def test_init_all_parameters_extraction(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_EXTRACTION,
)
assert job._display_name == _TEST_DISPLAY_NAME
assert (job._training_task_definition ==
schema.training_job.definition.automl_text_extraction)
assert (job._training_task_inputs_dict ==
training_job_inputs.AutoMlTextExtractionInputs())
_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}"
)