$.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={{$.inputs.parameters[''dataflow_machine_type'']}}",
            "--dataflow_worker_container_image=us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00",
            "--dataflow_disk_size_gb={{$.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
          - '{"display_name": "automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}",
            "encryption_spec": {"kms_key_name":"{{$.inputs.parameters[''encryption_spec_key_name'']}}"},
            "job_spec": {"worker_pool_specs": [{"replica_count": 1, "machine_spec":
            {"machine_type": "n1-standard-8"}, "container_spec": {"image_uri":"us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:20230110_1125_RC00",
            "args": ["transform", "--transform_output_artifact_path={{$.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={{$.inputs.parameters[''dataflow_machine_type'']}}",
            "--dataflow_worker_container_image=us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00",
            "--dataflow_disk_size_gb={{$.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={{$.outputs.parameters[''gcp_resources''].output_file}}"]}}]}}'
          command:
          - python3
          - -u
          - -m
          - google_cloud_pipeline_components.container.v1.custom_job.launcher
          image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
      exec-bool-identity:
        container:
          args:
          - --value
          - '{{$.inputs.parameters[''value'']}}'
          - '----output-paths'
          - '{{$.outputs.parameters[''Output''].output_file}}'
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp)

            printf "%s" "$0" > "$program_path"

            python3 -u "$program_path" "$@"

            '
          - "def _bool_identity(value):\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\ndef _deserialize_bool(s)\
            \ -> bool:\n    from distutils.util import strtobool\n    return strtobool(s)\
            \ == 1\n\ndef _serialize_str(str_value: str) -> str:\n    if not isinstance(str_value,\
            \ str):\n        raise TypeError('Value \"{}\" has type \"{}\" instead\
            \ of str.'.format(\n            str(str_value), str(type(str_value))))\n\
            \    return str_value\n\nimport argparse\n_parser = argparse.ArgumentParser(prog='Bool\
            \ identity', description='Returns boolean value.')\n_parser.add_argument(\"\
            --value\", dest=\"value\", type=_deserialize_bool, required=True, default=argparse.SUPPRESS)\n\
            _parser.add_argument(\"----output-paths\", dest=\"_output_paths\", type=str,\
            \ nargs=1)\n_parsed_args = vars(_parser.parse_args())\n_output_files =\
            \ _parsed_args.pop(\"_output_paths\", [])\n\n_outputs = _bool_identity(**_parsed_args)\n\
            \n_outputs = [_outputs]\n\n_output_serializers = [\n    _serialize_str,\n\
            \n]\n\nimport os\nfor idx, output_file in enumerate(_output_files):\n\
            \    try:\n        os.makedirs(os.path.dirname(output_file))\n    except\
            \ OSError:\n        pass\n    with open(output_file, 'w') as f:\n    \
            \    f.write(_output_serializers[idx](_outputs[idx]))\n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      exec-bool-identity-2:
        container:
          args:
          - --value
          - '{{$.inputs.parameters[''value'']}}'
          - '----output-paths'
          - '{{$.outputs.parameters[''Output''].output_file}}'
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp)

            printf "%s" "$0" > "$program_path"

            python3 -u "$program_path" "$@"

            '
          - "def _bool_identity(value):\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\ndef _deserialize_bool(s)\
            \ -> bool:\n    from distutils.util import strtobool\n    return strtobool(s)\
            \ == 1\n\ndef _serialize_str(str_value: str) -> str:\n    if not isinstance(str_value,\
            \ str):\n        raise TypeError('Value \"{}\" has type \"{}\" instead\
            \ of str.'.format(\n            str(str_value), str(type(str_value))))\n\
            \    return str_value\n\nimport argparse\n_parser = argparse.ArgumentParser(prog='Bool\
            \ identity', description='Returns boolean value.')\n_parser.add_argument(\"\
            --value\", dest=\"value\", type=_deserialize_bool, required=True, default=argparse.SUPPRESS)\n\
            _parser.add_argument(\"----output-paths\", dest=\"_output_paths\", type=str,\
            \ nargs=1)\n_parsed_args = vars(_parser.parse_args())\n_output_files =\
            \ _parsed_args.pop(\"_output_paths\", [])\n\n_outputs = _bool_identity(**_parsed_args)\n\
            \n_outputs = [_outputs]\n\n_output_serializers = [\n    _serialize_str,\n\
            \n]\n\nimport os\nfor idx, output_file in enumerate(_output_files):\n\
            \    try:\n        os.makedirs(os.path.dirname(output_file))\n    except\
            \ OSError:\n        pass\n    with open(output_file, 'w') as f:\n    \
            \    f.write(_output_serializers[idx](_outputs[idx]))\n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      exec-bool-identity-3:
        container:
          args:
          - --value
          - '{{$.inputs.parameters[''value'']}}'
          - '----output-paths'
          - '{{$.outputs.parameters[''Output''].output_file}}'
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp)

