python/pipelines/automl_tabular_pl

# 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. # PIPELINE DEFINITION # Name: automl-tabular # Description: The AutoML Tabular pipeline v1. # Inputs: # additional_experiments: dict # cv_trainer_worker_pool_specs_override: list # data_source_bigquery_table_path: str [Default: ''] # data_source_csv_filenames: str [Default: ''] # dataflow_service_account: str [Default: ''] # dataflow_subnetwork: str [Default: ''] # dataflow_use_public_ips: bool [Default: True] # disable_early_stopping: bool [Default: False] # distill_batch_predict_machine_type: str [Default: 'n1-standard-16'] # distill_batch_predict_max_replica_count: int [Default: 25.0] # distill_batch_predict_starting_replica_count: int [Default: 25.0] # enable_probabilistic_inference: bool [Default: False] # encryption_spec_key_name: str [Default: ''] # evaluation_batch_explain_machine_type: str [Default: 'n1-highmem-8'] # evaluation_batch_explain_max_replica_count: int [Default: 10.0] # evaluation_batch_explain_starting_replica_count: int [Default: 10.0] # evaluation_batch_predict_machine_type: str [Default: 'n1-highmem-8'] # evaluation_batch_predict_max_replica_count: int [Default: 20.0] # evaluation_batch_predict_starting_replica_count: int [Default: 20.0] # evaluation_dataflow_disk_size_gb: int [Default: 50.0] # evaluation_dataflow_machine_type: str [Default: 'n1-standard-4'] # evaluation_dataflow_max_num_workers: int [Default: 100.0] # evaluation_dataflow_starting_num_workers: int [Default: 10.0] # export_additional_model_without_custom_ops: bool [Default: False] # fast_testing: bool [Default: False] # location: str # model_description: str [Default: ''] # model_display_name: str [Default: ''] # optimization_objective: str # optimization_objective_precision_value: float [Default: -1.0] # optimization_objective_recall_value: float [Default: -1.0] # predefined_split_key: str [Default: ''] # prediction_type: str # project: str # quantiles: list # root_dir: str # run_distillation: bool [Default: False] # run_evaluation: bool [Default: False] # stage_1_num_parallel_trials: int [Default: 35.0] # stage_1_tuner_worker_pool_specs_override: list # stage_1_tuning_result_artifact_uri: str [Default: ''] # stage_2_num_parallel_trials: int [Default: 35.0] # stage_2_num_selected_trials: int [Default: 5.0] # stats_and_example_gen_dataflow_disk_size_gb: int [Default: 40.0] # stats_and_example_gen_dataflow_machine_type: str [Default: 'n1-standard-16'] # stats_and_example_gen_dataflow_max_num_workers: int [Default: 25.0] # stratified_split_key: str [Default: ''] # study_spec_parameters_override: list # target_column: str # test_fraction: float [Default: -1.0] # timestamp_split_key: str [Default: ''] # train_budget_milli_node_hours: float # training_fraction: float [Default: -1.0] # transform_dataflow_disk_size_gb: int [Default: 40.0] # transform_dataflow_machine_type: str [Default: 'n1-standard-16'] # transform_dataflow_max_num_workers: int [Default: 25.0] # transformations: str # validation_fraction: float [Default: -1.0] # vertex_dataset: system.Artifact # weight_column: str [Default: ''] # Outputs: # feature-attribution-2-feature_attributions: system.Metrics # feature-attribution-3-feature_attributions: system.Metrics # feature-attribution-feature_attributions: system.Metrics # model-evaluation-2-evaluation_metrics: system.Metrics # model-evaluation-3-evaluation_metrics: system.Metrics # model-evaluation-evaluation_metrics: system.Metrics components: comp-automl-tabular-cv-trainer: executorLabel: exec-automl-tabular-cv-trainer inputDefinitions: artifacts: materialized_cv_splits: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 tuning_result_input: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: deadline_hours: parameterType: NUMBER_DOUBLE encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING num_parallel_trials: parameterType: NUMBER_INTEGER num_selected_features: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER num_selected_trials: parameterType: NUMBER_INTEGER project: parameterType: STRING root_dir: parameterType: STRING single_run_max_secs: parameterType: NUMBER_INTEGER worker_pool_specs_override_json: defaultValue: [] isOptional: true parameterType: LIST outputDefinitions: artifacts: tuning_result_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: execution_metrics: parameterType: STRUCT gcp_resources: parameterType: STRING comp-automl-tabular-cv-trainer-2: executorLabel: exec-automl-tabular-cv-trainer-2 inputDefinitions: artifacts: materialized_cv_splits: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 tuning_result_input: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: deadline_hours: parameterType: NUMBER_DOUBLE encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING num_parallel_trials: parameterType: NUMBER_INTEGER num_selected_features: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER num_selected_trials: parameterType: NUMBER_INTEGER project: parameterType: STRING root_dir: parameterType: STRING single_run_max_secs: parameterType: NUMBER_INTEGER worker_pool_specs_override_json: defaultValue: [] isOptional: true parameterType: LIST outputDefinitions: artifacts: tuning_result_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: execution_metrics: parameterType: STRUCT gcp_resources: parameterType: STRING comp-automl-tabular-ensemble: executorLabel: exec-automl-tabular-ensemble inputDefinitions: artifacts: dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 instance_baseline: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 tuning_result_input: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 warmup_data: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 isOptional: true parameters: encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING export_additional_model_without_custom_ops: defaultValue: false isOptional: true parameterType: BOOLEAN location: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model_architecture: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model_without_custom_ops: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 parameters: explanation_metadata: parameterType: STRUCT explanation_parameters: parameterType: STRUCT gcp_resources: parameterType: STRING comp-automl-tabular-ensemble-2: executorLabel: exec-automl-tabular-ensemble-2 inputDefinitions: artifacts: dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 instance_baseline: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 tuning_result_input: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 warmup_data: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 isOptional: true parameters: encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING export_additional_model_without_custom_ops: defaultValue: false isOptional: true parameterType: BOOLEAN location: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model_architecture: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model_without_custom_ops: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 parameters: explanation_metadata: parameterType: STRUCT explanation_parameters: parameterType: STRUCT gcp_resources: parameterType: STRING comp-automl-tabular-ensemble-3: executorLabel: exec-automl-tabular-ensemble-3 inputDefinitions: artifacts: dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 instance_baseline: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 tuning_result_input: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 warmup_data: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 isOptional: true parameters: encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING export_additional_model_without_custom_ops: defaultValue: false isOptional: true parameterType: BOOLEAN location: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model_architecture: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 model_without_custom_ops: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 parameters: explanation_metadata: parameterType: STRUCT explanation_parameters: parameterType: STRUCT gcp_resources: parameterType: STRING comp-automl-tabular-finalizer: executorLabel: exec-automl-tabular-finalizer inputDefinitions: parameters: encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: parameters: gcp_resources: parameterType: STRING comp-automl-tabular-infra-validator: executorLabel: exec-automl-tabular-infra-validator inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 comp-automl-tabular-infra-validator-2: executorLabel: exec-automl-tabular-infra-validator-2 inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 comp-automl-tabular-infra-validator-3: executorLabel: exec-automl-tabular-infra-validator-3 inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 comp-automl-tabular-stage-1-tuner: executorLabel: exec-automl-tabular-stage-1-tuner inputDefinitions: artifacts: feature_ranking: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true materialized_eval_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 materialized_train_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: deadline_hours: parameterType: NUMBER_DOUBLE disable_early_stopping: defaultValue: false isOptional: true parameterType: BOOLEAN encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING num_parallel_trials: parameterType: NUMBER_INTEGER num_selected_features: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER num_selected_trials: parameterType: NUMBER_INTEGER project: parameterType: STRING reduce_search_space_mode: defaultValue: regular isOptional: true parameterType: STRING root_dir: parameterType: STRING run_distillation: defaultValue: false isOptional: true parameterType: BOOLEAN single_run_max_secs: parameterType: NUMBER_INTEGER study_spec_parameters_override: defaultValue: [] isOptional: true parameterType: LIST tune_feature_selection_rate: defaultValue: false isOptional: true parameterType: BOOLEAN worker_pool_specs_override_json: defaultValue: [] isOptional: true parameterType: LIST outputDefinitions: artifacts: tuning_result_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: execution_metrics: parameterType: STRUCT gcp_resources: parameterType: STRING comp-automl-tabular-stage-1-tuner-2: executorLabel: exec-automl-tabular-stage-1-tuner-2 inputDefinitions: artifacts: feature_ranking: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true materialized_eval_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 materialized_train_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: deadline_hours: parameterType: NUMBER_DOUBLE disable_early_stopping: defaultValue: false isOptional: true parameterType: BOOLEAN encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING num_parallel_trials: parameterType: NUMBER_INTEGER num_selected_features: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER num_selected_trials: parameterType: NUMBER_INTEGER project: parameterType: STRING reduce_search_space_mode: defaultValue: regular isOptional: true parameterType: STRING root_dir: parameterType: STRING run_distillation: defaultValue: false isOptional: true parameterType: BOOLEAN single_run_max_secs: parameterType: NUMBER_INTEGER study_spec_parameters_override: defaultValue: [] isOptional: true parameterType: LIST tune_feature_selection_rate: defaultValue: false isOptional: true parameterType: BOOLEAN worker_pool_specs_override_json: defaultValue: [] isOptional: true parameterType: LIST outputDefinitions: artifacts: tuning_result_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: execution_metrics: parameterType: STRUCT gcp_resources: parameterType: STRING comp-automl-tabular-transform: executorLabel: exec-automl-tabular-transform inputDefinitions: artifacts: dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 eval_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 test_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 train_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 parameters: dataflow_disk_size_gb: defaultValue: 40.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-16 isOptional: true parameterType: STRING dataflow_max_num_workers: defaultValue: 25.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: materialized_eval_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 materialized_test_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 materialized_train_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 training_schema_uri: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-automl-tabular-transform-2: executorLabel: exec-automl-tabular-transform-2 inputDefinitions: artifacts: dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 eval_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 test_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 train_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 parameters: dataflow_disk_size_gb: defaultValue: 40.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-16 isOptional: true parameterType: STRING dataflow_max_num_workers: defaultValue: 25.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: materialized_eval_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 materialized_test_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 materialized_train_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 training_schema_uri: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-bool-identity: executorLabel: exec-bool-identity inputDefinitions: parameters: value: parameterType: BOOLEAN outputDefinitions: parameters: Output: parameterType: STRING comp-bool-identity-2: executorLabel: exec-bool-identity-2 inputDefinitions: parameters: value: parameterType: BOOLEAN outputDefinitions: parameters: Output: parameterType: STRING comp-bool-identity-3: executorLabel: exec-bool-identity-3 inputDefinitions: parameters: value: parameterType: BOOLEAN outputDefinitions: parameters: Output: parameterType: STRING comp-calculate-training-parameters: executorLabel: exec-calculate-training-parameters inputDefinitions: parameters: fast_testing: defaultValue: false isOptional: true parameterType: BOOLEAN is_skip_architecture_search: defaultValue: false isOptional: true parameterType: BOOLEAN run_distillation: parameterType: BOOLEAN stage_1_num_parallel_trials: parameterType: NUMBER_INTEGER stage_2_num_parallel_trials: parameterType: NUMBER_INTEGER train_budget_milli_node_hours: parameterType: NUMBER_DOUBLE outputDefinitions: parameters: distill_stage_1_deadline_hours: parameterType: NUMBER_DOUBLE reduce_search_space_mode: parameterType: STRING stage_1_deadline_hours: parameterType: NUMBER_DOUBLE stage_1_num_selected_trials: parameterType: NUMBER_INTEGER stage_1_single_run_max_secs: parameterType: NUMBER_INTEGER stage_2_deadline_hours: parameterType: NUMBER_DOUBLE stage_2_single_run_max_secs: parameterType: NUMBER_INTEGER comp-calculate-training-parameters-2: executorLabel: exec-calculate-training-parameters-2 inputDefinitions: parameters: fast_testing: defaultValue: false isOptional: true parameterType: BOOLEAN is_skip_architecture_search: defaultValue: false isOptional: true parameterType: BOOLEAN run_distillation: parameterType: BOOLEAN stage_1_num_parallel_trials: parameterType: NUMBER_INTEGER stage_2_num_parallel_trials: parameterType: NUMBER_INTEGER train_budget_milli_node_hours: parameterType: NUMBER_DOUBLE outputDefinitions: parameters: distill_stage_1_deadline_hours: parameterType: NUMBER_DOUBLE reduce_search_space_mode: parameterType: STRING stage_1_deadline_hours: parameterType: NUMBER_DOUBLE stage_1_num_selected_trials: parameterType: NUMBER_INTEGER stage_1_single_run_max_secs: parameterType: NUMBER_INTEGER stage_2_deadline_hours: parameterType: NUMBER_DOUBLE stage_2_single_run_max_secs: parameterType: NUMBER_INTEGER comp-condition-2: dag: outputs: artifacts: feature-attribution-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-feature_attributions producerSubtask: condition-3 model-evaluation-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-evaluation_metrics producerSubtask: condition-3 tasks: automl-tabular-cv-trainer: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-cv-trainer dependentTasks: - calculate-training-parameters - importer inputs: artifacts: materialized_cv_splits: componentInputArtifact: pipelinechannel--merge-materialized-splits-splits metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata transform_output: componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output tuning_result_input: taskOutputArtifact: outputArtifactKey: artifact producerTask: importer parameters: deadline_hours: taskOutputParameter: outputParameterKey: stage_2_deadline_hours producerTask: calculate-training-parameters encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location num_parallel_trials: componentInputParameter: pipelinechannel--stage_2_num_parallel_trials num_selected_trials: componentInputParameter: pipelinechannel--stage_2_num_selected_trials project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir single_run_max_secs: taskOutputParameter: outputParameterKey: stage_2_single_run_max_secs producerTask: calculate-training-parameters worker_pool_specs_override_json: componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override taskInfo: name: automl-tabular-cv-trainer automl-tabular-ensemble: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-ensemble dependentTasks: - automl-tabular-cv-trainer inputs: artifacts: dataset_schema: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema instance_baseline: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata transform_output: componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output tuning_result_input: taskOutputArtifact: outputArtifactKey: tuning_result_output producerTask: automl-tabular-cv-trainer warmup_data: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name export_additional_model_without_custom_ops: componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: automl-tabular-ensemble automl-tabular-infra-validator: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-infra-validator dependentTasks: - automl-tabular-ensemble inputs: artifacts: unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble taskInfo: name: automl-tabular-infra-validator bool-identity: cachingOptions: enableCache: true componentRef: name: comp-bool-identity inputs: parameters: value: componentInputParameter: pipelinechannel--run_evaluation taskInfo: name: bool-identity calculate-training-parameters: cachingOptions: enableCache: true componentRef: name: comp-calculate-training-parameters inputs: parameters: fast_testing: componentInputParameter: pipelinechannel--fast_testing is_skip_architecture_search: runtimeValue: constant: 1.0 run_distillation: componentInputParameter: pipelinechannel--run_distillation stage_1_num_parallel_trials: componentInputParameter: pipelinechannel--stage_1_num_parallel_trials stage_2_num_parallel_trials: componentInputParameter: pipelinechannel--stage_2_num_parallel_trials train_budget_milli_node_hours: componentInputParameter: pipelinechannel--train_budget_milli_node_hours taskInfo: name: calculate-training-parameters condition-3: componentRef: name: comp-condition-3 dependentTasks: - automl-tabular-ensemble - bool-identity - model-upload inputs: artifacts: pipelinechannel--automl-tabular-ensemble-explanation_metadata_artifact: taskOutputArtifact: outputArtifactKey: explanation_metadata_artifact producerTask: automl-tabular-ensemble pipelinechannel--automl-tabular-ensemble-unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble pipelinechannel--model-upload-model: taskOutputArtifact: outputArtifactKey: model producerTask: model-upload parameters: pipelinechannel--automl-tabular-ensemble-explanation_parameters: taskOutputParameter: outputParameterKey: explanation_parameters producerTask: automl-tabular-ensemble pipelinechannel--bool-identity-Output: taskOutputParameter: outputParameterKey: Output producerTask: bool-identity pipelinechannel--dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips pipelinechannel--encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers pipelinechannel--location: componentInputParameter: pipelinechannel--location pipelinechannel--prediction_type: componentInputParameter: pipelinechannel--prediction_type pipelinechannel--project: componentInputParameter: pipelinechannel--project pipelinechannel--root_dir: componentInputParameter: pipelinechannel--root_dir pipelinechannel--string-not-empty-Output: componentInputParameter: pipelinechannel--string-not-empty-Output pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json pipelinechannel--tabular-stats-and-example-gen-test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json pipelinechannel--target_column: componentInputParameter: pipelinechannel--target_column taskInfo: name: is-evaluation triggerPolicy: condition: inputs.parameter_values['pipelinechannel--bool-identity-Output'] == 'true' importer: cachingOptions: enableCache: true componentRef: name: comp-importer inputs: parameters: uri: componentInputParameter: pipelinechannel--stage_1_tuning_result_artifact_uri taskInfo: name: importer model-upload: cachingOptions: enableCache: true componentRef: name: comp-model-upload dependentTasks: - automl-tabular-ensemble inputs: artifacts: explanation_metadata_artifact: taskOutputArtifact: outputArtifactKey: explanation_metadata_artifact producerTask: automl-tabular-ensemble unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble parameters: description: componentInputParameter: pipelinechannel--model_description display_name: componentInputParameter: pipelinechannel--set-optional-inputs-model_display_name encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name explanation_parameters: taskOutputParameter: outputParameterKey: explanation_parameters producerTask: automl-tabular-ensemble location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project taskInfo: name: model-upload inputDefinitions: artifacts: pipelinechannel--automl-tabular-transform-transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--merge-materialized-splits-splits: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-eval_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-instance_baseline: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: pipelinechannel--cv_trainer_worker_pool_specs_override: parameterType: LIST pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--export_additional_model_without_custom_ops: parameterType: BOOLEAN pipelinechannel--fast_testing: parameterType: BOOLEAN pipelinechannel--location: parameterType: STRING pipelinechannel--model_description: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--root_dir: parameterType: STRING pipelinechannel--run_distillation: parameterType: BOOLEAN pipelinechannel--run_evaluation: parameterType: BOOLEAN pipelinechannel--set-optional-inputs-model_display_name: parameterType: STRING pipelinechannel--stage_1_num_parallel_trials: parameterType: NUMBER_INTEGER pipelinechannel--stage_1_tuning_result_artifact_uri: parameterType: STRING pipelinechannel--stage_2_num_parallel_trials: parameterType: NUMBER_INTEGER pipelinechannel--stage_2_num_selected_trials: parameterType: NUMBER_INTEGER pipelinechannel--string-not-empty-Output: parameterType: STRING pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-test_split_json: parameterType: LIST pipelinechannel--target_column: parameterType: STRING pipelinechannel--train_budget_milli_node_hours: parameterType: NUMBER_DOUBLE outputDefinitions: artifacts: feature-attribution-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-condition-3: dag: outputs: artifacts: feature-attribution-feature_attributions: artifactSelectors: - outputArtifactKey: feature_attributions producerSubtask: feature-attribution model-evaluation-evaluation_metrics: artifactSelectors: - outputArtifactKey: evaluation_metrics producerSubtask: model-evaluation tasks: feature-attribution: cachingOptions: enableCache: true componentRef: name: comp-feature-attribution dependentTasks: - model-batch-explanation inputs: artifacts: predictions_gcs_source: taskOutputArtifact: outputArtifactKey: gcs_output_directory producerTask: model-batch-explanation parameters: dataflow_disk_size: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type dataflow_max_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips dataflow_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: feature-attribution model-batch-explanation: cachingOptions: enableCache: true componentRef: name: comp-model-batch-explanation inputs: artifacts: explanation_metadata_artifact: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-explanation_metadata_artifact unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name explanation_parameters: componentInputParameter: pipelinechannel--automl-tabular-ensemble-explanation_parameters gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json generate_explanation: runtimeValue: constant: 1.0 instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count taskInfo: name: model-batch-explanation model-batch-predict: cachingOptions: enableCache: true componentRef: name: comp-model-batch-predict inputs: artifacts: unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-predict-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count taskInfo: name: model-batch-predict model-evaluation: cachingOptions: enableCache: true componentRef: name: comp-model-evaluation dependentTasks: - model-batch-predict inputs: artifacts: batch_prediction_job: taskOutputArtifact: outputArtifactKey: batchpredictionjob producerTask: model-batch-predict parameters: dataflow_disk_size: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type dataflow_max_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips dataflow_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name ground_truth_column: componentInputParameter: pipelinechannel--target_column ground_truth_format: runtimeValue: constant: jsonl location: componentInputParameter: pipelinechannel--location prediction_label_column: runtimeValue: constant: '' prediction_score_column: runtimeValue: constant: '' predictions_format: runtimeValue: constant: jsonl problem_type: componentInputParameter: pipelinechannel--prediction_type project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: model-evaluation model-evaluation-import: cachingOptions: enableCache: true componentRef: name: comp-model-evaluation-import dependentTasks: - feature-attribution - model-evaluation inputs: artifacts: feature_attributions: taskOutputArtifact: outputArtifactKey: feature_attributions producerTask: feature-attribution metrics: taskOutputArtifact: outputArtifactKey: evaluation_metrics producerTask: model-evaluation model: componentInputArtifact: pipelinechannel--model-upload-model parameters: dataset_paths: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json dataset_type: runtimeValue: constant: tf-record display_name: runtimeValue: constant: AutoML Tabular problem_type: componentInputParameter: pipelinechannel--prediction_type taskInfo: name: model-evaluation-import inputDefinitions: artifacts: pipelinechannel--automl-tabular-ensemble-explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--automl-tabular-ensemble-unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 pipelinechannel--model-upload-model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 parameters: pipelinechannel--automl-tabular-ensemble-explanation_parameters: parameterType: STRUCT pipelinechannel--bool-identity-Output: parameterType: STRING pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--location: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--root_dir: parameterType: STRING pipelinechannel--string-not-empty-Output: parameterType: STRING pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-test_split_json: parameterType: LIST pipelinechannel--target_column: parameterType: STRING outputDefinitions: artifacts: feature-attribution-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-condition-4: dag: outputs: artifacts: feature-attribution-2-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-2-feature_attributions producerSubtask: condition-5 feature-attribution-3-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-3-feature_attributions producerSubtask: condition-7 model-evaluation-2-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-2-evaluation_metrics producerSubtask: condition-5 model-evaluation-3-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-3-evaluation_metrics producerSubtask: condition-7 tasks: automl-tabular-cv-trainer-2: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-cv-trainer-2 dependentTasks: - automl-tabular-stage-1-tuner - calculate-training-parameters-2 inputs: artifacts: materialized_cv_splits: componentInputArtifact: pipelinechannel--merge-materialized-splits-splits metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata transform_output: componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output tuning_result_input: taskOutputArtifact: outputArtifactKey: tuning_result_output producerTask: automl-tabular-stage-1-tuner parameters: deadline_hours: taskOutputParameter: outputParameterKey: stage_2_deadline_hours producerTask: calculate-training-parameters-2 encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location num_parallel_trials: componentInputParameter: pipelinechannel--stage_2_num_parallel_trials num_selected_trials: componentInputParameter: pipelinechannel--stage_2_num_selected_trials project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir single_run_max_secs: taskOutputParameter: outputParameterKey: stage_2_single_run_max_secs producerTask: calculate-training-parameters-2 worker_pool_specs_override_json: componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override taskInfo: name: automl-tabular-cv-trainer-2 automl-tabular-ensemble-2: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-ensemble-2 dependentTasks: - automl-tabular-cv-trainer-2 inputs: artifacts: dataset_schema: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema instance_baseline: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata transform_output: componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output tuning_result_input: taskOutputArtifact: outputArtifactKey: tuning_result_output producerTask: automl-tabular-cv-trainer-2 warmup_data: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name export_additional_model_without_custom_ops: componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: automl-tabular-ensemble-2 automl-tabular-infra-validator-2: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-infra-validator-2 dependentTasks: - automl-tabular-ensemble-2 inputs: artifacts: unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble-2 taskInfo: name: automl-tabular-infra-validator-2 automl-tabular-stage-1-tuner: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-stage-1-tuner dependentTasks: - calculate-training-parameters-2 inputs: artifacts: materialized_eval_split: componentInputArtifact: pipelinechannel--automl-tabular-transform-materialized_eval_split materialized_train_split: componentInputArtifact: pipelinechannel--automl-tabular-transform-materialized_train_split metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata transform_output: componentInputArtifact: pipelinechannel--automl-tabular-transform-transform_output parameters: deadline_hours: taskOutputParameter: outputParameterKey: stage_1_deadline_hours producerTask: calculate-training-parameters-2 disable_early_stopping: componentInputParameter: pipelinechannel--disable_early_stopping encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location num_parallel_trials: componentInputParameter: pipelinechannel--stage_1_num_parallel_trials num_selected_trials: taskOutputParameter: outputParameterKey: stage_1_num_selected_trials producerTask: calculate-training-parameters-2 project: componentInputParameter: pipelinechannel--project reduce_search_space_mode: taskOutputParameter: outputParameterKey: reduce_search_space_mode producerTask: calculate-training-parameters-2 root_dir: componentInputParameter: pipelinechannel--root_dir single_run_max_secs: taskOutputParameter: outputParameterKey: stage_1_single_run_max_secs producerTask: calculate-training-parameters-2 study_spec_parameters_override: componentInputParameter: pipelinechannel--study_spec_parameters_override worker_pool_specs_override_json: componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override taskInfo: name: automl-tabular-stage-1-tuner bool-identity-2: cachingOptions: enableCache: true componentRef: name: comp-bool-identity-2 inputs: parameters: value: componentInputParameter: pipelinechannel--run_evaluation taskInfo: name: bool-identity-2 bool-identity-3: cachingOptions: enableCache: true componentRef: name: comp-bool-identity-3 inputs: parameters: value: componentInputParameter: pipelinechannel--run_distillation taskInfo: name: bool-identity-3 calculate-training-parameters-2: cachingOptions: enableCache: true componentRef: name: comp-calculate-training-parameters-2 inputs: parameters: fast_testing: componentInputParameter: pipelinechannel--fast_testing is_skip_architecture_search: runtimeValue: constant: 0.0 run_distillation: componentInputParameter: pipelinechannel--run_distillation stage_1_num_parallel_trials: componentInputParameter: pipelinechannel--stage_1_num_parallel_trials stage_2_num_parallel_trials: componentInputParameter: pipelinechannel--stage_2_num_parallel_trials train_budget_milli_node_hours: componentInputParameter: pipelinechannel--train_budget_milli_node_hours taskInfo: name: calculate-training-parameters-2 condition-5: componentRef: name: comp-condition-5 dependentTasks: - automl-tabular-ensemble-2 - bool-identity-2 - bool-identity-3 inputs: artifacts: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact: taskOutputArtifact: outputArtifactKey: explanation_metadata_artifact producerTask: automl-tabular-ensemble-2 pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble-2 parameters: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters: taskOutputParameter: outputParameterKey: explanation_parameters producerTask: automl-tabular-ensemble-2 pipelinechannel--bool-identity-2-Output: taskOutputParameter: outputParameterKey: Output producerTask: bool-identity-2 pipelinechannel--bool-identity-3-Output: taskOutputParameter: outputParameterKey: Output producerTask: bool-identity-3 pipelinechannel--dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips pipelinechannel--encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers pipelinechannel--location: componentInputParameter: pipelinechannel--location pipelinechannel--model_description: componentInputParameter: pipelinechannel--model_description pipelinechannel--prediction_type: componentInputParameter: pipelinechannel--prediction_type pipelinechannel--project: componentInputParameter: pipelinechannel--project pipelinechannel--root_dir: componentInputParameter: pipelinechannel--root_dir pipelinechannel--set-optional-inputs-model_display_name: componentInputParameter: pipelinechannel--set-optional-inputs-model_display_name pipelinechannel--string-not-empty-Output: componentInputParameter: pipelinechannel--string-not-empty-Output pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json pipelinechannel--tabular-stats-and-example-gen-test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json pipelinechannel--target_column: componentInputParameter: pipelinechannel--target_column taskInfo: name: no-distill triggerPolicy: condition: inputs.parameter_values['pipelinechannel--bool-identity-3-Output'] == 'false' condition-7: componentRef: name: comp-condition-7 dependentTasks: - automl-tabular-ensemble-2 - bool-identity-2 - bool-identity-3 - calculate-training-parameters-2 inputs: artifacts: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble-2 pipelinechannel--tabular-stats-and-example-gen-dataset_schema: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema pipelinechannel--tabular-stats-and-example-gen-eval_split: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split pipelinechannel--tabular-stats-and-example-gen-instance_baseline: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline pipelinechannel--tabular-stats-and-example-gen-metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata pipelinechannel--tabular-stats-and-example-gen-test_split: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-test_split pipelinechannel--tabular-stats-and-example-gen-train_split: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-train_split parameters: pipelinechannel--bool-identity-2-Output: taskOutputParameter: outputParameterKey: Output producerTask: bool-identity-2 pipelinechannel--bool-identity-3-Output: taskOutputParameter: outputParameterKey: Output producerTask: bool-identity-3 pipelinechannel--calculate-training-parameters-2-distill_stage_1_deadline_hours: taskOutputParameter: outputParameterKey: distill_stage_1_deadline_hours producerTask: calculate-training-parameters-2 pipelinechannel--calculate-training-parameters-2-reduce_search_space_mode: taskOutputParameter: outputParameterKey: reduce_search_space_mode producerTask: calculate-training-parameters-2 pipelinechannel--calculate-training-parameters-2-stage_1_single_run_max_secs: taskOutputParameter: outputParameterKey: stage_1_single_run_max_secs producerTask: calculate-training-parameters-2 pipelinechannel--dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips pipelinechannel--disable_early_stopping: componentInputParameter: pipelinechannel--disable_early_stopping pipelinechannel--distill_batch_predict_machine_type: componentInputParameter: pipelinechannel--distill_batch_predict_machine_type pipelinechannel--distill_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count pipelinechannel--distill_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count pipelinechannel--encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers pipelinechannel--export_additional_model_without_custom_ops: componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops pipelinechannel--location: componentInputParameter: pipelinechannel--location pipelinechannel--prediction_type: componentInputParameter: pipelinechannel--prediction_type pipelinechannel--project: componentInputParameter: pipelinechannel--project pipelinechannel--root_dir: componentInputParameter: pipelinechannel--root_dir pipelinechannel--stage_1_num_parallel_trials: componentInputParameter: pipelinechannel--stage_1_num_parallel_trials pipelinechannel--stage_1_tuner_worker_pool_specs_override: componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override pipelinechannel--string-not-empty-Output: componentInputParameter: pipelinechannel--string-not-empty-Output pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json pipelinechannel--tabular-stats-and-example-gen-test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json pipelinechannel--target_column: componentInputParameter: pipelinechannel--target_column pipelinechannel--transform_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb pipelinechannel--transform_dataflow_machine_type: componentInputParameter: pipelinechannel--transform_dataflow_machine_type pipelinechannel--transform_dataflow_max_num_workers: componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers taskInfo: name: is-distill triggerPolicy: condition: inputs.parameter_values['pipelinechannel--bool-identity-3-Output'] == 'true' inputDefinitions: artifacts: pipelinechannel--automl-tabular-transform-materialized_eval_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--automl-tabular-transform-materialized_train_split: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--automl-tabular-transform-transform_output: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--merge-materialized-splits-splits: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-eval_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-instance_baseline: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-test_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-train_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 parameters: pipelinechannel--cv_trainer_worker_pool_specs_override: parameterType: LIST pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--disable_early_stopping: parameterType: BOOLEAN pipelinechannel--distill_batch_predict_machine_type: parameterType: STRING pipelinechannel--distill_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--distill_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--export_additional_model_without_custom_ops: parameterType: BOOLEAN pipelinechannel--fast_testing: parameterType: BOOLEAN pipelinechannel--location: parameterType: STRING pipelinechannel--model_description: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--root_dir: parameterType: STRING pipelinechannel--run_distillation: parameterType: BOOLEAN pipelinechannel--run_evaluation: parameterType: BOOLEAN pipelinechannel--set-optional-inputs-model_display_name: parameterType: STRING pipelinechannel--stage_1_num_parallel_trials: parameterType: NUMBER_INTEGER pipelinechannel--stage_1_tuner_worker_pool_specs_override: parameterType: LIST pipelinechannel--stage_2_num_parallel_trials: parameterType: NUMBER_INTEGER pipelinechannel--stage_2_num_selected_trials: parameterType: NUMBER_INTEGER pipelinechannel--string-not-empty-Output: parameterType: STRING pipelinechannel--study_spec_parameters_override: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-test_split_json: parameterType: LIST pipelinechannel--target_column: parameterType: STRING pipelinechannel--train_budget_milli_node_hours: parameterType: NUMBER_DOUBLE pipelinechannel--transform_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--transform_dataflow_machine_type: parameterType: STRING pipelinechannel--transform_dataflow_max_num_workers: parameterType: NUMBER_INTEGER outputDefinitions: artifacts: feature-attribution-2-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 feature-attribution-3-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-2-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-3-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-condition-5: dag: outputs: artifacts: feature-attribution-2-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-2-feature_attributions producerSubtask: condition-6 model-evaluation-2-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-2-evaluation_metrics producerSubtask: condition-6 tasks: condition-6: componentRef: name: comp-condition-6 dependentTasks: - model-upload-2 inputs: artifacts: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model pipelinechannel--model-upload-2-model: taskOutputArtifact: outputArtifactKey: model producerTask: model-upload-2 parameters: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters: componentInputParameter: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters pipelinechannel--bool-identity-2-Output: componentInputParameter: pipelinechannel--bool-identity-2-Output pipelinechannel--bool-identity-3-Output: componentInputParameter: pipelinechannel--bool-identity-3-Output pipelinechannel--dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips pipelinechannel--encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers pipelinechannel--location: componentInputParameter: pipelinechannel--location pipelinechannel--prediction_type: componentInputParameter: pipelinechannel--prediction_type pipelinechannel--project: componentInputParameter: pipelinechannel--project pipelinechannel--root_dir: componentInputParameter: pipelinechannel--root_dir pipelinechannel--string-not-empty-Output: componentInputParameter: pipelinechannel--string-not-empty-Output pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json pipelinechannel--tabular-stats-and-example-gen-test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json pipelinechannel--target_column: componentInputParameter: pipelinechannel--target_column taskInfo: name: is-evaluation triggerPolicy: condition: inputs.parameter_values['pipelinechannel--bool-identity-2-Output'] == 'true' model-upload-2: cachingOptions: enableCache: true componentRef: name: comp-model-upload-2 inputs: artifacts: explanation_metadata_artifact: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model parameters: description: componentInputParameter: pipelinechannel--model_description display_name: componentInputParameter: pipelinechannel--set-optional-inputs-model_display_name encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name explanation_parameters: componentInputParameter: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project taskInfo: name: model-upload-2 inputDefinitions: artifacts: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 parameters: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters: parameterType: STRUCT pipelinechannel--bool-identity-2-Output: parameterType: STRING pipelinechannel--bool-identity-3-Output: parameterType: STRING pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--location: parameterType: STRING pipelinechannel--model_description: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--root_dir: parameterType: STRING pipelinechannel--set-optional-inputs-model_display_name: parameterType: STRING pipelinechannel--string-not-empty-Output: parameterType: STRING pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-test_split_json: parameterType: LIST pipelinechannel--target_column: parameterType: STRING outputDefinitions: artifacts: feature-attribution-2-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-2-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-condition-6: dag: outputs: artifacts: feature-attribution-2-feature_attributions: artifactSelectors: - outputArtifactKey: feature_attributions producerSubtask: feature-attribution-2 model-evaluation-2-evaluation_metrics: artifactSelectors: - outputArtifactKey: evaluation_metrics producerSubtask: model-evaluation-2 tasks: feature-attribution-2: cachingOptions: enableCache: true componentRef: name: comp-feature-attribution-2 dependentTasks: - model-batch-explanation-2 inputs: artifacts: predictions_gcs_source: taskOutputArtifact: outputArtifactKey: gcs_output_directory producerTask: model-batch-explanation-2 parameters: dataflow_disk_size: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type dataflow_max_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips dataflow_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: feature-attribution-2 model-batch-explanation-2: cachingOptions: enableCache: true componentRef: name: comp-model-batch-explanation-2 inputs: artifacts: explanation_metadata_artifact: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name explanation_parameters: componentInputParameter: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json generate_explanation: runtimeValue: constant: 1.0 instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count taskInfo: name: model-batch-explanation-2 model-batch-predict-2: cachingOptions: enableCache: true componentRef: name: comp-model-batch-predict-2 inputs: artifacts: unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-predict-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count taskInfo: name: model-batch-predict-2 model-evaluation-2: cachingOptions: enableCache: true componentRef: name: comp-model-evaluation-2 dependentTasks: - model-batch-predict-2 inputs: artifacts: batch_prediction_job: taskOutputArtifact: outputArtifactKey: batchpredictionjob producerTask: model-batch-predict-2 parameters: dataflow_disk_size: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type dataflow_max_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips dataflow_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name ground_truth_column: componentInputParameter: pipelinechannel--target_column ground_truth_format: runtimeValue: constant: jsonl location: componentInputParameter: pipelinechannel--location prediction_label_column: runtimeValue: constant: '' prediction_score_column: runtimeValue: constant: '' predictions_format: runtimeValue: constant: jsonl problem_type: componentInputParameter: pipelinechannel--prediction_type project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: model-evaluation-2 model-evaluation-import-2: cachingOptions: enableCache: true componentRef: name: comp-model-evaluation-import-2 dependentTasks: - feature-attribution-2 - model-evaluation-2 inputs: artifacts: feature_attributions: taskOutputArtifact: outputArtifactKey: feature_attributions producerTask: feature-attribution-2 metrics: taskOutputArtifact: outputArtifactKey: evaluation_metrics producerTask: model-evaluation-2 model: componentInputArtifact: pipelinechannel--model-upload-2-model parameters: dataset_paths: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json dataset_type: runtimeValue: constant: tf-record display_name: runtimeValue: constant: AutoML Tabular problem_type: componentInputParameter: pipelinechannel--prediction_type taskInfo: name: model-evaluation-import-2 inputDefinitions: artifacts: pipelinechannel--automl-tabular-ensemble-2-explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 pipelinechannel--model-upload-2-model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 parameters: pipelinechannel--automl-tabular-ensemble-2-explanation_parameters: parameterType: STRUCT pipelinechannel--bool-identity-2-Output: parameterType: STRING pipelinechannel--bool-identity-3-Output: parameterType: STRING pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--location: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--root_dir: parameterType: STRING pipelinechannel--string-not-empty-Output: parameterType: STRING pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-test_split_json: parameterType: LIST pipelinechannel--target_column: parameterType: STRING outputDefinitions: artifacts: feature-attribution-2-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-2-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-condition-7: dag: outputs: artifacts: feature-attribution-3-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-3-feature_attributions producerSubtask: condition-8 model-evaluation-3-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-3-evaluation_metrics producerSubtask: condition-8 tasks: automl-tabular-ensemble-3: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-ensemble-3 dependentTasks: - automl-tabular-stage-1-tuner-2 - automl-tabular-transform-2 inputs: artifacts: dataset_schema: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema instance_baseline: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-instance_baseline metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata transform_output: taskOutputArtifact: outputArtifactKey: transform_output producerTask: automl-tabular-transform-2 tuning_result_input: taskOutputArtifact: outputArtifactKey: tuning_result_output producerTask: automl-tabular-stage-1-tuner-2 warmup_data: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name export_additional_model_without_custom_ops: componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: automl-tabular-ensemble-3 automl-tabular-infra-validator-3: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-infra-validator-3 dependentTasks: - automl-tabular-ensemble-3 inputs: artifacts: unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble-3 taskInfo: name: automl-tabular-infra-validator-3 automl-tabular-stage-1-tuner-2: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-stage-1-tuner-2 dependentTasks: - automl-tabular-transform-2 inputs: artifacts: materialized_eval_split: taskOutputArtifact: outputArtifactKey: materialized_eval_split producerTask: automl-tabular-transform-2 materialized_train_split: taskOutputArtifact: outputArtifactKey: materialized_train_split producerTask: automl-tabular-transform-2 metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata transform_output: taskOutputArtifact: outputArtifactKey: transform_output producerTask: automl-tabular-transform-2 parameters: deadline_hours: componentInputParameter: pipelinechannel--calculate-training-parameters-2-distill_stage_1_deadline_hours disable_early_stopping: componentInputParameter: pipelinechannel--disable_early_stopping encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location num_parallel_trials: componentInputParameter: pipelinechannel--stage_1_num_parallel_trials num_selected_trials: runtimeValue: constant: 1.0 project: componentInputParameter: pipelinechannel--project reduce_search_space_mode: componentInputParameter: pipelinechannel--calculate-training-parameters-2-reduce_search_space_mode root_dir: componentInputParameter: pipelinechannel--root_dir run_distillation: runtimeValue: constant: 1.0 single_run_max_secs: componentInputParameter: pipelinechannel--calculate-training-parameters-2-stage_1_single_run_max_secs worker_pool_specs_override_json: componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override taskInfo: name: automl-tabular-stage-1-tuner-2 automl-tabular-transform-2: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-transform-2 dependentTasks: - write-bp-result-path - write-bp-result-path-2 inputs: artifacts: dataset_schema: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-dataset_schema eval_split: taskOutputArtifact: outputArtifactKey: result producerTask: write-bp-result-path-2 metadata: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-metadata test_split: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-test_split train_split: taskOutputArtifact: outputArtifactKey: result producerTask: write-bp-result-path parameters: dataflow_disk_size_gb: componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--transform_dataflow_machine_type dataflow_max_num_workers: componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: automl-tabular-transform-2 condition-8: componentRef: name: comp-condition-8 dependentTasks: - automl-tabular-ensemble-3 - model-upload-3 inputs: artifacts: pipelinechannel--automl-tabular-ensemble-3-explanation_metadata_artifact: taskOutputArtifact: outputArtifactKey: explanation_metadata_artifact producerTask: automl-tabular-ensemble-3 pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble-3 pipelinechannel--model-upload-3-model: taskOutputArtifact: outputArtifactKey: model producerTask: model-upload-3 parameters: pipelinechannel--automl-tabular-ensemble-3-explanation_parameters: taskOutputParameter: outputParameterKey: explanation_parameters producerTask: automl-tabular-ensemble-3 pipelinechannel--bool-identity-2-Output: componentInputParameter: pipelinechannel--bool-identity-2-Output pipelinechannel--bool-identity-3-Output: componentInputParameter: pipelinechannel--bool-identity-3-Output pipelinechannel--dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips pipelinechannel--encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers pipelinechannel--location: componentInputParameter: pipelinechannel--location pipelinechannel--prediction_type: componentInputParameter: pipelinechannel--prediction_type pipelinechannel--project: componentInputParameter: pipelinechannel--project pipelinechannel--root_dir: componentInputParameter: pipelinechannel--root_dir pipelinechannel--string-not-empty-Output: componentInputParameter: pipelinechannel--string-not-empty-Output pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json pipelinechannel--tabular-stats-and-example-gen-test_split_json: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json pipelinechannel--target_column: componentInputParameter: pipelinechannel--target_column taskInfo: name: is-evaluation triggerPolicy: condition: inputs.parameter_values['pipelinechannel--bool-identity-2-Output'] == 'true' model-batch-predict-3: cachingOptions: enableCache: true componentRef: name: comp-model-batch-predict-3 dependentTasks: - read-input-uri inputs: artifacts: unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: taskOutputParameter: outputParameterKey: Output producerTask: read-input-uri instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-predict-train-split location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--distill_batch_predict_machine_type max_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count predictions_format: runtimeValue: constant: tf-record project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count taskInfo: name: model-batch-predict-3 model-batch-predict-4: cachingOptions: enableCache: true componentRef: name: comp-model-batch-predict-4 dependentTasks: - read-input-uri-2 inputs: artifacts: unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: taskOutputParameter: outputParameterKey: Output producerTask: read-input-uri-2 instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-predict-eval-split location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--distill_batch_predict_machine_type max_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count predictions_format: runtimeValue: constant: tf-record project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count taskInfo: name: model-batch-predict-4 model-upload-3: cachingOptions: enableCache: true componentRef: name: comp-model-upload-3 dependentTasks: - automl-tabular-ensemble-3 - automl-tabular-infra-validator-3 inputs: artifacts: explanation_metadata_artifact: taskOutputArtifact: outputArtifactKey: explanation_metadata_artifact producerTask: automl-tabular-ensemble-3 unmanaged_container_model: taskOutputArtifact: outputArtifactKey: unmanaged_container_model producerTask: automl-tabular-ensemble-3 parameters: display_name: runtimeValue: constant: automl-tabular-distill-model-upload-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name explanation_parameters: taskOutputParameter: outputParameterKey: explanation_parameters producerTask: automl-tabular-ensemble-3 location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project taskInfo: name: model-upload-3 read-input-uri: cachingOptions: enableCache: true componentRef: name: comp-read-input-uri inputs: artifacts: split_uri: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-train_split taskInfo: name: read-input-uri read-input-uri-2: cachingOptions: enableCache: true componentRef: name: comp-read-input-uri-2 inputs: artifacts: split_uri: componentInputArtifact: pipelinechannel--tabular-stats-and-example-gen-eval_split taskInfo: name: read-input-uri-2 write-bp-result-path: cachingOptions: enableCache: true componentRef: name: comp-write-bp-result-path dependentTasks: - model-batch-predict-3 inputs: artifacts: bp_job: taskOutputArtifact: outputArtifactKey: batchpredictionjob producerTask: model-batch-predict-3 taskInfo: name: write-bp-result-path write-bp-result-path-2: cachingOptions: enableCache: true componentRef: name: comp-write-bp-result-path-2 dependentTasks: - model-batch-predict-4 inputs: artifacts: bp_job: taskOutputArtifact: outputArtifactKey: batchpredictionjob producerTask: model-batch-predict-4 taskInfo: name: write-bp-result-path-2 inputDefinitions: artifacts: pipelinechannel--automl-tabular-ensemble-2-unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-eval_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-instance_baseline: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-test_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 pipelinechannel--tabular-stats-and-example-gen-train_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 parameters: pipelinechannel--bool-identity-2-Output: parameterType: STRING pipelinechannel--bool-identity-3-Output: parameterType: STRING pipelinechannel--calculate-training-parameters-2-distill_stage_1_deadline_hours: parameterType: NUMBER_DOUBLE pipelinechannel--calculate-training-parameters-2-reduce_search_space_mode: parameterType: STRING pipelinechannel--calculate-training-parameters-2-stage_1_single_run_max_secs: parameterType: NUMBER_INTEGER pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--disable_early_stopping: parameterType: BOOLEAN pipelinechannel--distill_batch_predict_machine_type: parameterType: STRING pipelinechannel--distill_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--distill_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--export_additional_model_without_custom_ops: parameterType: BOOLEAN pipelinechannel--location: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--root_dir: parameterType: STRING pipelinechannel--stage_1_num_parallel_trials: parameterType: NUMBER_INTEGER pipelinechannel--stage_1_tuner_worker_pool_specs_override: parameterType: LIST pipelinechannel--string-not-empty-Output: parameterType: STRING pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-test_split_json: parameterType: LIST pipelinechannel--target_column: parameterType: STRING pipelinechannel--transform_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--transform_dataflow_machine_type: parameterType: STRING pipelinechannel--transform_dataflow_max_num_workers: parameterType: NUMBER_INTEGER outputDefinitions: artifacts: feature-attribution-3-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-3-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-condition-8: dag: outputs: artifacts: feature-attribution-3-feature_attributions: artifactSelectors: - outputArtifactKey: feature_attributions producerSubtask: feature-attribution-3 model-evaluation-3-evaluation_metrics: artifactSelectors: - outputArtifactKey: evaluation_metrics producerSubtask: model-evaluation-3 tasks: feature-attribution-3: cachingOptions: enableCache: true componentRef: name: comp-feature-attribution-3 dependentTasks: - model-batch-explanation-3 inputs: artifacts: predictions_gcs_source: taskOutputArtifact: outputArtifactKey: gcs_output_directory producerTask: model-batch-explanation-3 parameters: dataflow_disk_size: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type dataflow_max_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips dataflow_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: feature-attribution-3 model-batch-explanation-3: cachingOptions: enableCache: true componentRef: name: comp-model-batch-explanation-3 inputs: artifacts: explanation_metadata_artifact: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-3-explanation_metadata_artifact unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name explanation_parameters: componentInputParameter: pipelinechannel--automl-tabular-ensemble-3-explanation_parameters gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json generate_explanation: runtimeValue: constant: 1.0 instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-explain-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count taskInfo: name: model-batch-explanation-3 model-batch-predict-5: cachingOptions: enableCache: true componentRef: name: comp-model-batch-predict-5 inputs: artifacts: unmanaged_container_model: componentInputArtifact: pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model parameters: encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name gcs_destination_output_uri_prefix: componentInputParameter: pipelinechannel--root_dir gcs_source_uris: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json instances_format: runtimeValue: constant: tf-record job_display_name: runtimeValue: constant: batch-predict-evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} location: componentInputParameter: pipelinechannel--location machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count predictions_format: runtimeValue: constant: jsonl project: componentInputParameter: pipelinechannel--project starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count taskInfo: name: model-batch-predict-5 model-evaluation-3: cachingOptions: enableCache: true componentRef: name: comp-model-evaluation-3 dependentTasks: - model-batch-predict-5 inputs: artifacts: batch_prediction_job: taskOutputArtifact: outputArtifactKey: batchpredictionjob producerTask: model-batch-predict-5 parameters: dataflow_disk_size: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type dataflow_max_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips dataflow_workers_num: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name ground_truth_column: componentInputParameter: pipelinechannel--target_column ground_truth_format: runtimeValue: constant: jsonl location: componentInputParameter: pipelinechannel--location prediction_label_column: runtimeValue: constant: '' prediction_score_column: runtimeValue: constant: '' predictions_format: runtimeValue: constant: jsonl problem_type: componentInputParameter: pipelinechannel--prediction_type project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: model-evaluation-3 model-evaluation-import-3: cachingOptions: enableCache: true componentRef: name: comp-model-evaluation-import-3 dependentTasks: - feature-attribution-3 - model-evaluation-3 inputs: artifacts: feature_attributions: taskOutputArtifact: outputArtifactKey: feature_attributions producerTask: feature-attribution-3 metrics: taskOutputArtifact: outputArtifactKey: evaluation_metrics producerTask: model-evaluation-3 model: componentInputArtifact: pipelinechannel--model-upload-3-model parameters: dataset_paths: componentInputParameter: pipelinechannel--tabular-stats-and-example-gen-test_split_json dataset_type: runtimeValue: constant: tf-record display_name: runtimeValue: constant: AutoML Tabular problem_type: componentInputParameter: pipelinechannel--prediction_type taskInfo: name: model-evaluation-import-3 inputDefinitions: artifacts: pipelinechannel--automl-tabular-ensemble-3-explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 pipelinechannel--automl-tabular-ensemble-3-unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 pipelinechannel--model-upload-3-model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 parameters: pipelinechannel--automl-tabular-ensemble-3-explanation_parameters: parameterType: STRUCT pipelinechannel--bool-identity-2-Output: parameterType: STRING pipelinechannel--bool-identity-3-Output: parameterType: STRING pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--location: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--root_dir: parameterType: STRING pipelinechannel--string-not-empty-Output: parameterType: STRING pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: parameterType: LIST pipelinechannel--tabular-stats-and-example-gen-test_split_json: parameterType: LIST pipelinechannel--target_column: parameterType: STRING outputDefinitions: artifacts: feature-attribution-3-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-3-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-exit-handler-1: dag: outputs: artifacts: feature-attribution-2-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-2-feature_attributions producerSubtask: condition-4 feature-attribution-3-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-3-feature_attributions producerSubtask: condition-4 feature-attribution-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-feature_attributions producerSubtask: condition-2 model-evaluation-2-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-2-evaluation_metrics producerSubtask: condition-4 model-evaluation-3-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-3-evaluation_metrics producerSubtask: condition-4 model-evaluation-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-evaluation_metrics producerSubtask: condition-2 tasks: automl-tabular-transform: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-transform dependentTasks: - tabular-stats-and-example-gen inputs: artifacts: dataset_schema: taskOutputArtifact: outputArtifactKey: dataset_schema producerTask: tabular-stats-and-example-gen eval_split: taskOutputArtifact: outputArtifactKey: eval_split producerTask: tabular-stats-and-example-gen metadata: taskOutputArtifact: outputArtifactKey: metadata producerTask: tabular-stats-and-example-gen test_split: taskOutputArtifact: outputArtifactKey: test_split producerTask: tabular-stats-and-example-gen train_split: taskOutputArtifact: outputArtifactKey: train_split producerTask: tabular-stats-and-example-gen parameters: dataflow_disk_size_gb: componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--transform_dataflow_machine_type dataflow_max_num_workers: componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location project: componentInputParameter: pipelinechannel--project root_dir: componentInputParameter: pipelinechannel--root_dir taskInfo: name: automl-tabular-transform condition-2: componentRef: name: comp-condition-2 dependentTasks: - automl-tabular-transform - merge-materialized-splits - string-not-empty - tabular-stats-and-example-gen inputs: artifacts: pipelinechannel--automl-tabular-transform-transform_output: taskOutputArtifact: outputArtifactKey: transform_output producerTask: automl-tabular-transform pipelinechannel--merge-materialized-splits-splits: taskOutputArtifact: outputArtifactKey: splits producerTask: merge-materialized-splits pipelinechannel--tabular-stats-and-example-gen-dataset_schema: taskOutputArtifact: outputArtifactKey: dataset_schema producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-eval_split: taskOutputArtifact: outputArtifactKey: eval_split producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-instance_baseline: taskOutputArtifact: outputArtifactKey: instance_baseline producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-metadata: taskOutputArtifact: outputArtifactKey: metadata producerTask: tabular-stats-and-example-gen parameters: pipelinechannel--cv_trainer_worker_pool_specs_override: componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override pipelinechannel--dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips pipelinechannel--encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers pipelinechannel--export_additional_model_without_custom_ops: componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops pipelinechannel--fast_testing: componentInputParameter: pipelinechannel--fast_testing pipelinechannel--location: componentInputParameter: pipelinechannel--location pipelinechannel--model_description: componentInputParameter: pipelinechannel--model_description pipelinechannel--prediction_type: componentInputParameter: pipelinechannel--prediction_type pipelinechannel--project: componentInputParameter: pipelinechannel--project pipelinechannel--root_dir: componentInputParameter: pipelinechannel--root_dir pipelinechannel--run_distillation: componentInputParameter: pipelinechannel--run_distillation pipelinechannel--run_evaluation: componentInputParameter: pipelinechannel--run_evaluation pipelinechannel--set-optional-inputs-model_display_name: componentInputParameter: pipelinechannel--set-optional-inputs-model_display_name pipelinechannel--stage_1_num_parallel_trials: componentInputParameter: pipelinechannel--stage_1_num_parallel_trials pipelinechannel--stage_1_tuning_result_artifact_uri: componentInputParameter: pipelinechannel--stage_1_tuning_result_artifact_uri pipelinechannel--stage_2_num_parallel_trials: componentInputParameter: pipelinechannel--stage_2_num_parallel_trials pipelinechannel--stage_2_num_selected_trials: componentInputParameter: pipelinechannel--stage_2_num_selected_trials pipelinechannel--string-not-empty-Output: taskOutputParameter: outputParameterKey: Output producerTask: string-not-empty pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: taskOutputParameter: outputParameterKey: downsampled_test_split_json producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-test_split_json: taskOutputParameter: outputParameterKey: test_split_json producerTask: tabular-stats-and-example-gen pipelinechannel--target_column: componentInputParameter: pipelinechannel--target_column pipelinechannel--train_budget_milli_node_hours: componentInputParameter: pipelinechannel--train_budget_milli_node_hours taskInfo: name: stage_1_tuning_result_artifact_uri_not_empty triggerPolicy: condition: inputs.parameter_values['pipelinechannel--string-not-empty-Output'] == 'true' condition-4: componentRef: name: comp-condition-4 dependentTasks: - automl-tabular-transform - merge-materialized-splits - string-not-empty - tabular-stats-and-example-gen inputs: artifacts: pipelinechannel--automl-tabular-transform-materialized_eval_split: taskOutputArtifact: outputArtifactKey: materialized_eval_split producerTask: automl-tabular-transform pipelinechannel--automl-tabular-transform-materialized_train_split: taskOutputArtifact: outputArtifactKey: materialized_train_split producerTask: automl-tabular-transform pipelinechannel--automl-tabular-transform-transform_output: taskOutputArtifact: outputArtifactKey: transform_output producerTask: automl-tabular-transform pipelinechannel--merge-materialized-splits-splits: taskOutputArtifact: outputArtifactKey: splits producerTask: merge-materialized-splits pipelinechannel--tabular-stats-and-example-gen-dataset_schema: taskOutputArtifact: outputArtifactKey: dataset_schema producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-eval_split: taskOutputArtifact: outputArtifactKey: eval_split producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-instance_baseline: taskOutputArtifact: outputArtifactKey: instance_baseline producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-metadata: taskOutputArtifact: outputArtifactKey: metadata producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-test_split: taskOutputArtifact: outputArtifactKey: test_split producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-train_split: taskOutputArtifact: outputArtifactKey: train_split producerTask: tabular-stats-and-example-gen parameters: pipelinechannel--cv_trainer_worker_pool_specs_override: componentInputParameter: pipelinechannel--cv_trainer_worker_pool_specs_override pipelinechannel--dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips pipelinechannel--disable_early_stopping: componentInputParameter: pipelinechannel--disable_early_stopping pipelinechannel--distill_batch_predict_machine_type: componentInputParameter: pipelinechannel--distill_batch_predict_machine_type pipelinechannel--distill_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_max_replica_count pipelinechannel--distill_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--distill_batch_predict_starting_replica_count pipelinechannel--encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: pipelinechannel--evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: pipelinechannel--evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: pipelinechannel--evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: pipelinechannel--evaluation_dataflow_starting_num_workers pipelinechannel--export_additional_model_without_custom_ops: componentInputParameter: pipelinechannel--export_additional_model_without_custom_ops pipelinechannel--fast_testing: componentInputParameter: pipelinechannel--fast_testing pipelinechannel--location: componentInputParameter: pipelinechannel--location pipelinechannel--model_description: componentInputParameter: pipelinechannel--model_description pipelinechannel--prediction_type: componentInputParameter: pipelinechannel--prediction_type pipelinechannel--project: componentInputParameter: pipelinechannel--project pipelinechannel--root_dir: componentInputParameter: pipelinechannel--root_dir pipelinechannel--run_distillation: componentInputParameter: pipelinechannel--run_distillation pipelinechannel--run_evaluation: componentInputParameter: pipelinechannel--run_evaluation pipelinechannel--set-optional-inputs-model_display_name: componentInputParameter: pipelinechannel--set-optional-inputs-model_display_name pipelinechannel--stage_1_num_parallel_trials: componentInputParameter: pipelinechannel--stage_1_num_parallel_trials pipelinechannel--stage_1_tuner_worker_pool_specs_override: componentInputParameter: pipelinechannel--stage_1_tuner_worker_pool_specs_override pipelinechannel--stage_2_num_parallel_trials: componentInputParameter: pipelinechannel--stage_2_num_parallel_trials pipelinechannel--stage_2_num_selected_trials: componentInputParameter: pipelinechannel--stage_2_num_selected_trials pipelinechannel--string-not-empty-Output: taskOutputParameter: outputParameterKey: Output producerTask: string-not-empty pipelinechannel--study_spec_parameters_override: componentInputParameter: pipelinechannel--study_spec_parameters_override pipelinechannel--tabular-stats-and-example-gen-downsampled_test_split_json: taskOutputParameter: outputParameterKey: downsampled_test_split_json producerTask: tabular-stats-and-example-gen pipelinechannel--tabular-stats-and-example-gen-test_split_json: taskOutputParameter: outputParameterKey: test_split_json producerTask: tabular-stats-and-example-gen pipelinechannel--target_column: componentInputParameter: pipelinechannel--target_column pipelinechannel--train_budget_milli_node_hours: componentInputParameter: pipelinechannel--train_budget_milli_node_hours pipelinechannel--transform_dataflow_disk_size_gb: componentInputParameter: pipelinechannel--transform_dataflow_disk_size_gb pipelinechannel--transform_dataflow_machine_type: componentInputParameter: pipelinechannel--transform_dataflow_machine_type pipelinechannel--transform_dataflow_max_num_workers: componentInputParameter: pipelinechannel--transform_dataflow_max_num_workers taskInfo: name: stage_1_tuning_result_artifact_uri_empty triggerPolicy: condition: inputs.parameter_values['pipelinechannel--string-not-empty-Output'] == 'false' merge-materialized-splits: cachingOptions: enableCache: true componentRef: name: comp-merge-materialized-splits dependentTasks: - automl-tabular-transform inputs: artifacts: split_0: taskOutputArtifact: outputArtifactKey: materialized_train_split producerTask: automl-tabular-transform split_1: taskOutputArtifact: outputArtifactKey: materialized_eval_split producerTask: automl-tabular-transform taskInfo: name: merge-materialized-splits string-not-empty: cachingOptions: enableCache: true componentRef: name: comp-string-not-empty inputs: parameters: value: componentInputParameter: pipelinechannel--stage_1_tuning_result_artifact_uri taskInfo: name: string-not-empty tabular-stats-and-example-gen: cachingOptions: enableCache: true componentRef: name: comp-tabular-stats-and-example-gen inputs: parameters: additional_experiments_json: componentInputParameter: pipelinechannel--additional_experiments data_source_bigquery_table_path: componentInputParameter: pipelinechannel--set-optional-inputs-data_source_bigquery_table_path data_source_csv_filenames: componentInputParameter: pipelinechannel--set-optional-inputs-data_source_csv_filenames dataflow_disk_size_gb: componentInputParameter: pipelinechannel--stats_and_example_gen_dataflow_disk_size_gb dataflow_machine_type: componentInputParameter: pipelinechannel--stats_and_example_gen_dataflow_machine_type dataflow_max_num_workers: componentInputParameter: pipelinechannel--stats_and_example_gen_dataflow_max_num_workers dataflow_service_account: componentInputParameter: pipelinechannel--dataflow_service_account dataflow_subnetwork: componentInputParameter: pipelinechannel--dataflow_subnetwork dataflow_use_public_ips: componentInputParameter: pipelinechannel--dataflow_use_public_ips enable_probabilistic_inference: componentInputParameter: pipelinechannel--enable_probabilistic_inference encryption_spec_key_name: componentInputParameter: pipelinechannel--encryption_spec_key_name location: componentInputParameter: pipelinechannel--location optimization_objective: componentInputParameter: pipelinechannel--optimization_objective optimization_objective_precision_value: componentInputParameter: pipelinechannel--optimization_objective_precision_value optimization_objective_recall_value: componentInputParameter: pipelinechannel--optimization_objective_recall_value predefined_split_key: componentInputParameter: pipelinechannel--predefined_split_key prediction_type: componentInputParameter: pipelinechannel--prediction_type project: componentInputParameter: pipelinechannel--project quantiles: componentInputParameter: pipelinechannel--quantiles root_dir: componentInputParameter: pipelinechannel--root_dir run_distillation: componentInputParameter: pipelinechannel--run_distillation stratified_split_key: componentInputParameter: pipelinechannel--stratified_split_key target_column_name: componentInputParameter: pipelinechannel--target_column test_fraction: componentInputParameter: pipelinechannel--test_fraction timestamp_split_key: componentInputParameter: pipelinechannel--timestamp_split_key training_fraction: componentInputParameter: pipelinechannel--training_fraction transformations: runtimeValue: constant: '[]' transformations_path: componentInputParameter: pipelinechannel--transformations validation_fraction: componentInputParameter: pipelinechannel--validation_fraction weight_column_name: componentInputParameter: pipelinechannel--weight_column taskInfo: name: tabular-stats-and-example-gen inputDefinitions: parameters: pipelinechannel--additional_experiments: parameterType: STRUCT pipelinechannel--cv_trainer_worker_pool_specs_override: parameterType: LIST pipelinechannel--dataflow_service_account: parameterType: STRING pipelinechannel--dataflow_subnetwork: parameterType: STRING pipelinechannel--dataflow_use_public_ips: parameterType: BOOLEAN pipelinechannel--disable_early_stopping: parameterType: BOOLEAN pipelinechannel--distill_batch_predict_machine_type: parameterType: STRING pipelinechannel--distill_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--distill_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--enable_probabilistic_inference: parameterType: BOOLEAN pipelinechannel--encryption_spec_key_name: parameterType: STRING pipelinechannel--evaluation_batch_explain_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_explain_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_explain_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_machine_type: parameterType: STRING pipelinechannel--evaluation_batch_predict_max_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_batch_predict_starting_replica_count: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_machine_type: parameterType: STRING pipelinechannel--evaluation_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--evaluation_dataflow_starting_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--export_additional_model_without_custom_ops: parameterType: BOOLEAN pipelinechannel--fast_testing: parameterType: BOOLEAN pipelinechannel--location: parameterType: STRING pipelinechannel--model_description: parameterType: STRING pipelinechannel--optimization_objective: parameterType: STRING pipelinechannel--optimization_objective_precision_value: parameterType: NUMBER_DOUBLE pipelinechannel--optimization_objective_recall_value: parameterType: NUMBER_DOUBLE pipelinechannel--predefined_split_key: parameterType: STRING pipelinechannel--prediction_type: parameterType: STRING pipelinechannel--project: parameterType: STRING pipelinechannel--quantiles: parameterType: LIST pipelinechannel--root_dir: parameterType: STRING pipelinechannel--run_distillation: parameterType: BOOLEAN pipelinechannel--run_evaluation: parameterType: BOOLEAN pipelinechannel--set-optional-inputs-data_source_bigquery_table_path: parameterType: STRING pipelinechannel--set-optional-inputs-data_source_csv_filenames: parameterType: STRING pipelinechannel--set-optional-inputs-model_display_name: parameterType: STRING pipelinechannel--stage_1_num_parallel_trials: parameterType: NUMBER_INTEGER pipelinechannel--stage_1_tuner_worker_pool_specs_override: parameterType: LIST pipelinechannel--stage_1_tuning_result_artifact_uri: parameterType: STRING pipelinechannel--stage_2_num_parallel_trials: parameterType: NUMBER_INTEGER pipelinechannel--stage_2_num_selected_trials: parameterType: NUMBER_INTEGER pipelinechannel--stats_and_example_gen_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--stats_and_example_gen_dataflow_machine_type: parameterType: STRING pipelinechannel--stats_and_example_gen_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--stratified_split_key: parameterType: STRING pipelinechannel--study_spec_parameters_override: parameterType: LIST pipelinechannel--target_column: parameterType: STRING pipelinechannel--test_fraction: parameterType: NUMBER_DOUBLE pipelinechannel--timestamp_split_key: parameterType: STRING pipelinechannel--train_budget_milli_node_hours: parameterType: NUMBER_DOUBLE pipelinechannel--training_fraction: parameterType: NUMBER_DOUBLE pipelinechannel--transform_dataflow_disk_size_gb: parameterType: NUMBER_INTEGER pipelinechannel--transform_dataflow_machine_type: parameterType: STRING pipelinechannel--transform_dataflow_max_num_workers: parameterType: NUMBER_INTEGER pipelinechannel--transformations: parameterType: STRING pipelinechannel--validation_fraction: parameterType: NUMBER_DOUBLE pipelinechannel--weight_column: parameterType: STRING outputDefinitions: artifacts: feature-attribution-2-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 feature-attribution-3-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 feature-attribution-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-2-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-3-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 comp-feature-attribution: executorLabel: exec-feature-attribution inputDefinitions: artifacts: predictions_gcs_source: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true parameters: dataflow_disk_size: defaultValue: 50.