def test_compose():
batch_size = 3
pipe = Pipeline(batch_size, 1, None)
u = ops.random.Uniform()(range=(1, 2), shape=3)
c1 = ops.Compose([
ops.transforms.Translation(offset=u),
ops.transforms.Scale(scale=[1, 1,-1])
])
c2 = ops.Compose([
c1,
ops.transforms.Rotation(angle=90, axis=[0, 0, 1])
])
pipe.set_outputs(c2(fn.transforms.scale(scale=[2, 2, 2])), u)
pipe.build()
matrices, offsets = pipe.run()
assert len(matrices) == batch_size
for i in range(len(matrices)):
offset = offsets.at(i)
matrix = matrices.at(i)
assert offset.shape == (3,)
for j in range(3):
assert offset[j] >= 1 and offset[j] < 2 # check that it's not all zeros or sth
mtx = np.float32([[0, -1, 0],
[1, 0, 0],
[0, 0, -1]])
T = offset[:,np.newaxis] # convert to a columnn
T = np.dot(mtx, T)
mtx *= 2
assert np.allclose(matrix, np.concatenate([mtx, T], axis=1), rtol=1e-5, atol=1e-6)
def test_compose_change_device():
batch_size = 3
pipe = Pipeline(batch_size, 1, 0)
size = fn.random.uniform(shape=2, range=(300,500))
c = ops.Compose([
ops.decoders.Image(device="cpu"),
ops.Resize(size=size, device="gpu")
])
files, labels = fn.readers.caffe(path=caffe_db_folder, seed=1)
pipe.set_outputs(c(files), fn.resize(fn.decoders.image(files).gpu(), size=size))
pipe.build()
out = pipe.run()
assert isinstance(out[0], dali.backend.TensorListGPU)
test_utils.check_batch(out[0], out[1], batch_size=batch_size)
