def setup():
global barbara, barbara_t
global bshape, bshape_half
global ref_rowdfilt, ch
py3nvml.grab_gpus(1, gpu_fraction=0.5, env_set_ok=True)
barbara = datasets.barbara()
barbara = (barbara / barbara.max()).astype('float32')
barbara = barbara.transpose([2, 0, 1])
bshape = list(barbara.shape)
bshape_half = bshape[:]
bshape_half[2] //= 2
barbara_t = torch.unsqueeze(torch.tensor(barbara, dtype=torch.float32),
dim=0).to(dev)
ch = barbara_t.shape[1]
# Some useful functions
ref_rowdfilt = lambda x, ha, hb: np.stack(
[np_coldfilt(s.T, ha, hb).T for s in x], axis=0)
def setup():
global barbara, barbara_t
global bshape, bshape_extrarow
global ref_colfilter, ch
py3nvml.grab_gpus(1, gpu_fraction=0.5)
barbara = datasets.barbara()
barbara = (barbara / barbara.max()).astype('float32')
barbara = barbara.transpose([2, 0, 1])
bshape = list(barbara.shape)
bshape_extrarow = bshape[:]
bshape_extrarow[1] += 1
barbara_t = torch.unsqueeze(torch.tensor(barbara, dtype=torch.float32),
dim=0).to(dev)
ch = barbara_t.shape[1]
# Some useful functions
ref_colfilter = lambda x, h: np.stack([np_colfilter(s, h) for s in x],
axis=0)