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-4 isOptional: true parameterType: STRING dataflow_max_workers_num: defaultValue: 5.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN dataflow_workers_num: defaultValue: 1.0 isOptional: true parameterType: NUMBER_INTEGER encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: defaultValue: us-central1 isOptional: true parameterType: STRING predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-feature-attribution-2: executorLabel: exec-feature-attribution-2 inputDefinitions: artifacts: predictions_gcs_source: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true parameters: dataflow_disk_size: defaultValue: 50.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-4 isOptional: true parameterType: STRING dataflow_max_workers_num: defaultValue: 5.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN dataflow_workers_num: defaultValue: 1.0 isOptional: true parameterType: NUMBER_INTEGER encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: defaultValue: us-central1 isOptional: true parameterType: STRING predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-feature-attribution-3: executorLabel: exec-feature-attribution-3 inputDefinitions: artifacts: predictions_gcs_source: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true parameters: dataflow_disk_size: defaultValue: 50.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-4 isOptional: true parameterType: STRING dataflow_max_workers_num: defaultValue: 5.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN dataflow_workers_num: defaultValue: 1.0 isOptional: true parameterType: NUMBER_INTEGER encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: defaultValue: us-central1 isOptional: true parameterType: STRING predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-importer: executorLabel: exec-importer inputDefinitions: parameters: uri: parameterType: STRING outputDefinitions: artifacts: artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 comp-merge-materialized-splits: executorLabel: exec-merge-materialized-splits inputDefinitions: artifacts: split_0: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 split_1: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 outputDefinitions: artifacts: splits: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 comp-model-batch-explanation: executorLabel: exec-model-batch-explanation inputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-batch-explanation-2: executorLabel: exec-model-batch-explanation-2 inputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-batch-explanation-3: executorLabel: exec-model-batch-explanation-3 inputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-batch-predict: executorLabel: exec-model-batch-predict inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-batch-predict-2: executorLabel: exec-model-batch-predict-2 inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-batch-predict-3: executorLabel: exec-model-batch-predict-3 inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-batch-predict-4: executorLabel: exec-model-batch-predict-4 inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-batch-predict-5: executorLabel: exec-model-batch-predict-5 inputDefinitions: artifacts: unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: accelerator_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER accelerator_type: defaultValue: '' isOptional: true parameterType: STRING bigquery_destination_output_uri: defaultValue: '' isOptional: true parameterType: STRING bigquery_source_input_uri: defaultValue: '' isOptional: true parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT gcs_destination_output_uri_prefix: defaultValue: '' isOptional: true parameterType: STRING gcs_source_uris: defaultValue: [] isOptional: true parameterType: LIST generate_explanation: defaultValue: false isOptional: true parameterType: BOOLEAN instances_format: defaultValue: jsonl isOptional: true parameterType: STRING job_display_name: parameterType: STRING labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING machine_type: defaultValue: '' isOptional: true parameterType: STRING manual_batch_tuning_parameters_batch_size: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER max_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER model_parameters: defaultValue: {} isOptional: true parameterType: STRUCT predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING project: parameterType: STRING starting_replica_count: defaultValue: 0.0 isOptional: true parameterType: NUMBER_INTEGER outputDefinitions: artifacts: batchpredictionjob: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 bigquery_output_table: artifactType: schemaTitle: google.BQTable schemaVersion: 0.0.1 gcs_output_directory: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-evaluation: executorLabel: exec-model-evaluation inputDefinitions: artifacts: batch_prediction_job: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 parameters: dataflow_disk_size: defaultValue: 50.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-4 isOptional: true parameterType: STRING dataflow_max_workers_num: defaultValue: 100.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN dataflow_workers_num: defaultValue: 10.0 isOptional: true parameterType: NUMBER_INTEGER encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING example_weight_column: defaultValue: '' isOptional: true parameterType: STRING ground_truth_column: parameterType: STRING ground_truth_format: defaultValue: jsonl isOptional: true parameterType: STRING location: defaultValue: us-central1 isOptional: true parameterType: STRING prediction_id_column: defaultValue: '' isOptional: true parameterType: STRING prediction_label_column: defaultValue: '' isOptional: true parameterType: STRING prediction_score_column: defaultValue: '' isOptional: true parameterType: STRING predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING problem_type: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-evaluation-2: executorLabel: exec-model-evaluation-2 inputDefinitions: artifacts: batch_prediction_job: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 parameters: dataflow_disk_size: defaultValue: 50.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-4 isOptional: true parameterType: STRING dataflow_max_workers_num: defaultValue: 100.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN dataflow_workers_num: defaultValue: 10.0 isOptional: true parameterType: NUMBER_INTEGER encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING example_weight_column: defaultValue: '' isOptional: true parameterType: STRING ground_truth_column: parameterType: STRING ground_truth_format: defaultValue: jsonl isOptional: true parameterType: STRING location: defaultValue: us-central1 isOptional: true parameterType: STRING prediction_id_column: defaultValue: '' isOptional: true parameterType: STRING prediction_label_column: defaultValue: '' isOptional: true parameterType: STRING prediction_score_column: defaultValue: '' isOptional: true parameterType: STRING predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING problem_type: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-evaluation-3: executorLabel: exec-model-evaluation-3 inputDefinitions: artifacts: batch_prediction_job: artifactType: schemaTitle: google.VertexBatchPredictionJob schemaVersion: 0.0.1 parameters: dataflow_disk_size: defaultValue: 50.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-4 isOptional: true parameterType: STRING dataflow_max_workers_num: defaultValue: 100.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN dataflow_workers_num: defaultValue: 10.0 isOptional: true parameterType: NUMBER_INTEGER encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING example_weight_column: defaultValue: '' isOptional: true parameterType: STRING ground_truth_column: parameterType: STRING ground_truth_format: defaultValue: jsonl isOptional: true parameterType: STRING location: defaultValue: us-central1 isOptional: true parameterType: STRING prediction_id_column: defaultValue: '' isOptional: true parameterType: STRING prediction_label_column: defaultValue: '' isOptional: true parameterType: STRING prediction_score_column: defaultValue: '' isOptional: true parameterType: STRING predictions_format: defaultValue: jsonl isOptional: true parameterType: STRING problem_type: parameterType: STRING project: parameterType: STRING root_dir: parameterType: STRING outputDefinitions: artifacts: evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-evaluation-import: executorLabel: exec-model-evaluation-import inputDefinitions: artifacts: classification_metrics: artifactType: schemaTitle: google.ClassificationMetrics schemaVersion: 0.0.1 isOptional: true explanation: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true forecasting_metrics: artifactType: schemaTitle: google.ForecastingMetrics schemaVersion: 0.0.1 isOptional: true metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 regression_metrics: artifactType: schemaTitle: google.RegressionMetrics schemaVersion: 0.0.1 isOptional: true parameters: dataset_path: defaultValue: '' isOptional: true parameterType: STRING dataset_paths: defaultValue: [] isOptional: true parameterType: LIST dataset_type: defaultValue: '' isOptional: true parameterType: STRING display_name: defaultValue: '' isOptional: true parameterType: STRING problem_type: isOptional: true parameterType: STRING outputDefinitions: parameters: gcp_resources: parameterType: STRING comp-model-evaluation-import-2: executorLabel: exec-model-evaluation-import-2 inputDefinitions: artifacts: classification_metrics: artifactType: schemaTitle: google.ClassificationMetrics schemaVersion: 0.0.1 isOptional: true explanation: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true forecasting_metrics: artifactType: schemaTitle: google.ForecastingMetrics schemaVersion: 0.0.1 isOptional: true metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 regression_metrics: artifactType: schemaTitle: google.RegressionMetrics schemaVersion: 0.0.1 isOptional: true parameters: dataset_path: defaultValue: '' isOptional: true parameterType: STRING dataset_paths: defaultValue: [] isOptional: true parameterType: LIST dataset_type: defaultValue: '' isOptional: true parameterType: STRING display_name: defaultValue: '' isOptional: true parameterType: STRING problem_type: isOptional: true parameterType: STRING outputDefinitions: parameters: gcp_resources: parameterType: STRING comp-model-evaluation-import-3: executorLabel: exec-model-evaluation-import-3 inputDefinitions: artifacts: classification_metrics: artifactType: schemaTitle: google.ClassificationMetrics schemaVersion: 0.0.1 isOptional: true explanation: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true forecasting_metrics: artifactType: schemaTitle: google.ForecastingMetrics schemaVersion: 0.0.1 isOptional: true metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 isOptional: true model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 regression_metrics: artifactType: schemaTitle: google.RegressionMetrics schemaVersion: 0.0.1 isOptional: true parameters: dataset_path: defaultValue: '' isOptional: true parameterType: STRING dataset_paths: defaultValue: [] isOptional: true parameterType: LIST dataset_type: defaultValue: '' isOptional: true parameterType: STRING display_name: defaultValue: '' isOptional: true parameterType: STRING problem_type: isOptional: true parameterType: STRING outputDefinitions: parameters: gcp_resources: parameterType: STRING comp-model-upload: executorLabel: exec-model-upload inputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: description: defaultValue: '' isOptional: true parameterType: STRING display_name: parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING project: parameterType: STRING outputDefinitions: artifacts: model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-upload-2: executorLabel: exec-model-upload-2 inputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: description: defaultValue: '' isOptional: true parameterType: STRING display_name: parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING project: parameterType: STRING outputDefinitions: artifacts: model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-model-upload-3: executorLabel: exec-model-upload-3 inputDefinitions: artifacts: explanation_metadata_artifact: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 isOptional: true unmanaged_container_model: artifactType: schemaTitle: google.UnmanagedContainerModel schemaVersion: 0.0.1 isOptional: true parameters: description: defaultValue: '' isOptional: true parameterType: STRING display_name: parameterType: STRING encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING explanation_metadata: defaultValue: {} isOptional: true parameterType: STRUCT explanation_parameters: defaultValue: {} isOptional: true parameterType: STRUCT labels: defaultValue: {} isOptional: true parameterType: STRUCT location: defaultValue: us-central1 isOptional: true parameterType: STRING project: parameterType: STRING outputDefinitions: artifacts: model: artifactType: schemaTitle: google.VertexModel schemaVersion: 0.0.1 parameters: gcp_resources: parameterType: STRING comp-read-input-uri: executorLabel: exec-read-input-uri inputDefinitions: artifacts: split_uri: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 outputDefinitions: parameters: Output: parameterType: LIST comp-read-input-uri-2: executorLabel: exec-read-input-uri-2 inputDefinitions: artifacts: split_uri: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 outputDefinitions: parameters: Output: parameterType: LIST comp-set-optional-inputs: executorLabel: exec-set-optional-inputs inputDefinitions: artifacts: vertex_dataset: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: data_source_bigquery_table_path: parameterType: STRING data_source_csv_filenames: parameterType: STRING location: parameterType: STRING model_display_name: parameterType: STRING project: parameterType: STRING outputDefinitions: parameters: data_source_bigquery_table_path: parameterType: STRING data_source_csv_filenames: parameterType: STRING model_display_name: parameterType: STRING comp-string-not-empty: executorLabel: exec-string-not-empty inputDefinitions: parameters: value: parameterType: STRING outputDefinitions: parameters: Output: parameterType: STRING comp-tabular-stats-and-example-gen: executorLabel: exec-tabular-stats-and-example-gen inputDefinitions: parameters: additional_experiments: defaultValue: '' isOptional: true parameterType: STRING additional_experiments_json: defaultValue: {} isOptional: true parameterType: STRUCT data_source_bigquery_table_path: defaultValue: '' isOptional: true parameterType: STRING data_source_csv_filenames: defaultValue: '' isOptional: true parameterType: STRING dataflow_disk_size_gb: defaultValue: 40.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_machine_type: defaultValue: n1-standard-16 isOptional: true parameterType: STRING dataflow_max_num_workers: defaultValue: 25.0 isOptional: true parameterType: NUMBER_INTEGER dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN enable_probabilistic_inference: defaultValue: false isOptional: true parameterType: BOOLEAN encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING location: parameterType: STRING optimization_objective: defaultValue: '' isOptional: true parameterType: STRING optimization_objective_precision_value: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE optimization_objective_recall_value: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE predefined_split_key: defaultValue: '' isOptional: true parameterType: STRING prediction_type: parameterType: STRING project: parameterType: STRING quantiles: defaultValue: [] isOptional: true parameterType: LIST request_type: defaultValue: COLUMN_STATS_ONLY isOptional: true parameterType: STRING root_dir: parameterType: STRING run_distillation: defaultValue: false isOptional: true parameterType: BOOLEAN stratified_split_key: defaultValue: '' isOptional: true parameterType: STRING target_column_name: parameterType: STRING test_fraction: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE timestamp_split_key: defaultValue: '' isOptional: true parameterType: STRING training_fraction: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE transformations: parameterType: STRING transformations_path: defaultValue: '' isOptional: true parameterType: STRING validation_fraction: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE weight_column_name: defaultValue: '' isOptional: true parameterType: STRING outputDefinitions: artifacts: dataset_schema: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 dataset_stats: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 eval_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 instance_baseline: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 metadata: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 test_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 train_split: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 parameters: downsampled_test_split_json: parameterType: LIST gcp_resources: parameterType: STRING test_split_json: parameterType: LIST comp-write-bp-result-path: executorLabel: exec-write-bp-result-path inputDefinitions: artifacts: bp_job: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 outputDefinitions: artifacts: result: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 comp-write-bp-result-path-2: executorLabel: exec-write-bp-result-path-2 inputDefinitions: artifacts: bp_job: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 outputDefinitions: artifacts: result: artifactType: schemaTitle: system.Dataset schemaVersion: 0.0.1 deploymentSpec: executors: exec-automl-tabular-cv-trainer: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-cv-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"l2l_cv_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}", "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"--component_id={{$.pipeline_task_uuid}}\", \"--training_base_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/train\", \"--num_parallel_trial=", "{{$.inputs.parameters[''num_parallel_trials'']}}", "\", \"--single_run_max_secs=", "{{$.inputs.parameters[''single_run_max_secs'']}}", "\", \"--deadline_hours=", "{{$.inputs.parameters[''deadline_hours'']}}", "\", \"--valid_trials_completed_threshold=0.7\", \"--num_selected_trials=", "{{$.inputs.parameters[''num_selected_trials'']}}", "\", \"--num_selected_features=", "{{$.inputs.parameters[''num_selected_features'']}}", "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_cv_splits=", "{{$.inputs.artifacts[''materialized_cv_splits''].uri}}", "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}", "\", \"--tuning_result_output_path=", "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=", "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_custom_job=true\", \"--use_json=true\", \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-cv-trainer-2: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-cv-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"l2l_cv_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}", "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"--component_id={{$.pipeline_task_uuid}}\", \"--training_base_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/train\", \"--num_parallel_trial=", "{{$.inputs.parameters[''num_parallel_trials'']}}", "\", \"--single_run_max_secs=", "{{$.inputs.parameters[''single_run_max_secs'']}}", "\", \"--deadline_hours=", "{{$.inputs.parameters[''deadline_hours'']}}", "\", \"--valid_trials_completed_threshold=0.7\", \"--num_selected_trials=", "{{$.inputs.parameters[''num_selected_trials'']}}", "\", \"--num_selected_features=", "{{$.inputs.parameters[''num_selected_features'']}}", "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_cv_splits=", "{{$.inputs.artifacts[''materialized_cv_splits''].uri}}", "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}", "\", \"--tuning_result_output_path=", "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=", "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_custom_job=true\", \"--use_json=true\", \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-ensemble: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-ensemble-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-highmem-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"ensemble\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}", "\", \"--model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/model\", \"--custom_model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/custom_model\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--export_custom_model=", "{{$.inputs.parameters[''export_additional_model_without_custom_ops'']}}", "\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}", "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}", "\", \"--instance_baseline_path=", "{{$.inputs.artifacts[''instance_baseline''].uri}}", "\", \"--warmup_data=", "{{$.inputs.artifacts[''warmup_data''].uri}}", "\", \"--prediction_docker_uri=", "us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev", "\", \"--model_path=", "{{$.outputs.artifacts[''model''].uri}}", "\", \"--custom_model_path=", "{{$.outputs.artifacts[''model_without_custom_ops''].uri}}", "\", \"--explanation_metadata_path=", "{{$.outputs.parameters[''explanation_metadata''].output_file}}", ",", "{{$.outputs.artifacts[''explanation_metadata_artifact''].uri}}", "\", \"--explanation_parameters_path=", "{{$.outputs.parameters[''explanation_parameters''].output_file}}", "\", \"--model_architecture_path=", "{{$.outputs.artifacts[''model_architecture''].uri}}", "\", \"--use_json=true\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-ensemble-2: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-ensemble-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-highmem-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"ensemble\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}", "\", \"--model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/model\", \"--custom_model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/custom_model\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--export_custom_model=", "{{$.inputs.parameters[''export_additional_model_without_custom_ops'']}}", "\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}", "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}", "\", \"--instance_baseline_path=", "{{$.inputs.artifacts[''instance_baseline''].uri}}", "\", \"--warmup_data=", "{{$.inputs.artifacts[''warmup_data''].uri}}", "\", \"--prediction_docker_uri=", "us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev", "\", \"--model_path=", "{{$.outputs.artifacts[''model''].uri}}", "\", \"--custom_model_path=", "{{$.outputs.artifacts[''model_without_custom_ops''].uri}}", "\", \"--explanation_metadata_path=", "{{$.outputs.parameters[''explanation_metadata''].output_file}}", ",", "{{$.outputs.artifacts[''explanation_metadata_artifact''].uri}}", "\", \"--explanation_parameters_path=", "{{$.outputs.parameters[''explanation_parameters''].output_file}}", "\", \"--model_architecture_path=", "{{$.outputs.artifacts[''model_architecture''].uri}}", "\", \"--use_json=true\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-ensemble-3: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-ensemble-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-highmem-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"ensemble\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}", "\", \"--model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/model\", \"--custom_model_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/custom_model\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--export_custom_model=", "{{$.inputs.parameters[''export_additional_model_without_custom_ops'']}}", "\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}", "\", \"--tuning_result_input_path=", "{{$.inputs.artifacts[''tuning_result_input''].uri}}", "\", \"--instance_baseline_path=", "{{$.inputs.artifacts[''instance_baseline''].uri}}", "\", \"--warmup_data=", "{{$.inputs.artifacts[''warmup_data''].uri}}", "\", \"--prediction_docker_uri=", "us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev", "\", \"--model_path=", "{{$.outputs.artifacts[''model''].uri}}", "\", \"--custom_model_path=", "{{$.outputs.artifacts[''model_without_custom_ops''].uri}}", "\", \"--explanation_metadata_path=", "{{$.outputs.parameters[''explanation_metadata''].output_file}}", ",", "{{$.outputs.artifacts[''explanation_metadata_artifact''].uri}}", "\", \"--explanation_parameters_path=", "{{$.outputs.parameters[''explanation_parameters''].output_file}}", "\", \"--model_architecture_path=", "{{$.outputs.artifacts[''model_architecture''].uri}}", "\", \"--use_json=true\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-finalizer: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-finalizer-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"cancel_l2l_tuner\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--cleanup_lro_job_infos=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-infra-validator: container: args: - --executor_input - '{{$}}' image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev resources: cpuLimit: 8.0 memoryLimit: 52.0 exec-automl-tabular-infra-validator-2: container: args: - --executor_input - '{{$}}' image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev resources: cpuLimit: 8.0 memoryLimit: 52.0 exec-automl-tabular-infra-validator-3: container: args: - --executor_input - '{{$}}' image: us-docker.pkg.dev/vertex-ai/automl-tabular/prediction-server:dev resources: cpuLimit: 8.0 memoryLimit: 52.0 exec-automl-tabular-stage-1-tuner: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-stage-1-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"l2l_stage_1_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}", "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"--feature_selection_result_path=", "{{$.inputs.artifacts[''feature_ranking''].uri}}", "\", \"--disable_early_stopping=", "{{$.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'']}}", "\", \"--num_selected_features=", "{{$.inputs.parameters[''num_selected_features'']}}", "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_train_split=", "{{$.inputs.artifacts[''materialized_train_split''].uri}}", "\", \"--materialized_eval_split=", "{{$.inputs.artifacts[''materialized_eval_split''].uri}}", "\", \"--is_distill=", "{{$.inputs.parameters[''run_distillation'']}}", "\", \"--tuning_result_output_path=", "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=", "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_json=true\", \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-stage-1-tuner-2: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-stage-1-tuner-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"l2l_stage_1_tuner\", \"--transform_output_path=", "{{$.inputs.artifacts[''transform_output''].uri}}", "\", \"--training_docker_uri=", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"--feature_selection_result_path=", "{{$.inputs.artifacts[''feature_ranking''].uri}}", "\", \"--disable_early_stopping=", "{{$.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'']}}", "\", \"--num_selected_features=", "{{$.inputs.parameters[''num_selected_features'']}}", "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--materialized_train_split=", "{{$.inputs.artifacts[''materialized_train_split''].uri}}", "\", \"--materialized_eval_split=", "{{$.inputs.artifacts[''materialized_eval_split''].uri}}", "\", \"--is_distill=", "{{$.inputs.parameters[''run_distillation'']}}", "\", \"--tuning_result_output_path=", "{{$.outputs.artifacts[''tuning_result_output''].uri}}", "\", \"--kms_key_name=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--execution_metrics_path=", "{{$.outputs.parameters[''execution_metrics''].output_file}}", "\", \"--use_json=true\", \"--log_level=ERROR\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-transform: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"transform\", \"--transform_output_artifact_path=", "{{$.outputs.artifacts[''transform_output''].uri}}", "\", \"--transform_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform\", \"--materialized_splits_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform_materialized\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}", "\", \"--train_split=", "{{$.inputs.artifacts[''train_split''].uri}}", "\", \"--eval_split=", "{{$.inputs.artifacts[''eval_split''].uri}}", "\", \"--test_split=", "{{$.inputs.artifacts[''test_split''].uri}}", "\", \"--materialized_train_split=", "{{$.outputs.artifacts[''materialized_train_split''].uri}}", "\", \"--materialized_eval_split=", "{{$.outputs.artifacts[''materialized_eval_split''].uri}}", "\", \"--materialized_test_split=", "{{$.outputs.artifacts[''materialized_test_split''].uri}}", "\", \"--training_schema_path=", "{{$.outputs.artifacts[''training_schema_uri''].uri}}", "\", \"--job_name=automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}", "\", \"--dataflow_project=", "{{$.inputs.parameters[''project'']}}", "\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--dataflow_staging_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_staging\", \"--dataflow_tmp_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_tmp\", \"--dataflow_max_num_workers=", "{{$.inputs.parameters[''dataflow_max_num_workers'']}}", "\", \"--dataflow_machine_type=", "{{$.inputs.parameters[''dataflow_machine_type'']}}", "\", \"--dataflow_worker_container_image=", "us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:dev", "\", \"--dataflow_disk_size_gb=", "{{$.inputs.parameters[''dataflow_disk_size_gb'']}}", "\", \"--dataflow_subnetwork_fully_qualified=", "{{$.inputs.parameters[''dataflow_subnetwork'']}}", "\", \"--dataflow_use_public_ips=", "{{$.inputs.parameters[''dataflow_use_public_ips'']}}", "\", \"--dataflow_kms_key=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--dataflow_service_account=", "{{$.inputs.parameters[''dataflow_service_account'']}}", "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\", \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-automl-tabular-transform-2: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"transform\", \"--transform_output_artifact_path=", "{{$.outputs.artifacts[''transform_output''].uri}}", "\", \"--transform_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform\", \"--materialized_splits_output_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform_materialized\", \"--metadata_path=", "{{$.inputs.artifacts[''metadata''].uri}}", "\", \"--dataset_schema_path=", "{{$.inputs.artifacts[''dataset_schema''].uri}}", "\", \"--train_split=", "{{$.inputs.artifacts[''train_split''].uri}}", "\", \"--eval_split=", "{{$.inputs.artifacts[''eval_split''].uri}}", "\", \"--test_split=", "{{$.inputs.artifacts[''test_split''].uri}}", "\", \"--materialized_train_split=", "{{$.outputs.artifacts[''materialized_train_split''].uri}}", "\", \"--materialized_eval_split=", "{{$.outputs.artifacts[''materialized_eval_split''].uri}}", "\", \"--materialized_test_split=", "{{$.outputs.artifacts[''materialized_test_split''].uri}}", "\", \"--training_schema_path=", "{{$.outputs.artifacts[''training_schema_uri''].uri}}", "\", \"--job_name=automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}", "\", \"--dataflow_project=", "{{$.inputs.parameters[''project'']}}", "\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--dataflow_staging_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_staging\", \"--dataflow_tmp_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_tmp\", \"--dataflow_max_num_workers=", "{{$.inputs.parameters[''dataflow_max_num_workers'']}}", "\", \"--dataflow_machine_type=", "{{$.inputs.parameters[''dataflow_machine_type'']}}", "\", \"--dataflow_worker_container_image=", "us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:dev", "\", \"--dataflow_disk_size_gb=", "{{$.inputs.parameters[''dataflow_disk_size_gb'']}}", "\", \"--dataflow_subnetwork_fully_qualified=", "{{$.inputs.parameters[''dataflow_subnetwork'']}}", "\", \"--dataflow_use_public_ips=", "{{$.inputs.parameters[''dataflow_use_public_ips'']}}", "\", \"--dataflow_kms_key=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--dataflow_service_account=", "{{$.inputs.parameters[''dataflow_service_account'']}}", "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\", \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-bool-identity: container: args: - --executor_input - '{{$}}' - --function_to_execute - _bool_identity command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _bool_identity(value: bool) -> str:\n \"\"\"Returns boolean\ \ value.\n\n Args:\n value: Boolean value to return\n\n Returns:\n\ \ Boolean value.\n \"\"\"\n return 'true' if value else 'false'\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-bool-identity-2: container: args: - --executor_input - '{{$}}' - --function_to_execute - _bool_identity command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _bool_identity(value: bool) -> str:\n \"\"\"Returns boolean\ \ value.\n\n Args:\n value: Boolean value to return\n\n Returns:\n\ \ Boolean value.\n \"\"\"\n return 'true' if value else 'false'\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-bool-identity-3: container: args: - --executor_input - '{{$}}' - --function_to_execute - _bool_identity command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _bool_identity(value: bool) -> str:\n \"\"\"Returns boolean\ \ value.\n\n Args:\n value: Boolean value to return\n\n Returns:\n\ \ Boolean value.\n \"\"\"\n return 'true' if value else 'false'\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-calculate-training-parameters: container: args: - --executor_input - '{{$}}' - --function_to_execute - _calculate_training_parameters command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _calculate_training_parameters(\n stage_1_num_parallel_trials:\ \ int,\n train_budget_milli_node_hours: float,\n stage_2_num_parallel_trials:\ \ int,\n run_distillation: bool,\n is_skip_architecture_search: bool\ \ = False,\n fast_testing: bool = False,\n) -> NamedTuple('Outputs',\ \ [\n ('stage_1_deadline_hours', float), ('stage_1_num_selected_trials',\ \ int),\n ('stage_1_single_run_max_secs', int), ('stage_2_deadline_hours',\ \ float),\n ('stage_2_single_run_max_secs', int),\n ('distill_stage_1_deadline_hours',\ \ float), ('reduce_search_space_mode', str)\n]):\n \"\"\"Calculates training\ \ parameters.\n\n Args:\n stage_1_num_parallel_trials: Number of parallel\ \ trails for stage 1.\n train_budget_milli_node_hours: The train budget\ \ of creating this model,\n expressed in milli node hours i.e. 1,000\ \ value in this field means 1 node\n hour.\n stage_2_num_parallel_trials:\ \ Number of parallel trails for stage 2.\n run_distillation: Whether\ \ to run distill in the training pipeline.\n is_skip_architecture_search:\ \ If component is being called in the\n skip_architecture_search pipeline.\n\ \ fast_testing: Internal flag used for presubmit tests.\n\n Returns:\n\ \ stage_1_deadline_hours: Maximum number of hours to run stage 1.\n\ \ stage_1_num_selected_trials: Number of selected trails for stage\ \ 1.\n stage_1_single_run_max_secs: Maximum number seconds to for a\ \ single stage\n 1\n training trial.\n stage_2_deadline_hours:\ \ Maximum number of hours to run stage 2.\n stage_2_single_run_max_secs:\ \ Maximum number seconds to for a single stage\n 2\n training\ \ trial.\n distill_stage_1_deadline_hours: Maximum number of hours\ \ to run stage 1 for\n the model distillation.\n reduce_search_space_mode:\ \ The reduce search space mode. Possible values:\n minimal, regular,\ \ full.\n \"\"\"\n # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\ \ import collections\n import math\n # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\ \ num_folds = 5\n distill_total_trials = 100\n\n stage_1_deadline_hours\ \ = -1.0\n stage_1_num_selected_trials = -1\n stage_1_single_run_max_secs\ \ = -1\n stage_2_deadline_hours = -1.0\n stage_2_single_run_max_secs =\ \ -1\n distill_stage_1_deadline_hours = 1.0\n reduce_search_space_mode\ \ = 'regular'\n\n if is_skip_architecture_search:\n stage_2_deadline_hours\ \ = train_budget_milli_node_hours / 1000.0\n stage_2_single_run_max_secs\ \ = int(stage_2_deadline_hours * 3600.0 / 1.3)\n else:\n hours = float(train_budget_milli_node_hours)\ \ / 1000.0\n multiplier = stage_1_num_parallel_trials * hours / 500.0\n\ \ stage_1_single_run_max_secs = int(math.sqrt(multiplier) * 2400.0)\n\ \ phase_2_rounds = int(\n math.sqrt(multiplier) * 100 / stage_2_num_parallel_trials\ \ + 0.5)\n if phase_2_rounds < 1:\n phase_2_rounds = 1\n\n #\ \ All of magic number \"1.3\" above is because the trial doesn't\n #\ \ always finish in time_per_trial. 1.3 is an empirical safety margin here.\n\ \ stage_1_deadline_secs = int(hours * 3600.0 - 1.3 *\n \ \ stage_1_single_run_max_secs * phase_2_rounds)\n\n \ \ if stage_1_deadline_secs < hours * 3600.0 * 0.5:\n stage_1_deadline_secs\ \ = int(hours * 3600.0 * 0.5)\n # Phase 1 deadline is the same as phase\ \ 2 deadline in this case. Phase 2\n # can't finish in time after the\ \ deadline is cut, so adjust the time per\n # trial to meet the deadline.\n\ \ stage_1_single_run_max_secs = int(stage_1_deadline_secs /\n \ \ (1.3 * phase_2_rounds))\n\n reduce_search_space_mode\ \ = 'minimal'\n if multiplier > 2:\n reduce_search_space_mode =\ \ 'regular'\n if multiplier > 4:\n reduce_search_space_mode = 'full'\n\ \n # Stage 2 number of trials is stage_1_num_selected_trials *\n #\ \ num_folds, which should be equal to phase_2_rounds *\n # stage_2_num_parallel_trials.\ \ Use this information to calculate\n # stage_1_num_selected_trials:\n\ \ stage_1_num_selected_trials = int(phase_2_rounds *\n \ \ stage_2_num_parallel_trials / num_folds)\n stage_1_deadline_hours\ \ = stage_1_deadline_secs / 3600.0\n\n stage_2_deadline_hours = hours\ \ - stage_1_deadline_hours\n stage_2_single_run_max_secs = stage_1_single_run_max_secs\n\ \n if run_distillation:\n # All of magic number \"1.3\" above is\ \ because the trial doesn't always\n # finish in time_per_trial. 1.3\ \ is an empirical safety margin here.\n distill_stage_1_deadline_hours\ \ = math.ceil(\n float(distill_total_trials) / stage_1_num_parallel_trials\n\ \ ) * stage_1_single_run_max_secs * 1.3 / 3600.0\n\n if fast_testing:\n\ \ distill_stage_1_deadline_hours = 0.2\n stage_1_deadline_hours =\ \ 0.2\n stage_1_single_run_max_secs = 1\n stage_2_deadline_hours =\ \ 0.2\n stage_2_single_run_max_secs = 1\n\n return collections.namedtuple('Outputs',\ \ [\n 'stage_1_deadline_hours', 'stage_1_num_selected_trials',\n \ \ 'stage_1_single_run_max_secs', 'stage_2_deadline_hours',\n 'stage_2_single_run_max_secs',\ \ 'distill_stage_1_deadline_hours',\n 'reduce_search_space_mode'\n\ \ ])(stage_1_deadline_hours, stage_1_num_selected_trials,\n stage_1_single_run_max_secs,\ \ stage_2_deadline_hours,\n stage_2_single_run_max_secs, distill_stage_1_deadline_hours,\n\ \ reduce_search_space_mode)\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-calculate-training-parameters-2: container: args: - --executor_input - '{{$}}' - --function_to_execute - _calculate_training_parameters command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _calculate_training_parameters(\n stage_1_num_parallel_trials:\ \ int,\n train_budget_milli_node_hours: float,\n stage_2_num_parallel_trials:\ \ int,\n run_distillation: bool,\n is_skip_architecture_search: bool\ \ = False,\n fast_testing: bool = False,\n) -> NamedTuple('Outputs',\ \ [\n ('stage_1_deadline_hours', float), ('stage_1_num_selected_trials',\ \ int),\n ('stage_1_single_run_max_secs', int), ('stage_2_deadline_hours',\ \ float),\n ('stage_2_single_run_max_secs', int),\n ('distill_stage_1_deadline_hours',\ \ float), ('reduce_search_space_mode', str)\n]):\n \"\"\"Calculates training\ \ parameters.\n\n Args:\n stage_1_num_parallel_trials: Number of parallel\ \ trails for stage 1.\n train_budget_milli_node_hours: The train budget\ \ of creating this model,\n expressed in milli node hours i.e. 1,000\ \ value in this field means 1 node\n hour.\n stage_2_num_parallel_trials:\ \ Number of parallel trails for stage 2.\n run_distillation: Whether\ \ to run distill in the training pipeline.\n is_skip_architecture_search:\ \ If component is being called in the\n skip_architecture_search pipeline.\n\ \ fast_testing: Internal flag used for presubmit tests.\n\n Returns:\n\ \ stage_1_deadline_hours: Maximum number of hours to run stage 1.\n\ \ stage_1_num_selected_trials: Number of selected trails for stage\ \ 1.\n stage_1_single_run_max_secs: Maximum number seconds to for a\ \ single stage\n 1\n training trial.\n stage_2_deadline_hours:\ \ Maximum number of hours to run stage 2.\n stage_2_single_run_max_secs:\ \ Maximum number seconds to for a single stage\n 2\n training\ \ trial.\n distill_stage_1_deadline_hours: Maximum number of hours\ \ to run stage 1 for\n the model distillation.\n reduce_search_space_mode:\ \ The reduce search space mode. Possible values:\n minimal, regular,\ \ full.\n \"\"\"\n # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\ \ import collections\n import math\n # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\ \ num_folds = 5\n distill_total_trials = 100\n\n stage_1_deadline_hours\ \ = -1.0\n stage_1_num_selected_trials = -1\n stage_1_single_run_max_secs\ \ = -1\n stage_2_deadline_hours = -1.0\n stage_2_single_run_max_secs =\ \ -1\n distill_stage_1_deadline_hours = 1.0\n reduce_search_space_mode\ \ = 'regular'\n\n if is_skip_architecture_search:\n stage_2_deadline_hours\ \ = train_budget_milli_node_hours / 1000.0\n stage_2_single_run_max_secs\ \ = int(stage_2_deadline_hours * 3600.0 / 1.3)\n else:\n hours = float(train_budget_milli_node_hours)\ \ / 1000.0\n multiplier = stage_1_num_parallel_trials * hours / 500.0\n\ \ stage_1_single_run_max_secs = int(math.sqrt(multiplier) * 2400.0)\n\ \ phase_2_rounds = int(\n math.sqrt(multiplier) * 100 / stage_2_num_parallel_trials\ \ + 0.5)\n if phase_2_rounds < 1:\n phase_2_rounds = 1\n\n #\ \ All of magic number \"1.3\" above is because the trial doesn't\n #\ \ always finish in time_per_trial. 