def test_tensordot_basic(app_inst: ArrayApplication):
shape = 2, 4, 10, 15
npX = np.arange(np.product(shape)).reshape(*shape)
rX = app_inst.array(npX, block_shape=(1, 2, 10, 3))
rResult = rX.T.tensordot(rX, axes=1)
assert np.allclose(rResult.get(), (np.tensordot(npX.T, npX, axes=1)))
common.check_block_integrity(rResult)
def test_tensordot_all_shapes(app_inst: ArrayApplication):
for axes in [0, 1, 2]:
if axes == 2:
a = np.arange(7 * 6 * 4).reshape((7, 6, 4))
b = np.arange(6 * 4 * 9).reshape((6, 4, 9))
c = np.tensordot(a, b, axes=axes)
elif axes in (1, 0):
a = np.arange(7 * 6 * 4).reshape((7, 6, 4))
b = np.arange(6 * 4 * 9).reshape((4, 6, 9))
c = np.tensordot(a, b, axes=axes)
else:
raise Exception()
a_block_shapes = list(
itertools.product(
*list(map(lambda x: list(range(1, x + 1)), a.shape))))
b_block_shapes = list(
itertools.product(
*list(map(lambda x: list(range(1, x + 1)), b.shape))))
pbar = tqdm.tqdm(total=np.product(
[len(a_block_shapes), len(b_block_shapes)]))
for a_block_shape in a_block_shapes:
for b_block_shape in b_block_shapes:
pbar.update(1)
if a_block_shape[-axes:] != b_block_shape[:axes]:
continue
pbar.set_description(
"axes=%s %s @ %s" %
(str(axes), str(a_block_shape), str(b_block_shape)))
block_a = app_inst.array(a, block_shape=a_block_shape)
block_b = app_inst.array(b, block_shape=b_block_shape)
block_c = block_a.tensordot(block_b, axes=axes)
assert np.allclose(block_c.get(), c)
common.check_block_integrity(block_c)
def test_bops(bop_data: tuple):
X, Y, npX, npY = bop_data
# Add
Z = X + Y
npZ = npX + npY
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Subtract
Z = X - Y
npZ = npX - npY
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Multiply
Z = X * Y
npZ = npX * npY
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Divide
Z = X / Y
npZ = npX / npY
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Power
Z = X**Y
npZ = npX**npY
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
def test_tensordot_large_shape(app_inst: ArrayApplication):
a = np.arange(4 * 6 * 10 * 90).reshape((90, 10, 6, 4))
b = np.arange(4 * 6 * 10 * 75).reshape((4, 6, 10, 75))
c = np.tensordot(a, b, axes=1)
block_a = app_inst.array(a, block_shape=(30, 5, 3, 2))
block_b = app_inst.array(b, block_shape=(2, 3, 5, 25))
block_c = block_a.tensordot(block_b, axes=1)
assert np.allclose(block_c.get(), c)
common.check_block_integrity(block_c)
def test_concatenate(app_inst: ArrayApplication):
axis = 1
real_X, _ = BimodalGaussian.get_dataset(1000, 9)
real_ones = np.ones(shape=(1000, 1))
X = app_inst.array(real_X, block_shape=(100, 9))
ones = app_inst.ones((1000, 1), (100, 1), dtype=X.dtype)
X_concated = app_inst.concatenate([X, ones],
axis=axis,
axis_block_size=X.block_shape[axis])
common.check_block_integrity(X_concated)
real_X_concated = np.concatenate([real_X, real_ones], axis=axis)
assert np.allclose(X_concated.get(), real_X_concated)
real_X2 = np.random.random_sample(1000 * 17).reshape(1000, 17)
X2 = app_inst.array(real_X2, block_shape=(X.block_shape[0], 3))
X_concated = app_inst.concatenate([X, ones, X2],
axis=axis,
axis_block_size=X.block_shape[axis])
common.check_block_integrity(X_concated)
real_X_concated = np.concatenate([real_X, real_ones, real_X2], axis=axis)
assert np.allclose(X_concated.get(), real_X_concated)
y1 = app_inst.zeros(shape=(50, ), block_shape=(10, ), dtype=int)
y2 = app_inst.ones(shape=(50, ), block_shape=(10, ), dtype=int)
y = app_inst.concatenate([y1, y2], axis=0)
common.check_block_integrity(y)
def test_conversions(conversions_data: tuple):
X, npX, Y = conversions_data
# Add
Z = X + Y
npZ = npX + Y
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
if isinstance(Y, np.ndarray):
with pytest.raises(TypeError):
Z = Y + X
else:
Z = Y + X
npZ = Y + npX
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Subtract
Z = X - Y
npZ = npX - Y
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
if isinstance(Y, np.ndarray):
with pytest.raises(TypeError):
Z = Y - X
else:
Z = Y - X
npZ = Y - npX
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Multiply
Z = X * Y
npZ = npX * Y
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
if isinstance(Y, np.ndarray):
with pytest.raises(TypeError):
Z = Y * X
else:
Z = Y * X
npZ = Y * npX
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Divide
Z = X / Y
npZ = npX / Y
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
if isinstance(Y, np.ndarray):
with pytest.raises(TypeError):
Z = Y / X
else:
Z = Y / X
npZ = Y / npX
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
# Power
Z = X**Y
npZ = npX**Y
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
if isinstance(Y, np.ndarray):
with pytest.raises(TypeError):
Z = Y**X
else:
Z = Y**X
npZ = Y**npX
assert np.allclose(Z.get(), npZ)
common.check_block_integrity(Z)
def test_array_integrity(app_inst: ArrayApplication):
shape = 12, 21
npX = np.arange(np.product(shape)).reshape(*shape)
X = app_inst.array(npX, block_shape=(6, 7))
common.check_block_integrity(X)
