def test_dtcwt2(size, J, no_grad=False, dev='cuda'):
x = torch.randn(*size, requires_grad=(not no_grad)).to(dev)
h0a, h0b, _, _, h1a, h1b, _, _ = level1('farras')
cols, rows = lowlevel2.prep_filt_quad_afb2d(h0a, h1a, h0b, h1b, device=dev)
yh = []
for j in range(3):
x, y = lowlevel2.quad_afb2d(x, cols, rows, mode='zero')
yh.append(y)
return x, yh
def test_dtcwt(size, J, no_grad=False, dev='cuda'):
x = torch.randn(*size, requires_grad=(not no_grad)).to(dev)
h0a, h0b, _, _, h1a, h1b, _, _ = level1('farras')
filts = lowlevel2.prep_filt_quad_afb2d_nonsep(h0a,
h1a,
h0a,
h1a,
h0a,
h1a,
h0b,
h1b,
h0b,
h1b,
h0a,
h1a,
h0b,
h1b,
h0b,
h1b,
device=dev)
for j in range(3):
yl, yh = lowlevel.afb2d_nonsep(x, filts, mode='zero')
x = yl.reshape(yl.shape[0], -1, yl.shape[-2], yl.shape[-1])