            printf "%s" "$0" > "$program_path"

            python3 -u "$program_path" "$@"

            '
          - "def _bool_identity(value):\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\ndef _deserialize_bool(s)\
            \ -> bool:\n    from distutils.util import strtobool\n    return strtobool(s)\
            \ == 1\n\ndef _serialize_str(str_value: str) -> str:\n    if not isinstance(str_value,\
            \ str):\n        raise TypeError('Value \"{}\" has type \"{}\" instead\
            \ of str.'.format(\n            str(str_value), str(type(str_value))))\n\
            \    return str_value\n\nimport argparse\n_parser = argparse.ArgumentParser(prog='Bool\
            \ identity', description='Returns boolean value.')\n_parser.add_argument(\"\
            --value\", dest=\"value\", type=_deserialize_bool, required=True, default=argparse.SUPPRESS)\n\
            _parser.add_argument(\"----output-paths\", dest=\"_output_paths\", type=str,\
            \ nargs=1)\n_parsed_args = vars(_parser.parse_args())\n_output_files =\
            \ _parsed_args.pop(\"_output_paths\", [])\n\n_outputs = _bool_identity(**_parsed_args)\n\
            \n_outputs = [_outputs]\n\n_output_serializers = [\n    _serialize_str,\n\
            \n]\n\nimport os\nfor idx, output_file in enumerate(_output_files):\n\
            \    try:\n        os.makedirs(os.path.dirname(output_file))\n    except\
            \ OSError:\n        pass\n    with open(output_file, 'w') as f:\n    \
            \    f.write(_output_serializers[idx](_outputs[idx]))\n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      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.v2.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

            '
          - "\nimport kfp\nfrom kfp.v2 import dsl\nfrom kfp.v2.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/dataflow-worker:20230110_1125_RC00
      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.v2.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

            '
          - "\nimport kfp\nfrom kfp.v2 import dsl\nfrom kfp.v2.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/dataflow-worker:20230110_1125_RC00
      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
          - '{{$.inputs.parameters[''root_dir'']}}/{{$.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
          - '{{$.inputs.parameters[''root_dir'']}}/{{$.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
          - '{{$.inputs.parameters[''root_dir'']}}/{{$.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-importer:
        importer:
          artifactUri:
            runtimeParameter: uri
          typeSchema:
            schemaTitle: system.Artifact
            schemaVersion: 0.0.1
      exec-merge-materialized-splits:
        container:
          args:
          - --split-0
          - '{{$.inputs.artifacts[''split_0''].path}}'
          - --split-1
          - '{{$.inputs.artifacts[''split_1''].path}}'
          - --splits
          - '{{$.outputs.artifacts[''splits''].path}}'
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp)

            printf "%s" "$0" > "$program_path"

            python3 -u "$program_path" "$@"

