def test_random_transforms():
from mxnet.gluon.data.vision import transforms
tmp_t = transforms.Compose([transforms.Resize(300), transforms.RandomResizedCrop(224)])
transform = transforms.Compose([transforms.RandomApply(tmp_t, 0.5)])
img = mx.nd.ones((10, 10, 3), dtype='uint8')
iteration = 1000
num_apply = 0
for _ in range(iteration):
out = transform(img)
if out.shape[0] == 224:
num_apply += 1
assert_almost_equal(num_apply/float(iteration), 0.5, 0.1)
def test_random_transforms():
from mxnet.gluon.data.vision import transforms
counter = 0
def transform_fn(x):
nonlocal counter
counter += 1
return x
transform = transforms.Compose([transforms.RandomApply(transform_fn, 0.5)])
img = mx.np.ones((10, 10, 3), dtype='uint8')
iteration = 10000
num_apply = 0
for _ in range(iteration):
out = transform(img)
assert counter == pytest.approx(5000, 1e-1)