Suite.run#

Suite.run(train_dataset: Optional[VisionData] = None, test_dataset: Optional[VisionData] = None, random_state: int = 42, with_display: bool = True, max_samples: Optional[int] = None, run_single_dataset: Optional[str] = None) SuiteResult[source]#

Run all checks.

Parameters
train_datasetOptional[VisionData] , default: None

VisionData object, representing data the model was fitted on

test_datasetOptional[VisionData] , default: None

VisionData object, representing data the models predicts on

random_stateint

A seed to set for pseudo-random functions

with_displaybool , default: True

flag that determines if checks will calculate display (redundant in some checks).

max_samplesOptional[int] , default: None

Each check will run on a number of samples which is the minimum between the n_samples parameter of the check and this parameter. If this argument is None then the number of samples for each check will be determined by the n_samples argument.

run_single_dataset: Optional[str], default None

‘Train’, ‘Test’ , or None to run on both train and test.

Returns
SuiteResult

All results by all initialized checks