            '
          - "def _make_parent_dirs_and_return_path(file_path: str):\n    import os\n\
            \    os.makedirs(os.path.dirname(file_path), exist_ok=True)\n    return\
            \ file_path\n\ndef _merge_materialized_splits(\n    split_0,\n    split_1,\n\
            \    splits,\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\
            import argparse\n_parser = argparse.ArgumentParser(prog='Merge materialized\
            \ splits', description='Merge two materialized splits.')\n_parser.add_argument(\"\
            --split-0\", dest=\"split_0\", type=str, required=True, default=argparse.SUPPRESS)\n\
            _parser.add_argument(\"--split-1\", dest=\"split_1\", type=str, required=True,\
            \ default=argparse.SUPPRESS)\n_parser.add_argument(\"--splits\", dest=\"\
            splits\", type=_make_parent_dirs_and_return_path, required=True, default=argparse.SUPPRESS)\n\
            _parsed_args = vars(_parser.parse_args())\n\n_outputs = _merge_materialized_splits(**_parsed_args)\n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      exec-model-batch-explanation:
        container:
          args:
          - --type
          - BatchPredictionJob
          - --payload
          - '{"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
          - '{"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
          - '{"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
          - '{"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
          - '{{$}}'
          command:
          - python3
          - -u
          - -m
          - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher
          image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32
      exec-model-batch-predict-2:
        container:
          args:
          - --type
          - BatchPredictionJob
          - --payload
          - '{"display_name": "{{$.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
          - '{"display_name": "{{$.inputs.parameters[''job_display_name'']}}", "model":
            "{{$.inputs.artifacts[''model''].metadata[''resourceName'']}}", "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
          - '{"display_name": "{{$.inputs.parameters[''job_display_name'']}}", "model":
            "{{$.inputs.artifacts[''model''].metadata[''resourceName'']}}", "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
          - '{"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
          - '{{$.inputs.parameters[''ground_truth_format'']}}'
          - --ground_truth_gcs_source
          - '{{$.inputs.parameters[''ground_truth_gcs_source'']}}'
          - --key_prefix_in_prediction_dataset
          - instance
          - --key_columns
          - '{{$.inputs.parameters[''key_columns'']}}'
          - --root_dir
          - '{{$.inputs.parameters[''root_dir'']}}/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}'
          - --classification_type
          - '{{$.inputs.parameters[''classification_type'']}}'
          - --class_names
          - '{{$.inputs.parameters[''class_names'']}}'
          - --ground_truth_column
          - instance.{{$.inputs.parameters['ground_truth_column']}}
          - --prediction_score_column
          - '{{$.inputs.parameters[''prediction_score_column'']}}'
          - --prediction_label_column
          - '{{$.inputs.parameters[''prediction_label_column'']}}'
          - --prediction_id_column
          - '{{$.inputs.parameters[''prediction_id_column'']}}'
          - --example_weight_column
          - '{{$.inputs.parameters[''example_weight_column'']}}'
          - --positive_classes
          - '{{$.inputs.parameters[''positive_classes'']}}'
          - --generate_feature_attribution
          - '{{$.inputs.parameters[''generate_feature_attribution'']}}'
          - --dataflow_job_prefix
          - evaluation-{{$.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'']}}'
          - --ground_truth_gcs_source
          - '{{$.inputs.parameters[''ground_truth_gcs_source'']}}'
          - --key_prefix_in_prediction_dataset
          - instance
          - --key_columns
          - '{{$.inputs.parameters[''key_columns'']}}'
          - --root_dir
          - '{{$.inputs.parameters[''root_dir'']}}/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}'
          - --classification_type
          - '{{$.inputs.parameters[''classification_type'']}}'
          - --class_names
          - '{{$.inputs.parameters[''class_names'']}}'
          - --ground_truth_column
          - instance.{{$.inputs.parameters['ground_truth_column']}}
          - --prediction_score_column
          - '{{$.inputs.parameters[''prediction_score_column'']}}'
          - --prediction_label_column
          - '{{$.inputs.parameters[''prediction_label_column'']}}'
          - --prediction_id_column
          - '{{$.inputs.parameters[''prediction_id_column'']}}'
          - --example_weight_column
          - '{{$.inputs.parameters[''example_weight_column'']}}'
          - --positive_classes
          - '{{$.inputs.parameters[''positive_classes'']}}'
          - --generate_feature_attribution
          - '{{$.inputs.parameters[''generate_feature_attribution'']}}'
          - --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
          - '{{$.inputs.parameters[''ground_truth_format'']}}'
          - --ground_truth_gcs_source
          - '{{$.inputs.parameters[''ground_truth_gcs_source'']}}'
          - --key_prefix_in_prediction_dataset
          - instance
          - --key_columns
          - '{{$.inputs.parameters[''key_columns'']}}'
          - --root_dir
          - '{{$.inputs.parameters[''root_dir'']}}/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}'
          - --classification_type
          - '{{$.inputs.parameters[''classification_type'']}}'
          - --class_names
          - '{{$.inputs.parameters[''class_names'']}}'
          - --ground_truth_column
          - instance.{{$.inputs.parameters['ground_truth_column']}}
          - --prediction_score_column
          - '{{$.inputs.parameters[''prediction_score_column'']}}'
          - --prediction_label_column
          - '{{$.inputs.parameters[''prediction_label_column'']}}'
          - --prediction_id_column
          - '{{$.inputs.parameters[''prediction_id_column'']}}'
          - --example_weight_column
          - '{{$.inputs.parameters[''example_weight_column'']}}'
          - --positive_classes
          - '{{$.inputs.parameters[''positive_classes'']}}'
          - --generate_feature_attribution
          - '{{$.inputs.parameters[''generate_feature_attribution'']}}'
          - --dataflow_job_prefix
          - evaluation-{{$.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
          - '{{$.inputs.parameters[''display_name'']}}'
          - --dataset_path
          - '{{$.inputs.parameters[''dataset_path'']}}'
          - --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
          - '{{$.inputs.parameters[''display_name'']}}'
          - --dataset_path
          - '{{$.inputs.parameters[''dataset_path'']}}'
          - --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
          - '{{$.inputs.parameters[''display_name'']}}'
          - --dataset_path
          - '{{$.inputs.parameters[''dataset_path'']}}'
          - --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
          - '{"display_name": "{{$.inputs.parameters[''display_name'']}}", "description":
            "{{$.inputs.parameters[''description'']}}", "explanation_spec": {"parameters":
            {{$.inputs.parameters[''explanation_parameters'']}}, "metadata": {{$.inputs.parameters[''explanation_metadata'']}}},
            "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
          - '{"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
          - '{{$}}'
          command:
          - python3
          - -u
          - -m
          - launcher
          image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
      exec-model-upload-3:
        container:
          args:
          - --type
          - UploadModel
          - --payload
          - '{"display_name": "{{$.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-4:
        container:
          args:
          - --type
          - UploadModel
          - --payload
          - '{"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
          - '{{$}}'
          command:
          - python3
          - -u
          - -m
          - launcher
          image: gcr.io/ml-pipeline/automl-tables-private:1.0.13
      exec-read-input-uri:
        container:
          args:
          - --split-uri
          - '{{$.inputs.artifacts[''split_uri''].path}}'
          - '----output-paths'
          - '{{$.outputs.parameters[''Output''].output_file}}'
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp)

