def __init__(self,
explained_model,
model_builder,
masking_operation,
loss,
downsample_factors=(1, ),
num_models=1):
super(CXPlain, self).__init__()
self.explained_model = explained_model
self.model_builder = model_builder
self.masking_operation = masking_operation
self.loss = loss
self.last_masked_data = None
self.prediction_model = None
Validation.check_is_positive_integer_greaterequals_1(
num_models, var_name="num_models")
self.num_models = num_models
Validation.check_downsample_factors_at_initialisation(
downsample_factors)
self.downsample_factors = downsample_factors
def __init__(self,
callbacks=list([]),
early_stopping_patience=12,
batch_size=64,
num_epochs=100,
validation_fraction=0.1,
shuffle=True,
learning_rate=0.0001,
optimizer=None,
verbose=0):
self.batch_size = batch_size
Validation.check_is_positive_integer_greaterequals_1(
num_epochs, var_name="num_epochs")
self.num_epochs = num_epochs
Validation.check_is_fraction(validation_fraction,
var_name="validation_fraction")
self.validation_fraction = validation_fraction
self.shuffle = shuffle
self.learning_rate = learning_rate
self.optimizer = optimizer
self.verbose = verbose
self.callbacks = callbacks
self.early_stopping_patience = early_stopping_patience
def test_check_is_positive_integer_greaterequals_1(self):
with self.assertRaises(ValueError):
Validation.check_is_positive_integer_greaterequals_1(-1)
with self.assertRaises(ValueError):
Validation.check_is_positive_integer_greaterequals_1(1.1)
with self.assertRaises(ValueError):
Validation.check_is_positive_integer_greaterequals_1(-1.1)
with self.assertRaises(ValueError):
Validation.check_is_positive_integer_greaterequals_1(0)
Validation.check_is_positive_integer_greaterequals_1(1)
Validation.check_is_positive_integer_greaterequals_1(2)