wehub-resource-sync
36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
import numpy as np
|
|
|
|
from keras.src import testing
|
|
from keras.src.datasets import cifar100
|
|
|
|
|
|
class Cifar100LoadDataTest(testing.TestCase):
|
|
def test_shapes_fine_label_mode(self):
|
|
(x_train, y_train), (x_test, y_test) = cifar100.load_data(
|
|
label_mode="fine"
|
|
)
|
|
self.assertEqual(x_train.shape, (50000, 32, 32, 3))
|
|
self.assertEqual(y_train.shape, (50000, 1))
|
|
self.assertEqual(x_test.shape, (10000, 32, 32, 3))
|
|
self.assertEqual(y_test.shape, (10000, 1))
|
|
|
|
def test_shapes_coarse_label_mode(self):
|
|
(x_train, y_train), (x_test, y_test) = cifar100.load_data(
|
|
label_mode="coarse"
|
|
)
|
|
self.assertEqual(x_train.shape, (50000, 32, 32, 3))
|
|
self.assertEqual(y_train.shape, (50000, 1))
|
|
self.assertEqual(x_test.shape, (10000, 32, 32, 3))
|
|
self.assertEqual(y_test.shape, (10000, 1))
|
|
|
|
def test_dtypes(self):
|
|
(x_train, y_train), (x_test, y_test) = cifar100.load_data()
|
|
self.assertEqual(x_train.dtype, np.uint8)
|
|
self.assertEqual(y_train.dtype, np.int64)
|
|
self.assertEqual(x_test.dtype, np.uint8)
|
|
self.assertEqual(y_test.dtype, np.int64)
|
|
|
|
def test_invalid_label_mode(self):
|
|
with self.assertRaises(ValueError):
|
|
cifar100.load_data(label_mode="invalid")
|