            printf "%s" "$0" > "$program_path"

            python3 -u "$program_path" "$@"

            '
          - "def _read_input_uri(split_uri):\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\
            def _serialize_json(obj) -> str:\n    if isinstance(obj, str):\n     \
            \   return obj\n    import json\n\n    def default_serializer(obj):\n\
            \        if hasattr(obj, 'to_struct'):\n            return obj.to_struct()\n\
            \        else:\n            raise TypeError(\n                \"Object\
            \ of type '%s' is not JSON serializable and does not have .to_struct()\
            \ method.\"\n                % obj.__class__.__name__)\n\n    return json.dumps(obj,\
            \ default=default_serializer, sort_keys=True)\n\nimport argparse\n_parser\
            \ = argparse.ArgumentParser(prog='Read input uri', description='Construct\
            \ Dataset based on the batch prediction job.')\n_parser.add_argument(\"\
            --split-uri\", dest=\"split_uri\", type=str, required=True, default=argparse.SUPPRESS)\n\
            _parser.add_argument(\"----output-paths\", dest=\"_output_paths\", type=str,\
            \ nargs=1)\n_parsed_args = vars(_parser.parse_args())\n_output_files =\
            \ _parsed_args.pop(\"_output_paths\", [])\n\n_outputs = _read_input_uri(**_parsed_args)\n\
            \n_outputs = [_outputs]\n\n_output_serializers = [\n    _serialize_json,\n\
            \n]\n\nimport os\nfor idx, output_file in enumerate(_output_files):\n\
            \    try:\n        os.makedirs(os.path.dirname(output_file))\n    except\
            \ OSError:\n        pass\n    with open(output_file, 'w') as f:\n    \
            \    f.write(_output_serializers[idx](_outputs[idx]))\n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      exec-read-input-uri-2:
        container:
          args:
          - --split-uri
          - '{{$.inputs.artifacts[''split_uri''].path}}'
          - '----output-paths'
          - '{{$.outputs.parameters[''Output''].output_file}}'
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp)

            printf "%s" "$0" > "$program_path"

            python3 -u "$program_path" "$@"