1.3 is an empirical safety margin here.\n\ \ stage_1_deadline_secs = int(hours * 3600.0 - 1.3 *\n \ \ stage_1_single_run_max_secs * phase_2_rounds)\n\n \ \ if stage_1_deadline_secs < hours * 3600.0 * 0.5:\n stage_1_deadline_secs\ \ = int(hours * 3600.0 * 0.5)\n # Phase 1 deadline is the same as phase\ \ 2 deadline in this case. Phase 2\n # can't finish in time after the\ \ deadline is cut, so adjust the time per\n # trial to meet the deadline.\n\ \ stage_1_single_run_max_secs = int(stage_1_deadline_secs /\n \ \ (1.3 * phase_2_rounds))\n\n reduce_search_space_mode\ \ = 'minimal'\n if multiplier > 2:\n reduce_search_space_mode =\ \ 'regular'\n if multiplier > 4:\n reduce_search_space_mode = 'full'\n\ \n # Stage 2 number of trials is stage_1_num_selected_trials *\n #\ \ num_folds, which should be equal to phase_2_rounds *\n # stage_2_num_parallel_trials.\ \ Use this information to calculate\n # stage_1_num_selected_trials:\n\ \ stage_1_num_selected_trials = int(phase_2_rounds *\n \ \ stage_2_num_parallel_trials / num_folds)\n stage_1_deadline_hours\ \ = stage_1_deadline_secs / 3600.0\n\n stage_2_deadline_hours = hours\ \ - stage_1_deadline_hours\n stage_2_single_run_max_secs = stage_1_single_run_max_secs\n\ \n if run_distillation:\n # All of magic number \"1.3\" above is\ \ because the trial doesn't always\n # finish in time_per_trial. 1.3\ \ is an empirical safety margin here.\n distill_stage_1_deadline_hours\ \ = math.ceil(\n float(distill_total_trials) / stage_1_num_parallel_trials\n\ \ ) * stage_1_single_run_max_secs * 1.3 / 3600.0\n\n if fast_testing:\n\ \ distill_stage_1_deadline_hours = 0.2\n stage_1_deadline_hours =\ \ 0.2\n stage_1_single_run_max_secs = 1\n stage_2_deadline_hours =\ \ 0.2\n stage_2_single_run_max_secs = 1\n\n return collections.namedtuple('Outputs',\ \ [\n 'stage_1_deadline_hours', 'stage_1_num_selected_trials',\n \ \ 'stage_1_single_run_max_secs', 'stage_2_deadline_hours',\n 'stage_2_single_run_max_secs',\ \ 'distill_stage_1_deadline_hours',\n 'reduce_search_space_mode'\n\ \ ])(stage_1_deadline_hours, stage_1_num_selected_trials,\n stage_1_single_run_max_secs,\ \ stage_2_deadline_hours,\n stage_2_single_run_max_secs, distill_stage_1_deadline_hours,\n\ \ reduce_search_space_mode)\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-feature-attribution: container: args: - --task - explanation - --setup_file - /setup.py - --project_id - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --batch_prediction_gcs_source - '{{$.inputs.artifacts[''predictions_gcs_source''].uri}}' - --batch_prediction_format - '{{$.inputs.parameters[''predictions_format'']}}' - --root_dir - '{{$.inputs.parameters[''root_dir'']}}/{{$.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: - --executor_input - '{{$}}' - --function_to_execute - _merge_materialized_splits command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _merge_materialized_splits(\n split_0: dsl.InputPath('MaterializedSplit'),\n\ \ split_1: dsl.InputPath('MaterializedSplit'),\n splits: dsl.OutputPath('MaterializedSplit'),\n\ ):\n \"\"\"Merge two materialized splits.\n\n Args:\n split_0: The\ \ first materialized split.\n split_1: The second materialized split.\n\ \ splits: The merged materialized split.\n \"\"\"\n with open(split_0,\ \ 'r') as f:\n split_0_content = f.read()\n with open(split_1, 'r')\ \ as f:\n split_1_content = f.read()\n with open(splits, 'w') as f:\n\ \ f.write(','.join([split_0_content, split_1_content]))\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-model-batch-explanation: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}", "\"", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - launcher image: gcr.io/ml-pipeline/automl-tables-private:1.0.13 exec-model-batch-explanation-2: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}", "\"", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - launcher image: gcr.io/ml-pipeline/automl-tables-private:1.0.13 exec-model-batch-explanation-3: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}", "\"", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - launcher image: gcr.io/ml-pipeline/automl-tables-private:1.0.13 exec-model-batch-predict: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-model-batch-predict-2: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-model-batch-predict-3: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-model-batch-predict-4: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-model-batch-predict-5: container: args: - --type - BatchPredictionJob - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''job_display_name'']}}", "\", ", " \"input_config\": {", "\"instances_format\": \"", "{{$.inputs.parameters[''instances_format'']}}", "\"", ", \"gcs_source\": {", "\"uris\":", "{{$.inputs.parameters[''gcs_source_uris'']}}", "}", ", \"bigquery_source\": {", "\"input_uri\": \"", "{{$.inputs.parameters[''bigquery_source_input_uri'']}}", "\"", "}", "}", ", \"model_parameters\": ", "{{$.inputs.parameters[''model_parameters'']}}", ", \"output_config\": {", "\"predictions_format\": \"", "{{$.inputs.parameters[''predictions_format'']}}", "\"", ", \"gcs_destination\": {", "\"output_uri_prefix\": \"", "{{$.inputs.parameters[''gcs_destination_output_uri_prefix'']}}", "\"", "}", ", \"bigquery_destination\": {", "\"output_uri\": \"", "{{$.inputs.parameters[''bigquery_destination_output_uri'']}}", "\"", "}", "}", ", \"dedicated_resources\": {", "\"machine_spec\": {", "\"machine_type\": \"", "{{$.inputs.parameters[''machine_type'']}}", "\"", ", \"accelerator_type\": \"", "{{$.inputs.parameters[''accelerator_type'']}}", "\"", ", \"accelerator_count\": ", "{{$.inputs.parameters[''accelerator_count'']}}", "}", ", \"starting_replica_count\": ", "{{$.inputs.parameters[''starting_replica_count'']}}", ", \"max_replica_count\": ", "{{$.inputs.parameters[''max_replica_count'']}}", "}", ", \"manual_batch_tuning_parameters\": {", "\"batch_size\": ", "{{$.inputs.parameters[''manual_batch_tuning_parameters_batch_size'']}}", "}", ", \"generate_explanation\": ", "{{$.inputs.parameters[''generate_explanation'']}}", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.batch_prediction_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-model-evaluation: container: args: - --setup_file - /setup.py - --json_mode - 'true' - --project_id - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --problem_type - '{{$.inputs.parameters[''problem_type'']}}' - --batch_prediction_format - '{{$.inputs.parameters[''predictions_format'']}}' - --batch_prediction_gcs_source - '{{$.inputs.artifacts[''batch_prediction_job''].metadata[''gcsOutputDirectory'']}}' - --ground_truth_format - '{{$.inputs.parameters[''ground_truth_format'']}}' - --key_prefix_in_prediction_dataset - instance - --root_dir - '{{$.inputs.parameters[''root_dir'']}}/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}' - --classification_type - multiclass - --ground_truth_column - instance.{{$.inputs.parameters['ground_truth_column']}} - --prediction_score_column - '{{$.inputs.parameters[''prediction_score_column'']}}' - --prediction_label_column - '{{$.inputs.parameters[''prediction_label_column'']}}' - --prediction_id_column - '' - --example_weight_column - '' - --generate_feature_attribution - 'false' - --dataflow_job_prefix - evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} - --dataflow_service_account - '{{$.inputs.parameters[''dataflow_service_account'']}}' - --dataflow_disk_size - '{{$.inputs.parameters[''dataflow_disk_size'']}}' - --dataflow_machine_type - '{{$.inputs.parameters[''dataflow_machine_type'']}}' - --dataflow_workers_num - '{{$.inputs.parameters[''dataflow_workers_num'']}}' - --dataflow_max_workers_num - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}' - --dataflow_subnetwork - '{{$.inputs.parameters[''dataflow_subnetwork'']}}' - --dataflow_use_public_ips - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}' - --kms_key_name - '{{$.inputs.parameters[''encryption_spec_key_name'']}}' - --output_metrics_gcs_path - '{{$.outputs.artifacts[''evaluation_metrics''].uri}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python - /main.py image: gcr.io/ml-pipeline/model-evaluation:v0.4 exec-model-evaluation-2: container: args: - --setup_file - /setup.py - --json_mode - 'true' - --project_id - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --problem_type - '{{$.inputs.parameters[''problem_type'']}}' - --batch_prediction_format - '{{$.inputs.parameters[''predictions_format'']}}' - --batch_prediction_gcs_source - '{{$.inputs.artifacts[''batch_prediction_job''].metadata[''gcsOutputDirectory'']}}' - --ground_truth_format - '{{$.inputs.parameters[''ground_truth_format'']}}' - --key_prefix_in_prediction_dataset - instance - --root_dir - '{{$.inputs.parameters[''root_dir'']}}/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}' - --classification_type - multiclass - --ground_truth_column - instance.{{$.inputs.parameters['ground_truth_column']}} - --prediction_score_column - '{{$.inputs.parameters[''prediction_score_column'']}}' - --prediction_label_column - '{{$.inputs.parameters[''prediction_label_column'']}}' - --prediction_id_column - '' - --example_weight_column - '' - --generate_feature_attribution - 'false' - --dataflow_job_prefix - evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} - --dataflow_service_account - '{{$.inputs.parameters[''dataflow_service_account'']}}' - --dataflow_disk_size - '{{$.inputs.parameters[''dataflow_disk_size'']}}' - --dataflow_machine_type - '{{$.inputs.parameters[''dataflow_machine_type'']}}' - --dataflow_workers_num - '{{$.inputs.parameters[''dataflow_workers_num'']}}' - --dataflow_max_workers_num - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}' - --dataflow_subnetwork - '{{$.inputs.parameters[''dataflow_subnetwork'']}}' - --dataflow_use_public_ips - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}' - --kms_key_name - '{{$.inputs.parameters[''encryption_spec_key_name'']}}' - --output_metrics_gcs_path - '{{$.outputs.artifacts[''evaluation_metrics''].uri}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python - /main.py image: gcr.io/ml-pipeline/model-evaluation:v0.4 exec-model-evaluation-3: container: args: - --setup_file - /setup.py - --json_mode - 'true' - --project_id - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --problem_type - '{{$.inputs.parameters[''problem_type'']}}' - --batch_prediction_format - '{{$.inputs.parameters[''predictions_format'']}}' - --batch_prediction_gcs_source - '{{$.inputs.artifacts[''batch_prediction_job''].metadata[''gcsOutputDirectory'']}}' - --ground_truth_format - '{{$.inputs.parameters[''ground_truth_format'']}}' - --key_prefix_in_prediction_dataset - instance - --root_dir - '{{$.inputs.parameters[''root_dir'']}}/{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}' - --classification_type - multiclass - --ground_truth_column - instance.{{$.inputs.parameters['ground_truth_column']}} - --prediction_score_column - '{{$.inputs.parameters[''prediction_score_column'']}}' - --prediction_label_column - '{{$.inputs.parameters[''prediction_label_column'']}}' - --prediction_id_column - '' - --example_weight_column - '' - --generate_feature_attribution - 'false' - --dataflow_job_prefix - evaluation-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}} - --dataflow_service_account - '{{$.inputs.parameters[''dataflow_service_account'']}}' - --dataflow_disk_size - '{{$.inputs.parameters[''dataflow_disk_size'']}}' - --dataflow_machine_type - '{{$.inputs.parameters[''dataflow_machine_type'']}}' - --dataflow_workers_num - '{{$.inputs.parameters[''dataflow_workers_num'']}}' - --dataflow_max_workers_num - '{{$.inputs.parameters[''dataflow_max_workers_num'']}}' - --dataflow_subnetwork - '{{$.inputs.parameters[''dataflow_subnetwork'']}}' - --dataflow_use_public_ips - '{{$.inputs.parameters[''dataflow_use_public_ips'']}}' - --kms_key_name - '{{$.inputs.parameters[''encryption_spec_key_name'']}}' - --output_metrics_gcs_path - '{{$.outputs.artifacts[''evaluation_metrics''].uri}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python - /main.py image: gcr.io/ml-pipeline/model-evaluation:v0.4 exec-model-evaluation-import: container: args: - --metrics - '{{$.inputs.artifacts[''metrics''].uri}}' - --metrics_explanation - '{{$.inputs.artifacts[''metrics''].metadata[''explanation_gcs_path'']}}' - '{"IfPresent": {"InputName": "feature_attributions", "Then": {"Concat": ["--feature_attributions", "{{$.inputs.artifacts[''feature_attributions''].uri}}"]}}}' - --problem_type - '{{$.inputs.parameters[''problem_type'']}}' - --display_name - '{{$.inputs.parameters[''display_name'']}}' - '{"IfPresent": {"InputName": "dataset_path", "Then": {"Concat": ["--dataset_path", "{{$.inputs.parameters[''dataset_path'']}}"]}}}' - '{"IfPresent": {"InputName": "dataset_paths", "Then": {"Concat": ["--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'']}}' - '{"IfPresent": {"InputName": "feature_attributions", "Then": {"Concat": ["--feature_attributions", "{{$.inputs.artifacts[''feature_attributions''].uri}}"]}}}' - --problem_type - '{{$.inputs.parameters[''problem_type'']}}' - --display_name - '{{$.inputs.parameters[''display_name'']}}' - '{"IfPresent": {"InputName": "dataset_path", "Then": {"Concat": ["--dataset_path", "{{$.inputs.parameters[''dataset_path'']}}"]}}}' - '{"IfPresent": {"InputName": "dataset_paths", "Then": {"Concat": ["--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'']}}' - '{"IfPresent": {"InputName": "feature_attributions", "Then": {"Concat": ["--feature_attributions", "{{$.inputs.artifacts[''feature_attributions''].uri}}"]}}}' - --problem_type - '{{$.inputs.parameters[''problem_type'']}}' - --display_name - '{{$.inputs.parameters[''display_name'']}}' - '{"IfPresent": {"InputName": "dataset_path", "Then": {"Concat": ["--dataset_path", "{{$.inputs.parameters[''dataset_path'']}}"]}}}' - '{"IfPresent": {"InputName": "dataset_paths", "Then": {"Concat": ["--dataset_paths", "{{$.inputs.parameters[''dataset_paths'']}}"]}}}' - --dataset_type - '{{$.inputs.parameters[''dataset_type'']}}' - --pipeline_job_id - '{{$.pipeline_job_uuid}}' - --pipeline_job_resource_name - '{{$.pipeline_job_resource_name}}' - --model_name - '{{$.inputs.artifacts[''model''].metadata[''resourceName'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.experimental.evaluation.import_model_evaluation image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-model-upload: container: args: - --type - UploadModel - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''display_name'']}}", "\"", ", \"description\": \"", "{{$.inputs.parameters[''description'']}}", "\"", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}", "\"", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - launcher image: gcr.io/ml-pipeline/automl-tables-private:1.0.13 exec-model-upload-2: container: args: - --type - UploadModel - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''display_name'']}}", "\"", ", \"description\": \"", "{{$.inputs.parameters[''description'']}}", "\"", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}", "\"", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - launcher image: gcr.io/ml-pipeline/automl-tables-private:1.0.13 exec-model-upload-3: container: args: - --type - UploadModel - --payload - '{"Concat": ["{", "\"display_name\": \"", "{{$.inputs.parameters[''display_name'']}}", "\"", ", \"description\": \"", "{{$.inputs.parameters[''description'']}}", "\"", ", \"explanation_spec\": {", "\"parameters\": ", "{{$.inputs.parameters[''explanation_parameters'']}}", ", \"metadata\": ", "{{$.inputs.parameters[''explanation_metadata'']}}", "}", ", \"explanation_metadata_artifact\": \"", "{{$.inputs.artifacts[''explanation_metadata_artifact''].uri}}", "\"", ", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}", ", \"labels\": ", "{{$.inputs.parameters[''labels'']}}", "}"]}' - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --executor_input - '{{$}}' command: - python3 - -u - -m - launcher image: gcr.io/ml-pipeline/automl-tables-private:1.0.13 exec-read-input-uri: container: args: - --executor_input - '{{$}}' - --function_to_execute - _read_input_uri command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _read_input_uri(split_uri: dsl.InputPath('Dataset')) -> list:\ \ # Required by KFP; pylint:disable=g-bare-generic\n \"\"\"Construct Dataset\ \ based on the batch prediction job.\n\n Args:\n split_uri: Tbe path\ \ to the file that contains Dataset data.\n\n Returns:\n The list of\ \ string that represents the batch prediction input files.\n \"\"\"\n \ \ # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ import json\n # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ with open(split_uri, 'r') as f:\n data_source = json.loads(f.read())\n\ \ return data_source['tf_record_data_source']['file_patterns']\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-read-input-uri-2: container: args: - --executor_input - '{{$}}' - --function_to_execute - _read_input_uri command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _read_input_uri(split_uri: dsl.InputPath('Dataset')) -> list:\ \ # Required by KFP; pylint:disable=g-bare-generic\n \"\"\"Construct Dataset\ \ based on the batch prediction job.\n\n Args:\n split_uri: Tbe path\ \ to the file that contains Dataset data.\n\n Returns:\n The list of\ \ string that represents the batch prediction input files.\n \"\"\"\n \ \ # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ import json\n # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ with open(split_uri, 'r') as f:\n data_source = json.loads(f.read())\n\ \ return data_source['tf_record_data_source']['file_patterns']\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-set-optional-inputs: container: args: - --executor_input - '{{$}}' - --function_to_execute - _set_optional_inputs command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _set_optional_inputs(\n project: str,\n location: str,\n\ \ data_source_csv_filenames: str,\n data_source_bigquery_table_path:\ \ str,\n vertex_dataset: Input[dsl.Artifact],\n model_display_name:\ \ str,\n) -> NamedTuple('Outputs', [\n ('data_source_csv_filenames',\ \ str),\n ('data_source_bigquery_table_path', str),\n ('model_display_name',\ \ str),\n]):\n \"\"\"Get the data source URI.\n\n Args:\n project:\ \ The GCP project that runs the pipeline components.\n location: The\ \ GCP region that runs the pipeline components.\n data_source_csv_filenames:\ \ The CSV GCS path when data source is CSV.\n data_source_bigquery_table_path:\ \ The BigQuery table when data source is BQ.\n vertex_dataset: The Vertex\ \ dataset when data source is Vertex dataset.\n model_display_name: The\ \ uploaded model's display name.\n\n Returns:\n A named tuple of CSV\ \ or BQ URI.\n \"\"\"\n # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\ \ import collections\n from google.cloud import aiplatform\n from google.cloud\ \ import aiplatform_v1beta1 as aip\n import uuid\n # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name\n\ \n if not model_display_name:\n model_display_name = f'tabular-workflow-model-{uuid.uuid4()}'\n\ \n if vertex_dataset is not None:\n # of format\n # projects/294348452381/locations/us-central1/datasets/7104764862735056896\n\ \ dataset_name = vertex_dataset.metadata['resourceName']\n\n aiplatform.init(project=project,\ \ location=location)\n client = aip.DatasetServiceClient(client_options={\n\ \ 'api_endpoint': f'{location}-aiplatform.googleapis.com'\n })\n\ \ dataset = client.get_dataset(name=dataset_name)\n input_config =\ \ dataset.metadata['inputConfig']\n print(input_config)\n if 'gcsSource'\ \ in input_config:\n data_source_csv_filenames = ','.join(input_config['gcsSource']['uri'])\n\ \ elif 'bigquerySource' in input_config:\n data_source_bigquery_table_path\ \ = input_config['bigquerySource']['uri']\n elif data_source_csv_filenames:\n\ \ pass\n elif data_source_bigquery_table_path:\n pass\n else:\n\ \ raise ValueError(\n 'One of vertex_dataset, data_source_csv_filenames,'\n\ \ ' data_source_bigquery_table_path must be specified'\n )\n\n\ \ return collections.namedtuple(\n 'Outputs',\n [\n \ \ 'data_source_csv_filenames',\n 'data_source_bigquery_table_path',\n\ \ 'model_display_name',\n ],\n )(\n data_source_csv_filenames,\n\ \ data_source_bigquery_table_path,\n model_display_name,\n )\n\ \n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-string-not-empty: container: args: - --executor_input - '{{$}}' - --function_to_execute - _string_not_empty command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _string_not_empty(value: str) -> str:\n \"\"\"Check if the input\ \ string value is not empty.\n\n Args:\n value: String value to be checked.\n\ \n Returns:\n Boolean value. -> 'true' if empty, 'false' if not empty.\ \ We need to use str\n instead of bool due to a limitation in KFP compiler.