def execute(self, context: "Context"): self.hook = AutoMLHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) model = self.hook.create_auto_ml_video_training_job( project_id=self.project_id, region=self.region, display_name=self.display_name, dataset=datasets.VideoDataset(dataset_name=self.dataset_id), prediction_type=self.prediction_type, model_type=self.model_type, labels=self.labels, training_encryption_spec_key_name=self.training_encryption_spec_key_name, model_encryption_spec_key_name=self.model_encryption_spec_key_name, training_fraction_split=self.training_fraction_split, test_fraction_split=self.test_fraction_split, training_filter_split=self.training_filter_split, test_filter_split=self.test_filter_split, model_display_name=self.model_display_name, model_labels=self.model_labels, sync=self.sync, ) result = Model.to_dict(model) model_id = self.hook.extract_model_id(result) VertexAIModelLink.persist(context=context, task_instance=self, model_id=model_id) return result
def execute(self, context: "Context"): self.hook = AutoMLHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) model = self.hook.create_auto_ml_image_training_job( project_id=self.project_id, region=self.region, display_name=self.display_name, dataset=datasets.ImageDataset(dataset_name=self.dataset_id), prediction_type=self.prediction_type, multi_label=self.multi_label, model_type=self.model_type, base_model=self.base_model, labels=self.labels, training_encryption_spec_key_name=self.training_encryption_spec_key_name, model_encryption_spec_key_name=self.model_encryption_spec_key_name, training_fraction_split=self.training_fraction_split, validation_fraction_split=self.validation_fraction_split, test_fraction_split=self.test_fraction_split, training_filter_split=self.training_filter_split, validation_filter_split=self.validation_filter_split, test_filter_split=self.test_filter_split, budget_milli_node_hours=self.budget_milli_node_hours, model_display_name=self.model_display_name, model_labels=self.model_labels, disable_early_stopping=self.disable_early_stopping, sync=self.sync, ) result = Model.to_dict(model) model_id = self.hook.extract_model_id(result) VertexAIModelLink.persist(context=context, task_instance=self, model_id=model_id) return result
def execute(self, context: "Context"): self.hook = AutoMLHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) model = self.hook.create_auto_ml_forecasting_training_job( project_id=self.project_id, region=self.region, display_name=self.display_name, dataset=datasets.TimeSeriesDataset(dataset_name=self.dataset_id), target_column=self.target_column, time_column=self.time_column, time_series_identifier_column=self.time_series_identifier_column, unavailable_at_forecast_columns=self. unavailable_at_forecast_columns, available_at_forecast_columns=self.available_at_forecast_columns, forecast_horizon=self.forecast_horizon, data_granularity_unit=self.data_granularity_unit, data_granularity_count=self.data_granularity_count, optimization_objective=self.optimization_objective, column_specs=self.column_specs, column_transformations=self.column_transformations, labels=self.labels, training_encryption_spec_key_name=self. training_encryption_spec_key_name, model_encryption_spec_key_name=self.model_encryption_spec_key_name, training_fraction_split=self.training_fraction_split, validation_fraction_split=self.validation_fraction_split, test_fraction_split=self.test_fraction_split, predefined_split_column_name=self.predefined_split_column_name, weight_column=self.weight_column, time_series_attribute_columns=self.time_series_attribute_columns, context_window=self.context_window, export_evaluated_data_items=self.export_evaluated_data_items, export_evaluated_data_items_bigquery_destination_uri=( self.export_evaluated_data_items_bigquery_destination_uri), export_evaluated_data_items_override_destination=( self.export_evaluated_data_items_override_destination), quantiles=self.quantiles, validation_options=self.validation_options, budget_milli_node_hours=self.budget_milli_node_hours, model_display_name=self.model_display_name, model_labels=self.model_labels, sync=self.sync, ) result = Model.to_dict(model) model_id = self.hook.extract_model_id(result) VertexAIModelLink.persist(context=context, task_instance=self, model_id=model_id) return result
def execute(self, context: "Context"): self.hook = AutoMLHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) model = self.hook.create_auto_ml_tabular_training_job( project_id=self.project_id, region=self.region, display_name=self.display_name, dataset=datasets.TabularDataset(dataset_name=self.dataset_id), target_column=self.target_column, optimization_prediction_type=self.optimization_prediction_type, optimization_objective=self.optimization_objective, column_specs=self.column_specs, column_transformations=self.column_transformations, optimization_objective_recall_value=self. optimization_objective_recall_value, optimization_objective_precision_value=self. optimization_objective_precision_value, labels=self.labels, training_encryption_spec_key_name=self. training_encryption_spec_key_name, model_encryption_spec_key_name=self.model_encryption_spec_key_name, training_fraction_split=self.training_fraction_split, validation_fraction_split=self.validation_fraction_split, test_fraction_split=self.test_fraction_split, predefined_split_column_name=self.predefined_split_column_name, timestamp_split_column_name=self.timestamp_split_column_name, weight_column=self.weight_column, budget_milli_node_hours=self.budget_milli_node_hours, model_display_name=self.model_display_name, model_labels=self.model_labels, disable_early_stopping=self.disable_early_stopping, export_evaluated_data_items=self.export_evaluated_data_items, export_evaluated_data_items_bigquery_destination_uri=( self.export_evaluated_data_items_bigquery_destination_uri), export_evaluated_data_items_override_destination=( self.export_evaluated_data_items_override_destination), sync=self.sync, ) result = Model.to_dict(model) model_id = self.hook.extract_model_id(result) VertexAIModelLink.persist(context=context, task_instance=self, model_id=model_id) return result