            '
          - "def _read_input_uri(split_uri):\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\
            def _serialize_json(obj) -> str:\n    if isinstance(obj, str):\n     \
            \   return obj\n    import json\n\n    def default_serializer(obj):\n\
            \        if hasattr(obj, 'to_struct'):\n            return obj.to_struct()\n\
            \        else:\n            raise TypeError(\n                \"Object\
            \ of type '%s' is not JSON serializable and does not have .to_struct()\
            \ method.\"\n                % obj.__class__.__name__)\n\n    return json.dumps(obj,\
            \ default=default_serializer, sort_keys=True)\n\nimport argparse\n_parser\
            \ = argparse.ArgumentParser(prog='Read input uri', description='Construct\
            \ Dataset based on the batch prediction job.')\n_parser.add_argument(\"\
            --split-uri\", dest=\"split_uri\", type=str, required=True, default=argparse.SUPPRESS)\n\
            _parser.add_argument(\"----output-paths\", dest=\"_output_paths\", type=str,\
            \ nargs=1)\n_parsed_args = vars(_parser.parse_args())\n_output_files =\
            \ _parsed_args.pop(\"_output_paths\", [])\n\n_outputs = _read_input_uri(**_parsed_args)\n\
            \n_outputs = [_outputs]\n\n_output_serializers = [\n    _serialize_json,\n\
            \n]\n\nimport os\nfor idx, output_file in enumerate(_output_files):\n\
            \    try:\n        os.makedirs(os.path.dirname(output_file))\n    except\
            \ OSError:\n        pass\n    with open(output_file, 'w') as f:\n    \
            \    f.write(_output_serializers[idx](_outputs[idx]))\n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      exec-set-model-can-skip-validation:
        container:
          args:
          - --executor_input
          - '{{$}}'
          - --function_to_execute
          - _set_model_can_skip_validation
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp -d)

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

            python3 -m kfp.v2.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

            '
          - "\nimport kfp\nfrom kfp.v2 import dsl\nfrom kfp.v2.dsl import *\nfrom\
            \ typing import *\n\ndef _set_model_can_skip_validation(model: Input[Artifact]):\n\
            \  \"\"\"Construct Dataset based on the batch prediction job.\n\n  Args:\n\
            \    model: The model artifact.\n  \"\"\"\n  # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
            \  import os\n  import tensorflow as tf\n  # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\
            \n  # create an empty CAN_SKIP_VALIDATION file\n  with tf.io.gfile.GFile(os.path.join(model.uri,\
            \ 'CAN_SKIP_VALIDATION'),\n                         'w') as f:\n    f.write('')\n\
            \n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      exec-string-not-empty:
        container:
          args:
          - --value
          - '{{$.inputs.parameters[''value'']}}'
          - '----output-paths'
          - '{{$.outputs.parameters[''Output''].output_file}}'
          command:
          - sh
          - -ec
          - 'program_path=$(mktemp)

            printf "%s" "$0" > "$program_path"

            python3 -u "$program_path" "$@"

            '
          - "def _string_not_empty(value):\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\ndef _serialize_str(str_value:\
            \ str) -> str:\n    if not isinstance(str_value, str):\n        raise\
            \ TypeError('Value \"{}\" has type \"{}\" instead of str.'.format(\n \
            \           str(str_value), str(type(str_value))))\n    return str_value\n\
            \nimport argparse\n_parser = argparse.ArgumentParser(prog='String not\
            \ empty', description='Check if the input string value is not empty.')\n\
            _parser.add_argument(\"--value\", dest=\"value\", type=str, required=True,\
            \ default=argparse.SUPPRESS)\n_parser.add_argument(\"----output-paths\"\
            , dest=\"_output_paths\", type=str, nargs=1)\n_parsed_args = vars(_parser.parse_args())\n\
            _output_files = _parsed_args.pop(\"_output_paths\", [])\n\n_outputs =\
            \ _string_not_empty(**_parsed_args)\n\n_outputs = [_outputs]\n\n_output_serializers\
            \ = [\n    _serialize_str,\n\n]\n\nimport os\nfor idx, output_file in\
            \ enumerate(_output_files):\n    try:\n        os.makedirs(os.path.dirname(output_file))\n\
            \    except OSError:\n        pass\n    with open(output_file, 'w') as\
            \ f:\n        f.write(_output_serializers[idx](_outputs[idx]))\n"
          image: us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00
      exec-tabular-stats-and-example-gen:
        container:
          args:
          - --type
          - CustomJob
          - --project
          - '{{$.inputs.parameters[''project'']}}'
          - --location
          - '{{$.inputs.parameters[''location'']}}'
          - --gcp_resources
          - '{{$.outputs.parameters[''gcp_resources''].output_file}}'
          - --payload
          - '{"display_name": "tabular-stats-and-example-gen-{{$.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:20230110_1125_RC00",
            "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'']}}",
            "--split_spec=", "--data_source=", "--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={{$.inputs.parameters[''dataflow_max_num_workers'']}}",
            "--dataflow_worker_container_image=us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:20230110_1125_RC00",
            "--dataflow_machine_type={{$.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.v2.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