\n\ \ \"\"\"\n return 'true' if value else 'false'\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-tabular-stats-and-example-gen: container: args: - --type - CustomJob - --project - '{{$.inputs.parameters[''project'']}}' - --location - '{{$.inputs.parameters[''location'']}}' - --gcp_resources - '{{$.outputs.parameters[''gcp_resources''].output_file}}' - --payload - '{"Concat": ["{\"display_name\": \"tabular-stats-and-example-gen-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}\", \"encryption_spec\": {\"kms_key_name\":\"", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\"}, \"job_spec\": {\"worker_pool_specs\": [{\"replica_count\": 1, \"machine_spec\": {\"machine_type\": \"n1-standard-8\"}, \"container_spec\": {\"image_uri\":\"", "us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:dev", "\", \"args\": [\"stats_generator\",", "\"--train_spec={\\\"prediction_type\\\": \\\"", "{{$.inputs.parameters[''prediction_type'']}}", "\\\", \\\"target_column\\\": \\\"", "{{$.inputs.parameters[''target_column_name'']}}", "\\\", \\\"optimization_objective\\\": \\\"", "{{$.inputs.parameters[''optimization_objective'']}}", "\\\", \\\"weight_column_name\\\": \\\"", "{{$.inputs.parameters[''weight_column_name'']}}", "\\\", \\\"transformations\\\": ", "{{$.inputs.parameters[''transformations'']}}", ", \\\"quantiles\\\": ", "{{$.inputs.parameters[''quantiles'']}}", ", \\\"enable_probabilistic_inference\\\": ", "{{$.inputs.parameters[''enable_probabilistic_inference'']}}", "}\", \"--transformations_override_path=", "{{$.inputs.parameters[''transformations_path'']}}", "\", \"--data_source_csv_filenames=", "{{$.inputs.parameters[''data_source_csv_filenames'']}}", "\", \"--data_source_bigquery_table_path=", "{{$.inputs.parameters[''data_source_bigquery_table_path'']}}", "\", \"--predefined_split_key=", "{{$.inputs.parameters[''predefined_split_key'']}}", "\", \"--timestamp_split_key=", "{{$.inputs.parameters[''timestamp_split_key'']}}", "\", \"--stratified_split_key=", "{{$.inputs.parameters[''stratified_split_key'']}}", "\", \"--training_fraction=", "{{$.inputs.parameters[''training_fraction'']}}", "\", \"--validation_fraction=", "{{$.inputs.parameters[''validation_fraction'']}}", "\", \"--test_fraction=", "{{$.inputs.parameters[''test_fraction'']}}", "\", \"--target_column=", "{{$.inputs.parameters[''target_column_name'']}}", "\", \"--request_type=", "{{$.inputs.parameters[''request_type'']}}", "\", \"--optimization_objective_recall_value=", "{{$.inputs.parameters[''optimization_objective_recall_value'']}}", "\", \"--optimization_objective_precision_value=", "{{$.inputs.parameters[''optimization_objective_precision_value'']}}", "\", \"--example_gen_gcs_output_prefix=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/example_gen_output\", \"--dataset_stats_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/stats/\", \"--stats_result_path=", "{{$.outputs.artifacts[''dataset_stats''].uri}}", "\", \"--dataset_schema_path=", "{{$.outputs.artifacts[''dataset_schema''].uri}}", "\", \"--job_name=tabular-stats-and-example-gen-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}", "\", \"--dataflow_project=", "{{$.inputs.parameters[''project'']}}", "\", \"--error_file_path=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/error.pb\", \"--dataflow_staging_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_staging\", \"--dataflow_tmp_dir=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/dataflow_tmp\", \"--dataflow_max_num_workers=", "{{$.inputs.parameters[''dataflow_max_num_workers'']}}", "\", \"--dataflow_worker_container_image=", "us-docker.pkg.dev/vertex-ai/automl-tabular/dataflow-worker:dev", "\", \"--dataflow_machine_type=", "{{$.inputs.parameters[''dataflow_machine_type'']}}", "\", \"--dataflow_disk_size_gb=", "{{$.inputs.parameters[''dataflow_disk_size_gb'']}}", "\", \"--dataflow_kms_key=", "{{$.inputs.parameters[''encryption_spec_key_name'']}}", "\", \"--dataflow_subnetwork_fully_qualified=", "{{$.inputs.parameters[''dataflow_subnetwork'']}}", "\", \"--dataflow_use_public_ips=", "{{$.inputs.parameters[''dataflow_use_public_ips'']}}", "\", \"--dataflow_service_account=", "{{$.inputs.parameters[''dataflow_service_account'']}}", "\", \"--is_distill=", "{{$.inputs.parameters[''run_distillation'']}}", "\", \"--additional_experiments=", "{{$.inputs.parameters[''additional_experiments'']}}", "\", \"--metadata_path=", "{{$.outputs.artifacts[''metadata''].uri}}", "\", \"--train_split=", "{{$.outputs.artifacts[''train_split''].uri}}", "\", \"--eval_split=", "{{$.outputs.artifacts[''eval_split''].uri}}", "\", \"--test_split=", "{{$.outputs.artifacts[''test_split''].uri}}", "\", \"--test_split_for_batch_prediction_component=", "{{$.outputs.parameters[''test_split_json''].output_file}}", "\", \"--downsampled_test_split_for_batch_prediction_component=", "{{$.outputs.parameters[''downsampled_test_split_json''].output_file}}", "\", \"--instance_baseline_path=", "{{$.outputs.artifacts[''instance_baseline''].uri}}", "\", \"--lro_job_info=", "{{$.inputs.parameters[''root_dir'']}}", "/{{$.pipeline_job_uuid}}/lro\", \"--gcp_resources_path=", "{{$.outputs.parameters[''gcp_resources''].output_file}}", "\", \"--parse_json=true\", \"--generate_additional_downsample_test_split=true\", \"--executor_input={{$.json_escape[1]}}\"]}}]}}"]}' command: - python3 - -u - -m - google_cloud_pipeline_components.container.v1.custom_job.launcher image: gcr.io/ml-pipeline/google-cloud-pipeline-components:1.0.32 exec-write-bp-result-path: container: args: - --executor_input - '{{$}}' - --function_to_execute - _write_bp_result_path command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _write_bp_result_path(\n bp_job: Input[Artifact],\n result:\ \ OutputPath('Dataset'),\n):\n \"\"\"Construct Dataset based on the batch\ \ prediction job.\n\n Args:\n bp_job: The batch prediction job artifact.\n\ \ result: Tbe path to the file that contains Dataset data.\n \"\"\"\n\ \ # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ import json\n # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ directory = bp_job.metadata['gcsOutputDirectory']\n data_source = {\n\ \ 'tf_record_data_source': {\n 'file_patterns': [f'{directory}/prediction.results-*',],\n\ \ 'coder': 'PROTO_VALUE',\n },\n }\n with open(result, 'w')\ \ as f:\n f.write(json.dumps(data_source))\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev exec-write-bp-result-path-2: container: args: - --executor_input - '{{$}}' - --function_to_execute - _write_bp_result_path command: - sh - -ec - 'program_path=$(mktemp -d) printf "%s" "$0" > "$program_path/ephemeral_component.py" python3 -m kfp.components.executor_main --component_module_path "$program_path/ephemeral_component.py" "$@" ' - "\nimport kfp\nfrom kfp import dsl\nfrom kfp.dsl import *\nfrom typing import\ \ *\n\ndef _write_bp_result_path(\n bp_job: Input[Artifact],\n result:\ \ OutputPath('Dataset'),\n):\n \"\"\"Construct Dataset based on the batch\ \ prediction job.\n\n Args:\n bp_job: The batch prediction job artifact.\n\ \ result: Tbe path to the file that contains Dataset data.\n \"\"\"\n\ \ # pylint: disable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ import json\n # pylint: enable=g-import-not-at-top,import-outside-toplevel,redefined-outer-name,reimported\n\ \ directory = bp_job.metadata['gcsOutputDirectory']\n data_source = {\n\ \ 'tf_record_data_source': {\n 'file_patterns': [f'{directory}/prediction.results-*',],\n\ \ 'coder': 'PROTO_VALUE',\n },\n }\n with open(result, 'w')\ \ as f:\n f.write(json.dumps(data_source))\n\n" image: us-docker.pkg.dev/vertex-ai/automl-tabular/kfp-v2-base:dev pipelineInfo: name: automl-tabular root: dag: outputs: artifacts: feature-attribution-2-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-2-feature_attributions producerSubtask: exit-handler-1 feature-attribution-3-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-3-feature_attributions producerSubtask: exit-handler-1 feature-attribution-feature_attributions: artifactSelectors: - outputArtifactKey: feature-attribution-feature_attributions producerSubtask: exit-handler-1 model-evaluation-2-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-2-evaluation_metrics producerSubtask: exit-handler-1 model-evaluation-3-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-3-evaluation_metrics producerSubtask: exit-handler-1 model-evaluation-evaluation_metrics: artifactSelectors: - outputArtifactKey: model-evaluation-evaluation_metrics producerSubtask: exit-handler-1 tasks: automl-tabular-finalizer: cachingOptions: enableCache: true componentRef: name: comp-automl-tabular-finalizer dependentTasks: - exit-handler-1 inputs: parameters: location: componentInputParameter: location project: componentInputParameter: project root_dir: componentInputParameter: root_dir taskInfo: name: automl-tabular-finalizer triggerPolicy: strategy: ALL_UPSTREAM_TASKS_COMPLETED exit-handler-1: componentRef: name: comp-exit-handler-1 dependentTasks: - set-optional-inputs inputs: parameters: pipelinechannel--additional_experiments: componentInputParameter: additional_experiments pipelinechannel--cv_trainer_worker_pool_specs_override: componentInputParameter: cv_trainer_worker_pool_specs_override pipelinechannel--dataflow_service_account: componentInputParameter: dataflow_service_account pipelinechannel--dataflow_subnetwork: componentInputParameter: dataflow_subnetwork pipelinechannel--dataflow_use_public_ips: componentInputParameter: dataflow_use_public_ips pipelinechannel--disable_early_stopping: componentInputParameter: disable_early_stopping pipelinechannel--distill_batch_predict_machine_type: componentInputParameter: distill_batch_predict_machine_type pipelinechannel--distill_batch_predict_max_replica_count: componentInputParameter: distill_batch_predict_max_replica_count pipelinechannel--distill_batch_predict_starting_replica_count: componentInputParameter: distill_batch_predict_starting_replica_count pipelinechannel--enable_probabilistic_inference: componentInputParameter: enable_probabilistic_inference pipelinechannel--encryption_spec_key_name: componentInputParameter: encryption_spec_key_name pipelinechannel--evaluation_batch_explain_machine_type: componentInputParameter: evaluation_batch_explain_machine_type pipelinechannel--evaluation_batch_explain_max_replica_count: componentInputParameter: evaluation_batch_explain_max_replica_count pipelinechannel--evaluation_batch_explain_starting_replica_count: componentInputParameter: evaluation_batch_explain_starting_replica_count pipelinechannel--evaluation_batch_predict_machine_type: componentInputParameter: evaluation_batch_predict_machine_type pipelinechannel--evaluation_batch_predict_max_replica_count: componentInputParameter: evaluation_batch_predict_max_replica_count pipelinechannel--evaluation_batch_predict_starting_replica_count: componentInputParameter: evaluation_batch_predict_starting_replica_count pipelinechannel--evaluation_dataflow_disk_size_gb: componentInputParameter: evaluation_dataflow_disk_size_gb pipelinechannel--evaluation_dataflow_machine_type: componentInputParameter: evaluation_dataflow_machine_type pipelinechannel--evaluation_dataflow_max_num_workers: componentInputParameter: evaluation_dataflow_max_num_workers pipelinechannel--evaluation_dataflow_starting_num_workers: componentInputParameter: evaluation_dataflow_starting_num_workers pipelinechannel--export_additional_model_without_custom_ops: componentInputParameter: export_additional_model_without_custom_ops pipelinechannel--fast_testing: componentInputParameter: fast_testing pipelinechannel--location: componentInputParameter: location pipelinechannel--model_description: componentInputParameter: model_description pipelinechannel--optimization_objective: componentInputParameter: optimization_objective pipelinechannel--optimization_objective_precision_value: componentInputParameter: optimization_objective_precision_value pipelinechannel--optimization_objective_recall_value: componentInputParameter: optimization_objective_recall_value pipelinechannel--predefined_split_key: componentInputParameter: predefined_split_key pipelinechannel--prediction_type: componentInputParameter: prediction_type pipelinechannel--project: componentInputParameter: project pipelinechannel--quantiles: componentInputParameter: quantiles pipelinechannel--root_dir: componentInputParameter: root_dir pipelinechannel--run_distillation: componentInputParameter: run_distillation pipelinechannel--run_evaluation: componentInputParameter: run_evaluation pipelinechannel--set-optional-inputs-data_source_bigquery_table_path: taskOutputParameter: outputParameterKey: data_source_bigquery_table_path producerTask: set-optional-inputs pipelinechannel--set-optional-inputs-data_source_csv_filenames: taskOutputParameter: outputParameterKey: data_source_csv_filenames producerTask: set-optional-inputs pipelinechannel--set-optional-inputs-model_display_name: taskOutputParameter: outputParameterKey: model_display_name producerTask: set-optional-inputs pipelinechannel--stage_1_num_parallel_trials: componentInputParameter: stage_1_num_parallel_trials pipelinechannel--stage_1_tuner_worker_pool_specs_override: componentInputParameter: stage_1_tuner_worker_pool_specs_override pipelinechannel--stage_1_tuning_result_artifact_uri: componentInputParameter: stage_1_tuning_result_artifact_uri pipelinechannel--stage_2_num_parallel_trials: componentInputParameter: stage_2_num_parallel_trials pipelinechannel--stage_2_num_selected_trials: componentInputParameter: stage_2_num_selected_trials pipelinechannel--stats_and_example_gen_dataflow_disk_size_gb: componentInputParameter: stats_and_example_gen_dataflow_disk_size_gb pipelinechannel--stats_and_example_gen_dataflow_machine_type: componentInputParameter: stats_and_example_gen_dataflow_machine_type pipelinechannel--stats_and_example_gen_dataflow_max_num_workers: componentInputParameter: stats_and_example_gen_dataflow_max_num_workers pipelinechannel--stratified_split_key: componentInputParameter: stratified_split_key pipelinechannel--study_spec_parameters_override: componentInputParameter: study_spec_parameters_override pipelinechannel--target_column: componentInputParameter: target_column pipelinechannel--test_fraction: componentInputParameter: test_fraction pipelinechannel--timestamp_split_key: componentInputParameter: timestamp_split_key pipelinechannel--train_budget_milli_node_hours: componentInputParameter: train_budget_milli_node_hours pipelinechannel--training_fraction: componentInputParameter: training_fraction pipelinechannel--transform_dataflow_disk_size_gb: componentInputParameter: transform_dataflow_disk_size_gb pipelinechannel--transform_dataflow_machine_type: componentInputParameter: transform_dataflow_machine_type pipelinechannel--transform_dataflow_max_num_workers: componentInputParameter: transform_dataflow_max_num_workers pipelinechannel--transformations: componentInputParameter: transformations pipelinechannel--validation_fraction: componentInputParameter: validation_fraction pipelinechannel--weight_column: componentInputParameter: weight_column taskInfo: name: exit-handler-1 set-optional-inputs: cachingOptions: enableCache: true componentRef: name: comp-set-optional-inputs inputs: artifacts: vertex_dataset: componentInputArtifact: vertex_dataset parameters: data_source_bigquery_table_path: componentInputParameter: data_source_bigquery_table_path data_source_csv_filenames: componentInputParameter: data_source_csv_filenames location: componentInputParameter: location model_display_name: componentInputParameter: model_display_name project: componentInputParameter: project taskInfo: name: set-optional-inputs inputDefinitions: artifacts: vertex_dataset: artifactType: schemaTitle: system.Artifact schemaVersion: 0.0.1 parameters: additional_experiments: isOptional: true parameterType: STRUCT cv_trainer_worker_pool_specs_override: isOptional: true parameterType: LIST data_source_bigquery_table_path: defaultValue: '' isOptional: true parameterType: STRING data_source_csv_filenames: defaultValue: '' isOptional: true parameterType: STRING dataflow_service_account: defaultValue: '' isOptional: true parameterType: STRING dataflow_subnetwork: defaultValue: '' isOptional: true parameterType: STRING dataflow_use_public_ips: defaultValue: true isOptional: true parameterType: BOOLEAN disable_early_stopping: defaultValue: false isOptional: true parameterType: BOOLEAN distill_batch_predict_machine_type: defaultValue: n1-standard-16 isOptional: true parameterType: STRING distill_batch_predict_max_replica_count: defaultValue: 25.0 isOptional: true parameterType: NUMBER_INTEGER distill_batch_predict_starting_replica_count: defaultValue: 25.0 isOptional: true parameterType: NUMBER_INTEGER enable_probabilistic_inference: defaultValue: false isOptional: true parameterType: BOOLEAN encryption_spec_key_name: defaultValue: '' isOptional: true parameterType: STRING evaluation_batch_explain_machine_type: defaultValue: n1-highmem-8 isOptional: true parameterType: STRING evaluation_batch_explain_max_replica_count: defaultValue: 10.0 isOptional: true parameterType: NUMBER_INTEGER evaluation_batch_explain_starting_replica_count: defaultValue: 10.0 isOptional: true parameterType: NUMBER_INTEGER evaluation_batch_predict_machine_type: defaultValue: n1-highmem-8 isOptional: true parameterType: STRING evaluation_batch_predict_max_replica_count: defaultValue: 20.0 isOptional: true parameterType: NUMBER_INTEGER evaluation_batch_predict_starting_replica_count: defaultValue: 20.0 isOptional: true parameterType: NUMBER_INTEGER evaluation_dataflow_disk_size_gb: defaultValue: 50.0 isOptional: true parameterType: NUMBER_INTEGER evaluation_dataflow_machine_type: defaultValue: n1-standard-4 isOptional: true parameterType: STRING evaluation_dataflow_max_num_workers: defaultValue: 100.0 isOptional: true parameterType: NUMBER_INTEGER evaluation_dataflow_starting_num_workers: defaultValue: 10.0 isOptional: true parameterType: NUMBER_INTEGER export_additional_model_without_custom_ops: defaultValue: false isOptional: true parameterType: BOOLEAN fast_testing: defaultValue: false isOptional: true parameterType: BOOLEAN location: parameterType: STRING model_description: defaultValue: '' isOptional: true parameterType: STRING model_display_name: defaultValue: '' isOptional: true parameterType: STRING optimization_objective: parameterType: STRING optimization_objective_precision_value: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE optimization_objective_recall_value: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE predefined_split_key: defaultValue: '' isOptional: true parameterType: STRING prediction_type: parameterType: STRING project: parameterType: STRING quantiles: isOptional: true parameterType: LIST root_dir: parameterType: STRING run_distillation: defaultValue: false isOptional: true parameterType: BOOLEAN run_evaluation: defaultValue: false isOptional: true parameterType: BOOLEAN stage_1_num_parallel_trials: defaultValue: 35.0 isOptional: true parameterType: NUMBER_INTEGER stage_1_tuner_worker_pool_specs_override: isOptional: true parameterType: LIST stage_1_tuning_result_artifact_uri: defaultValue: '' isOptional: true parameterType: STRING stage_2_num_parallel_trials: defaultValue: 35.0 isOptional: true parameterType: NUMBER_INTEGER stage_2_num_selected_trials: defaultValue: 5.0 isOptional: true parameterType: NUMBER_INTEGER stats_and_example_gen_dataflow_disk_size_gb: defaultValue: 40.0 isOptional: true parameterType: NUMBER_INTEGER stats_and_example_gen_dataflow_machine_type: defaultValue: n1-standard-16 isOptional: true parameterType: STRING stats_and_example_gen_dataflow_max_num_workers: defaultValue: 25.0 isOptional: true parameterType: NUMBER_INTEGER stratified_split_key: defaultValue: '' isOptional: true parameterType: STRING study_spec_parameters_override: isOptional: true parameterType: LIST target_column: parameterType: STRING test_fraction: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE timestamp_split_key: defaultValue: '' isOptional: true parameterType: STRING train_budget_milli_node_hours: parameterType: NUMBER_DOUBLE training_fraction: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE transform_dataflow_disk_size_gb: defaultValue: 40.0 isOptional: true parameterType: NUMBER_INTEGER transform_dataflow_machine_type: defaultValue: n1-standard-16 isOptional: true parameterType: STRING transform_dataflow_max_num_workers: defaultValue: 25.0 isOptional: true parameterType: NUMBER_INTEGER transformations: parameterType: STRING validation_fraction: defaultValue: -1.0 isOptional: true parameterType: NUMBER_DOUBLE weight_column: defaultValue: '' isOptional: true parameterType: STRING outputDefinitions: artifacts: feature-attribution-2-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 feature-attribution-3-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 feature-attribution-feature_attributions: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-2-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-3-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 model-evaluation-evaluation_metrics: artifactType: schemaTitle: system.Metrics schemaVersion: 0.0.1 schemaVersion: 2.1.0 sdkVersion: kfp-2.0.0-beta.13

python/pipelines/automl_tabular_pl_v2.yaml (8,127 lines of code) (raw):