def test_Mixup():
numbers1 = [1, 2, 3]
numbers2 = [4, 5, 6]
samples = list(zip(numbers1, numbers2))
build_batch = (nb.BuildBatch(3, prefetch=0).input(0, 'number',
float).output(
1, 'number', float))
# no mixup, return original batch
mixup = nb.Mixup(0.0)
batches = samples >> build_batch >> mixup >> Collect()
inputs, outputs = batches[0]
assert list(inputs[0]) == numbers1
assert list(outputs[0]) == numbers2
# mixup with alpaha=1.0
mixup = nb.Mixup(1.0)
batches = samples >> build_batch >> mixup >> Collect()
for input, output in batches:
input, output = input[0], output[0]
assert min(input) >= 1 and max(input) <= 3
assert min(output) >= 4 and max(output) <= 6
ri, ro = input[0] - samples[0][0], output[0] - samples[0][1]
assert approx(ri, 1e-3) == ro
def test_BuildBatch_verbose():
with Redirect() as out:
samples = [[1], [2], [3]]
build_batch = (nb.BuildBatch(2,
verbose=True).input(0, 'number', 'uint8'))
samples >> build_batch >> Consume()
assert out.getvalue() == '[2:uint8]\n[1:uint8]\n'
with Redirect() as out:
samples = [(np.array([1, 2, 3]), 0), (np.array([4, 5, 6]), 1),
(np.array([7, 8, 9]), 1)]
build_batch = (nb.BuildBatch(2, verbose=True).input(
0, 'vector', 'float32').output(1, 'one_hot', 'uint8', 2))
samples >> build_batch >> Consume()
expected = '[[2x3:float32], [2x2:uint8]]\n[[1x3:float32], [1x2:uint8]]\n'
assert out.getvalue() == expected
def test_BuildBatch():
numbers = [4.1, 3.2, 1.1]
vectors = [np.array([1, 2, 3]), np.array([2, 3, 4]), np.array([3, 4, 5])]
images = [np.zeros((5, 3)), np.ones((5, 3)), np.ones((5, 3))]
class_ids = [1, 2, 1]
samples = zip(numbers, vectors, images, class_ids)
build_batch = (nb.BuildBatch(2, prefetch=0).input(
0, 'number',
float).input(1, 'vector',
np.uint8).input(2, 'image', np.uint8,
False).output(3, 'one_hot', 'uint8', 3))
batches = samples >> build_batch >> Collect()
assert len(batches) == 2
batch = batches[0]
assert len(batch) == 2, 'Expect inputs and outputs'
ins, outs = batch
assert len(ins) == 3, 'Expect three input columns in batch'
assert len(outs) == 1, 'Expect one output column in batch'
assert np.array_equal(ins[0], nb.build_number_batch(numbers[:2], float))
assert np.array_equal(ins[1], nb.build_vector_batch(vectors[:2], 'uint8'))
assert np.array_equal(ins[2], nb.build_image_batch(images[:2], 'uint8'))
assert np.array_equal(outs[0],
nb.build_one_hot_batch(class_ids[:2], 'uint8', 3))
def test_BuildBatch_exceptions():
class_ids = [1, 2]
numbers = [4.1, 3.2]
samples = zip(numbers, class_ids)
with pytest.raises(ValueError) as ex:
build_batch = (nb.BuildBatch(2, prefetch=0).by(0, 'number', float).by(
1, 'invalid', 'uint8', 3))
samples >> build_batch >> Collect()
assert str(ex.value).startswith('Invalid builder')
def test_BuildBatch_fmt():
numbers1 = [1, 2, 3]
numbers2 = [4, 5, 6]
samples = zip(numbers1, numbers2)
build_batch = (nb.BuildBatch(3,
prefetch=0,
fmt=lambda t: ((t[0], t[1], t[0]), t[1])).by(
0, 'number',
float).by(1, 'number', float))
batches = samples >> build_batch >> Collect()
assert len(batches) == 1
((a, b, c), d) = batches[0]
assert list(a) == numbers1
assert list(b) == numbers2
assert list(c) == numbers1
assert list(d) == numbers2
def test_BuildBatch():
numbers = [4.1, 3.2, 1.1]
vectors = [np.array([1, 2, 3]), np.array([2, 3, 4]), np.array([3, 4, 5])]
images = [np.zeros((5, 3)), np.ones((5, 3)), np.ones((5, 3))]
class_ids = [1, 2, 1]
samples = zip(numbers, vectors, images, class_ids)
build_batch = (nb.BuildBatch(2, prefetch=0).by(0, 'number', float).by(
1, 'vector', np.uint8).by(2, 'image', np.uint8,
False).by(3, 'one_hot', 'uint8', 3))
batches = samples >> build_batch >> Collect()
assert len(batches) == 2
batch = batches[0]
assert len(batch) == 4, 'Expect four columns in batch'
assert np.array_equal(batch[0], nb.build_number_batch(numbers[:2], float))
assert np.array_equal(batch[1],
nb.build_vector_batch(vectors[:2], 'uint8'))
assert np.array_equal(batch[2], nb.build_image_batch(images[:2], 'uint8'))
assert np.array_equal(batch[3],
nb.build_one_hot_batch(class_ids[:2], 'uint8', 3))
def test_BuildBatch_prefetch():
samples = [[1], [2]]
build_batch = (nb.BuildBatch(2, prefetch=1).input(0, 'number', 'uint8'))
batches = samples >> build_batch >> Collect()
batch = batches[0][0]
assert np.array_equal(batch, np.array([1, 2], dtype='uint8'))