            '
          - "\nimport kfp\nfrom kfp.v2 import dsl\nfrom kfp.v2.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/dataflow-worker:20230110_1125_RC00
      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.v2.components.executor_main                         --component_module_path                         "$program_path/ephemeral_component.py"                         "$@"

            '
          - "\nimport kfp\nfrom kfp.v2 import dsl\nfrom kfp.v2.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/dataflow-worker:20230110_1125_RC00
  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:
          componentRef:
            name: comp-automl-tabular-finalizer
          dependentTasks:
          - exit-handler-1
          inputs:
            parameters:
              encryption_spec_key_name:
                runtimeValue:
                  constantValue:
                    stringValue: ''
              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
          inputs:
            parameters:
              pipelineparam--additional_experiments:
                componentInputParameter: additional_experiments
              pipelineparam--cv_trainer_worker_pool_specs_override:
                componentInputParameter: cv_trainer_worker_pool_specs_override
              pipelineparam--data_source_bigquery_table_path:
                componentInputParameter: data_source_bigquery_table_path
              pipelineparam--data_source_csv_filenames:
                componentInputParameter: data_source_csv_filenames
              pipelineparam--dataflow_service_account:
                componentInputParameter: dataflow_service_account
              pipelineparam--dataflow_subnetwork:
                componentInputParameter: dataflow_subnetwork
              pipelineparam--dataflow_use_public_ips:
                componentInputParameter: dataflow_use_public_ips
              pipelineparam--disable_early_stopping:
                componentInputParameter: disable_early_stopping
              pipelineparam--distill_batch_predict_machine_type:
                componentInputParameter: distill_batch_predict_machine_type
              pipelineparam--distill_batch_predict_max_replica_count:
                componentInputParameter: distill_batch_predict_max_replica_count
              pipelineparam--distill_batch_predict_starting_replica_count:
                componentInputParameter: distill_batch_predict_starting_replica_count
              pipelineparam--enable_probabilistic_inference:
                componentInputParameter: enable_probabilistic_inference
              pipelineparam--encryption_spec_key_name:
                componentInputParameter: encryption_spec_key_name
              pipelineparam--evaluation_batch_predict_machine_type:
                componentInputParameter: evaluation_batch_predict_machine_type
              pipelineparam--evaluation_batch_predict_max_replica_count:
                componentInputParameter: evaluation_batch_predict_max_replica_count
              pipelineparam--evaluation_batch_predict_starting_replica_count:
                componentInputParameter: evaluation_batch_predict_starting_replica_count
              pipelineparam--evaluation_dataflow_disk_size_gb:
                componentInputParameter: evaluation_dataflow_disk_size_gb
              pipelineparam--evaluation_dataflow_machine_type:
                componentInputParameter: evaluation_dataflow_machine_type
              pipelineparam--evaluation_dataflow_max_num_workers:
                componentInputParameter: evaluation_dataflow_max_num_workers
              pipelineparam--export_additional_model_without_custom_ops:
                componentInputParameter: export_additional_model_without_custom_ops
              pipelineparam--fast_testing:
                componentInputParameter: fast_testing
              pipelineparam--location:
                componentInputParameter: location
              pipelineparam--optimization_objective:
                componentInputParameter: optimization_objective
              pipelineparam--optimization_objective_precision_value:
                componentInputParameter: optimization_objective_precision_value
              pipelineparam--optimization_objective_recall_value:
                componentInputParameter: optimization_objective_recall_value
              pipelineparam--predefined_split_key:
                componentInputParameter: predefined_split_key
