def test_init_all_parameters_classification(self): """Ensure all private members are set correctly at initialization""" aiplatform.init(project=_TEST_PROJECT) job = training_jobs.AutoMLTextTrainingJob( display_name=_TEST_DISPLAY_NAME, prediction_type=_TEST_PREDICTION_TYPE_CLASSIFICATION, multi_label=_TEST_CLASSIFICATION_MULTILABEL, ) assert job._display_name == _TEST_DISPLAY_NAME assert (job._training_task_definition == schema.training_job.definition.automl_text_classification) assert (job._training_task_inputs_dict == training_job_inputs.AutoMlTextClassificationInputs( multi_label=_TEST_CLASSIFICATION_MULTILABEL))
_TEST_PREDICTION_TYPE_CLASSIFICATION = "classification" _TEST_CLASSIFICATION_MULTILABEL = True _TEST_PREDICTION_TYPE_EXTRACTION = "extraction" _TEST_PREDICTION_TYPE_SENTIMENT = "sentiment" _TEST_SENTIMENT_MAX = 10 _TEST_DATASET_NAME = "test-dataset-name" _TEST_MODEL_DISPLAY_NAME = "model-display-name" _TEST_LABELS = {"key": "value"} _TEST_MODEL_LABELS = {"model_key": "model_value"} _TEST_MODEL_ID = "98777645321" _TEST_TRAINING_TASK_INPUTS_CLASSIFICATION = ( training_job_inputs.AutoMlTextClassificationInputs( multi_label=_TEST_CLASSIFICATION_MULTILABEL)) _TEST_TRAINING_TASK_INPUTS_EXTRACTION = training_job_inputs.AutoMlTextExtractionInputs( ) _TEST_TRAINING_TASK_INPUTS_SENTIMENT = training_job_inputs.AutoMlTextSentimentInputs( sentiment_max=_TEST_SENTIMENT_MAX) _TEST_FRACTION_SPLIT_TRAINING = 0.6 _TEST_FRACTION_SPLIT_VALIDATION = 0.2 _TEST_FRACTION_SPLIT_TEST = 0.2 _TEST_FILTER_SPLIT_TRAINING = "train" _TEST_FILTER_SPLIT_VALIDATION = "validate" _TEST_FILTER_SPLIT_TEST = "test" _TEST_PREDEFINED_SPLIT_COLUMN_NAME = "predefined_column" _TEST_MODEL_NAME = ( f"projects/{_TEST_PROJECT}/locations/{_TEST_LOCATION}/models/{_TEST_MODEL_ID}"
_TEST_DATASET_DISPLAY_NAME = "test-dataset-display-name" _TEST_DATASET_NAME = "test-dataset-name" _TEST_DISPLAY_NAME = "test-display-name" _TEST_METADATA_SCHEMA_URI_TEXT = schema.dataset.metadata.text _TEST_PREDICTION_TYPE_CLASSIFICATION = "classification" _TEST_CLASSIFICATION_MULTILABEL = True _TEST_PREDICTION_TYPE_EXTRACTION = "extraction" _TEST_PREDICTION_TYPE_SENTIMENT = "sentiment" _TEST_SENTIMENT_MAX = 10 _TEST_DATASET_NAME = "test-dataset-name" _TEST_MODEL_DISPLAY_NAME = "model-display-name" _TEST_MODEL_ID = "98777645321" _TEST_TRAINING_TASK_INPUTS_CLASSIFICATION = training_job_inputs.AutoMlTextClassificationInputs( multi_label=_TEST_CLASSIFICATION_MULTILABEL) _TEST_TRAINING_TASK_INPUTS_EXTRACTION = training_job_inputs.AutoMlTextExtractionInputs( ) _TEST_TRAINING_TASK_INPUTS_SENTIMENT = training_job_inputs.AutoMlTextSentimentInputs( sentiment_max=_TEST_SENTIMENT_MAX) _TEST_FRACTION_SPLIT_TRAINING = 0.6 _TEST_FRACTION_SPLIT_VALIDATION = 0.2 _TEST_FRACTION_SPLIT_TEST = 0.2 _TEST_MODEL_NAME = ( f"projects/{_TEST_PROJECT}/locations/{_TEST_LOCATION}/models/{_TEST_MODEL_ID}" ) _TEST_PIPELINE_RESOURCE_NAME = ( f"projects/{_TEST_PROJECT}/locations/{_TEST_LOCATION}/trainingPipeline/12345"