airflow.providers.google.cloud.operators.vertex_ai.auto_ml

This module contains Google Vertex AI operators.

Module Contents

Classes

AutoMLTrainingJobBaseOperator

The base class for operators that launch AutoML jobs on VertexAI.

CreateAutoMLForecastingTrainingJobOperator

Create AutoML Forecasting Training job.

CreateAutoMLImageTrainingJobOperator

Create Auto ML Image Training job.

CreateAutoMLTabularTrainingJobOperator

Create Auto ML Tabular Training job.

CreateAutoMLTextTrainingJobOperator

Create Auto ML Text Training job.

CreateAutoMLVideoTrainingJobOperator

Create Auto ML Video Training job.

DeleteAutoMLTrainingJobOperator

Delete an AutoML training job.

ListAutoMLTrainingJobOperator

List an AutoML training job.
class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.AutoMLTrainingJobBaseOperator(*, project_id, region, display_name, labels=None, parent_model=None, is_default_version=None, model_version_aliases=None, model_version_description=None, training_encryption_spec_key_name=None, model_encryption_spec_key_name=None, training_fraction_split=None, test_fraction_split=None, model_display_name=None, model_labels=None, sync=True, gcp_conn_id='google_cloud_default', impersonation_chain=None, **kwargs)[source]

Bases: airflow.providers.google.cloud.operators.cloud_base.GoogleCloudBaseOperator

The base class for operators that launch AutoML jobs on VertexAI.

on_kill()[source]

Act as a callback called when the operator is killed; cancel any running job.

class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLForecastingTrainingJobOperator(*, dataset_id, target_column, time_column, time_series_identifier_column, unavailable_at_forecast_columns, available_at_forecast_columns, forecast_horizon, data_granularity_unit, data_granularity_count, optimization_objective=None, column_specs=None, column_transformations=None, validation_fraction_split=None, predefined_split_column_name=None, weight_column=None, time_series_attribute_columns=None, context_window=None, export_evaluated_data_items=False, export_evaluated_data_items_bigquery_destination_uri=None, export_evaluated_data_items_override_destination=False, quantiles=None, validation_options=None, budget_milli_node_hours=1000, region, impersonation_chain=None, parent_model=None, **kwargs)[source]

Bases: AutoMLTrainingJobBaseOperator

Create AutoML Forecasting Training job.

template_fields = ('parent_model', 'dataset_id', 'region', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLImageTrainingJobOperator(*, dataset_id, prediction_type='classification', multi_label=False, model_type='CLOUD', base_model=None, validation_fraction_split=None, training_filter_split=None, validation_filter_split=None, test_filter_split=None, budget_milli_node_hours=None, disable_early_stopping=False, region, impersonation_chain=None, parent_model=None, **kwargs)[source]

Bases: AutoMLTrainingJobBaseOperator

Create Auto ML Image Training job.

template_fields = ('parent_model', 'dataset_id', 'region', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTabularTrainingJobOperator(*, dataset_id, target_column, optimization_prediction_type, optimization_objective=None, column_specs=None, column_transformations=None, optimization_objective_recall_value=None, optimization_objective_precision_value=None, validation_fraction_split=None, predefined_split_column_name=None, timestamp_split_column_name=None, weight_column=None, budget_milli_node_hours=1000, disable_early_stopping=False, export_evaluated_data_items=False, export_evaluated_data_items_bigquery_destination_uri=None, export_evaluated_data_items_override_destination=False, region, impersonation_chain=None, parent_model=None, **kwargs)[source]

Bases: AutoMLTrainingJobBaseOperator

Create Auto ML Tabular Training job.

template_fields = ('parent_model', 'dataset_id', 'region', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTextTrainingJobOperator(*, dataset_id, prediction_type, multi_label=False, sentiment_max=10, validation_fraction_split=None, training_filter_split=None, validation_filter_split=None, test_filter_split=None, **kwargs)[source]

Bases: AutoMLTrainingJobBaseOperator

Create Auto ML Text Training job.

template_fields = ['parent_model', 'dataset_id', 'region', 'impersonation_chain'][source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLVideoTrainingJobOperator(*, dataset_id, prediction_type='classification', model_type='CLOUD', training_filter_split=None, test_filter_split=None, region, impersonation_chain=None, parent_model=None, **kwargs)[source]

Bases: AutoMLTrainingJobBaseOperator

Create Auto ML Video Training job.

template_fields = ('parent_model', 'dataset_id', 'region', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.DeleteAutoMLTrainingJobOperator(*, training_pipeline_id, region, project_id, retry=DEFAULT, timeout=None, metadata=(), gcp_conn_id='google_cloud_default', impersonation_chain=None, **kwargs)[source]

Bases: airflow.providers.google.cloud.operators.cloud_base.GoogleCloudBaseOperator

Delete an AutoML training job.

Can be used with AutoMLForecastingTrainingJob, AutoMLImageTrainingJob, AutoMLTabularTrainingJob, AutoMLTextTrainingJob, or AutoMLVideoTrainingJob.

property training_pipeline[source]

Alias for training_pipeline_id, used for compatibility (deprecated).

template_fields = ('training_pipeline_id', 'region', 'project_id', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

class airflow.providers.google.cloud.operators.vertex_ai.auto_ml.ListAutoMLTrainingJobOperator(*, region, project_id, page_size=None, page_token=None, filter=None, read_mask=None, retry=DEFAULT, timeout=None, metadata=(), gcp_conn_id='google_cloud_default', impersonation_chain=None, **kwargs)[source]

Bases: airflow.providers.google.cloud.operators.cloud_base.GoogleCloudBaseOperator

List an AutoML training job.

Can be used with AutoMLForecastingTrainingJob, AutoMLImageTrainingJob, AutoMLTabularTrainingJob, AutoMLTextTrainingJob, or AutoMLVideoTrainingJob in a Location.

template_fields = ('region', 'project_id', 'impersonation_chain')[source]
execute(context)[source]

Derive when creating an operator.

Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

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