              pipelineparam--prediction_type:
                componentInputParameter: prediction_type
              pipelineparam--project:
                componentInputParameter: project
              pipelineparam--quantiles:
                componentInputParameter: quantiles
              pipelineparam--root_dir:
                componentInputParameter: root_dir
              pipelineparam--run_distillation:
                componentInputParameter: run_distillation
              pipelineparam--run_evaluation:
                componentInputParameter: run_evaluation
              pipelineparam--stage_1_num_parallel_trials:
                componentInputParameter: stage_1_num_parallel_trials
              pipelineparam--stage_1_tuner_worker_pool_specs_override:
                componentInputParameter: stage_1_tuner_worker_pool_specs_override
              pipelineparam--stage_1_tuning_result_artifact_uri:
                componentInputParameter: stage_1_tuning_result_artifact_uri
              pipelineparam--stage_2_num_parallel_trials:
                componentInputParameter: stage_2_num_parallel_trials
              pipelineparam--stage_2_num_selected_trials:
                componentInputParameter: stage_2_num_selected_trials
              pipelineparam--stats_and_example_gen_dataflow_disk_size_gb:
                componentInputParameter: stats_and_example_gen_dataflow_disk_size_gb
              pipelineparam--stats_and_example_gen_dataflow_machine_type:
                componentInputParameter: stats_and_example_gen_dataflow_machine_type
              pipelineparam--stats_and_example_gen_dataflow_max_num_workers:
                componentInputParameter: stats_and_example_gen_dataflow_max_num_workers
              pipelineparam--stratified_split_key:
                componentInputParameter: stratified_split_key
              pipelineparam--study_spec_parameters_override:
                componentInputParameter: study_spec_parameters_override
              pipelineparam--target_column:
                componentInputParameter: target_column
              pipelineparam--test_fraction:
                componentInputParameter: test_fraction
              pipelineparam--timestamp_split_key:
                componentInputParameter: timestamp_split_key
              pipelineparam--train_budget_milli_node_hours:
                componentInputParameter: train_budget_milli_node_hours
              pipelineparam--training_fraction:
                componentInputParameter: training_fraction
              pipelineparam--transform_dataflow_disk_size_gb:
                componentInputParameter: transform_dataflow_disk_size_gb
              pipelineparam--transform_dataflow_machine_type:
                componentInputParameter: transform_dataflow_machine_type
              pipelineparam--transform_dataflow_max_num_workers:
                componentInputParameter: transform_dataflow_max_num_workers
              pipelineparam--transformations:
                componentInputParameter: transformations
              pipelineparam--validation_fraction:
                componentInputParameter: validation_fraction
              pipelineparam--weight_column:
                componentInputParameter: weight_column
          taskInfo:
            name: exit-handler-1
    inputDefinitions:
      parameters:
        additional_experiments:
          type: STRING
        cv_trainer_worker_pool_specs_override:
          type: STRING
        data_source_bigquery_table_path:
          type: STRING
        data_source_csv_filenames:
          type: STRING
        dataflow_service_account:
          type: STRING
        dataflow_subnetwork:
          type: STRING
        dataflow_use_public_ips:
          type: STRING
        disable_early_stopping:
          type: STRING
        distill_batch_predict_machine_type:
          type: STRING
        distill_batch_predict_max_replica_count:
          type: INT
        distill_batch_predict_starting_replica_count:
          type: INT
        enable_probabilistic_inference:
          type: STRING
        encryption_spec_key_name:
          type: STRING
        evaluation_batch_predict_machine_type:
          type: STRING
        evaluation_batch_predict_max_replica_count:
          type: INT
        evaluation_batch_predict_starting_replica_count:
          type: INT
        evaluation_dataflow_disk_size_gb:
          type: INT
        evaluation_dataflow_machine_type:
