def test_pre_train_negative_batch(self):
layer_sizes = [5, 20, 10]
d = DBN(layer_sizes, 10)
data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]]
with self.assertRaises(ValueError):
d.pre_train(data, 1, -1)
def test_pre_train_wrong_data_size(self):
layer_sizes = [5, 20]
d = DBN(layer_sizes, 10)
data = [[1, 1, 1, 1, 1, 1, 1]]
with self.assertRaises(ValueError):
d.pre_train(data, 1, 1)
def test_pre_train_correct_data_size(self):
layer_sizes = [5, 20, 10]
d = DBN(layer_sizes, 10)
data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]]
d.pre_train(data, 1, 1)
def test_pre_train_negative_batch(self):
layer_sizes = [5, 20, 10]
d = DBN(layer_sizes, 10)
data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]]
with self.assertRaises(ValueError):
d.pre_train(data, 1, -1)
def test_pre_train_wrong_data_size(self):
layer_sizes = [5, 20]
d = DBN(layer_sizes, 10)
data = [[1, 1, 1, 1, 1, 1, 1]]
with self.assertRaises(ValueError):
d.pre_train(data, 1, 1)
def test_pre_train_correct_data_size(self):
layer_sizes = [5, 20, 10]
d = DBN(layer_sizes, 10)
data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]]
d.pre_train(data, 1, 1)
