def test_ker_shape_5_order_2_stride_2():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
ker_shape = 5, 5
arr_out = np.zeros((8, 13, 4), dtype=DTYPE)
np.random.seed(42)
arr_in[:] = np.random.randn(np.prod(arr_in.shape)).reshape(arr_in.shape)
order = 2
stride = 2
idx = [[4, 3], [10, 6]]
gt = np.array(
[[4.81159449, 5.68032312, 5.07941389, 6.04614496], [4.87372255, 4.47074938, 4.07878876, 4.43441534]],
dtype=DTYPE,
)
lpool(
arr_in,
arr_out=arr_out,
ker_shape=ker_shape,
order=order,
stride=stride,
plugin=plugin,
plugin_kwargs=plugin_kwargs,
)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
arr_out = lpool(
arr_in, ker_shape=ker_shape, order=order, stride=stride, plugin=plugin, plugin_kwargs=plugin_kwargs
)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
def test_strides_scipy_naive():
arr_in = lena() / 1.0
arr_in = arr_in[:12, :12]
for stride in xrange(1, 12):
try:
gt = lpool(arr_in, stride=stride, plugin="scipy_naive")
gv = lpool(arr_in, stride=stride, plugin=plugin, plugin_kwargs=plugin_kwargs)
assert_array_equal(gv, gt)
except NotImplementedError:
raise SkipTest
def test_strides_self():
arr_in = lena() / 1.0
arr_in = arr_in[:12, :12]
for stride in xrange(1, 12):
try:
arr_out = lpool(arr_in, plugin=plugin, plugin_kwargs=plugin_kwargs)
gt = arr_out[::stride, ::stride]
gv = lpool(arr_in, stride=stride, plugin=plugin, plugin_kwargs=plugin_kwargs)
assert_array_equal(gv, gt)
except NotImplementedError:
raise SkipTest
def test_default_input_d_1():
arr_in = np.zeros((20, 30, 1), dtype=DTYPE)
ker_shape = 5, 5
arr_out = np.zeros((16, 26, 1), dtype=DTYPE)
np.random.seed(42)
arr_in[:] = np.random.randn(np.prod(arr_in.shape)).reshape(arr_in.shape)
idx = [[4, 8], [20, 12]]
gt = np.array([[-3.59586287], [9.16217232]], dtype=DTYPE)
lpool(arr_in, arr_out=arr_out, ker_shape=ker_shape, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
arr_out = lpool(arr_in, ker_shape=ker_shape, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
def test_test_lena_npy_array():
arr_in = lena()[::32, ::32].astype(DTYPE)
idx = [[4, 2], [4, 2]]
gt = np.array([1280.99987793, 992.0], dtype=DTYPE)
arr_out = lpool(arr_in, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
def test_ker_shape_5():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
ker_shape = 5, 5
arr_out = np.zeros((16, 26, 4), dtype=DTYPE)
np.random.seed(42)
arr_in[:] = np.random.randn(np.prod(arr_in.shape)).reshape(arr_in.shape)
idx = [[4, 8], [20, 12]]
gt = np.array(
[[7.93315649, -0.24066222, 0.64046526, -3.51567388], [7.14803362, -2.99622989, 9.5001564, 11.99116325]],
dtype=DTYPE,
)
lpool(arr_in, arr_out=arr_out, ker_shape=ker_shape, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
arr_out = lpool(arr_in, ker_shape=ker_shape, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
def test_test_lena_pt3_array():
lena32 = lena()[::32, ::32].astype(DTYPE) / 255.0
arr_in = Array(lena32.shape, dtype=DTYPE)
arr_in[:] = lena32
idx = [[4, 2], [4, 2]]
gt = np.array([5.02353001, 3.89019608], dtype=DTYPE)
arr_out = lpool(arr_in, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
def test_ker_shape_5_order_2():
arr_in = np.zeros((20, 30, 4), dtype=DTYPE)
ker_shape = 5, 5
arr_out = np.zeros((16, 26, 4), dtype=DTYPE)
np.random.seed(42)
arr_in[:] = np.random.randn(np.prod(arr_in.shape)).reshape(arr_in.shape)
order = 2
idx = [[4, 8], [20, 12]]
gt = np.array(
[[5.22081137, 4.9204731, 3.75381684, 4.892416], [5.60951042, 4.28514147, 4.77592659, 5.77252817]],
dtype=DTYPE,
)
lpool(arr_in, arr_out=arr_out, ker_shape=ker_shape, order=order, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
arr_out = lpool(arr_in, ker_shape=ker_shape, order=order, plugin=plugin, plugin_kwargs=plugin_kwargs)
gv = arr_out[idx]
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
def test_default_lena():
arr_in = lena().astype(np.float32) / 1.0
idx = [[4, 2], [4, 2]]
gt = np.array([1442.0, 1455.0], dtype=DTYPE)
arr_out = lpool(arr_in, plugin=plugin, plugin_kwargs=plugin_kwargs)
assert_equals(arr_out.ndim, arr_in.ndim)
gv = arr_out[idx]
print gv.shape
print gv
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
def test_default_lena_non_C_contiguous():
arr_in = lena() / 1.0
arr_in = np.asfortranarray(arr_in)
idx = [[4, 2], [4, 2]]
gt = np.array([1442.0, 1455.0], dtype=DTYPE)
try:
arr_out = lpool(arr_in, plugin=plugin, plugin_kwargs=plugin_kwargs)
assert_equals(arr_out.ndim, arr_in.ndim)
gv = arr_out[idx]
print gv.shape
print gv
assert_allclose_round(gv, gt, rtol=RTOL, atol=ATOL)
except NotImplementedError:
raise SkipTest