          type: STRING
        evaluation_dataflow_max_num_workers:
          type: INT
        export_additional_model_without_custom_ops:
          type: STRING
        fast_testing:
          type: STRING
        location:
          type: STRING
        optimization_objective:
          type: STRING
        optimization_objective_precision_value:
          type: DOUBLE
        optimization_objective_recall_value:
          type: DOUBLE
        predefined_split_key:
          type: STRING
        prediction_type:
          type: STRING
        project:
          type: STRING
        quantiles:
          type: STRING
        root_dir:
          type: STRING
        run_distillation:
          type: STRING
        run_evaluation:
          type: STRING
        stage_1_num_parallel_trials:
          type: INT
        stage_1_tuner_worker_pool_specs_override:
          type: STRING
        stage_1_tuning_result_artifact_uri:
          type: STRING
        stage_2_num_parallel_trials:
          type: INT
        stage_2_num_selected_trials:
          type: INT
        stats_and_example_gen_dataflow_disk_size_gb:
          type: INT
        stats_and_example_gen_dataflow_machine_type:
          type: STRING
        stats_and_example_gen_dataflow_max_num_workers:
          type: INT
        stratified_split_key:
          type: STRING
        study_spec_parameters_override:
          type: STRING
        target_column:
          type: STRING
        test_fraction:
          type: DOUBLE
        timestamp_split_key:
          type: STRING
        train_budget_milli_node_hours:
          type: DOUBLE
        training_fraction:
          type: DOUBLE
        transform_dataflow_disk_size_gb:
          type: INT
        transform_dataflow_machine_type:
          type: STRING
        transform_dataflow_max_num_workers:
          type: INT
        transformations:
          type: STRING
        validation_fraction:
          type: DOUBLE
        weight_column:
          type: 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: 2.0.0
  sdkVersion: kfp-1.8.14
runtimeConfig:
  parameters:
    data_source_bigquery_table_path:
      stringValue: ''
    data_source_csv_filenames:
      stringValue: ''
    dataflow_service_account:
      stringValue: ''
    dataflow_subnetwork:
      stringValue: ''
    dataflow_use_public_ips:
      stringValue: 'True'
    disable_early_stopping:
      stringValue: 'False'
    distill_batch_predict_machine_type:
      stringValue: n1-standard-16
    distill_batch_predict_max_replica_count:
      intValue: '25'
    distill_batch_predict_starting_replica_count:
      intValue: '25'
    enable_probabilistic_inference:
      stringValue: 'False'
    encryption_spec_key_name:
      stringValue: ''
    evaluation_batch_predict_machine_type:
      stringValue: n1-standard-16
    evaluation_batch_predict_max_replica_count:
      intValue: '25'
    evaluation_batch_predict_starting_replica_count:
      intValue: '25'
    evaluation_dataflow_disk_size_gb:
      intValue: '50'
    evaluation_dataflow_machine_type:
      stringValue: n1-standard-4
    evaluation_dataflow_max_num_workers:
      intValue: '25'
    export_additional_model_without_custom_ops:
      stringValue: 'False'
    fast_testing:
      stringValue: 'False'
    optimization_objective_precision_value:
      doubleValue: -1.0
    optimization_objective_recall_value:
      doubleValue: -1.0
    predefined_split_key:
      stringValue: ''
    run_distillation:
      stringValue: 'False'
    run_evaluation:
      stringValue: 'False'
    stage_1_num_parallel_trials:
      intValue: '35'
    stage_1_tuning_result_artifact_uri:
      stringValue: ''
    stage_2_num_parallel_trials:
      intValue: '35'
    stage_2_num_selected_trials:
      intValue: '5'
    stats_and_example_gen_dataflow_disk_size_gb:
      intValue: '40'
    stats_and_example_gen_dataflow_machine_type:
      stringValue: n1-standard-16
    stats_and_example_gen_dataflow_max_num_workers:
      intValue: '25'
    stratified_split_key:
      stringValue: ''
    test_fraction:
      doubleValue: -1.0
    timestamp_split_key:
      stringValue: ''
    training_fraction:
      doubleValue: -1.0
    transform_dataflow_disk_size_gb:
      intValue: '40'
    transform_dataflow_machine_type:
      stringValue: n1-standard-16
    transform_dataflow_max_num_workers:
      intValue: '25'
    validation_fraction:
      doubleValue: -1.0
    weight_column:
      stringValue: ''