def test_gradients():
ha = qshift('qshift_c')[0]
hb = qshift('qshift_c')[1]
im_t = torch.unsqueeze(torch.tensor(barbara, dtype=torch.float32,
requires_grad=True), dim=0)
y_t = coldfilt(im_t, prep_filt(ha, 1), prep_filt(hb, 1), np.sum(ha*hb) > 0)
dy = np.random.randn(*tuple(y_t.shape)).astype('float32')
torch.autograd.grad(y_t, im_t, grad_outputs=torch.tensor(dy))
def test_equal_numpy_qshift1(hp):
if hp:
ha = qshift('qshift_a')[4]
hb = qshift('qshift_a')[5]
else:
ha = qshift('qshift_a')[0]
hb = qshift('qshift_a')[1]
ref = ref_coldfilt(barbara, ha, hb)
y = coldfilt(barbara_t, prep_filt(ha, 1).to(dev), prep_filt(hb, 1).to(dev),
highpass=hp)
np.testing.assert_array_almost_equal(y[0].cpu(), ref, decimal=4)
def test_equal_small_in(hp):
if hp:
ha = qshift('qshift_a')[4]
hb = qshift('qshift_a')[5]
else:
ha = qshift('qshift_a')[0]
hb = qshift('qshift_a')[1]
im = barbara[:,0:4,0:4]
im_t = torch.unsqueeze(torch.tensor(im, dtype=torch.float32), dim=0).to(dev)
ref = ref_coldfilt(im, ha, hb)
y = coldfilt(im_t, prep_filt(ha, 1).to(dev), prep_filt(hb, 1).to(dev),
highpass=hp)
np.testing.assert_array_almost_equal(y[0].cpu(), ref, decimal=4)
def test_gradients(hp):
if hp:
ha = qshift('qshift_b')[4]
hb = qshift('qshift_b')[5]
else:
ha = qshift('qshift_b')[0]
hb = qshift('qshift_b')[1]
im_t = torch.unsqueeze(torch.tensor(barbara,
dtype=torch.float32,
requires_grad=True),
dim=0).to(dev)
y_t = rowdfilt(im_t,
prep_filt(ha, 1).to(dev),
prep_filt(hb, 1).to(dev),
highpass=hp)
np.random.randn(*tuple(y_t.shape)).astype('float32')
def test_equal_small_in():
h = qshift('qshift_b')[0]
im = barbara[:,0:4,0:4]
im_t = torch.unsqueeze(torch.tensor(im, dtype=torch.float32), dim=0).to(dev)
ref = ref_colfilter(im, h)
y = colfilter(im_t, prep_filt(h, 1).to(dev))
np.testing.assert_array_almost_equal(y[0].cpu(), ref, decimal=4)
def test_qshift():
h = qshift('qshift_a')[0]
y_op = colfilter(barbara_t, prep_filt(h, 1).to(dev))
assert list(y_op.shape)[1:] == bshape_extrarow
def test_equal_numpy_qshift1():
h = qshift('qshift_c')[0]
ref = ref_colfilter(barbara, h)
y = colfilter(barbara_t, prep_filt(h, 1).to(dev))
np.testing.assert_array_almost_equal(y[0].cpu(), ref, decimal=4)
