lmbda = 1e-2
opt = cbpdn.ConvBPDN.Options({
'Verbose': True,
'MaxMainIter': 250,
'HighMemSolve': True,
'RelStopTol': 5e-3,
'AuxVarObj': False
})
"""
If GPU available, run CUDA ConvBPDN solver, otherwise run standard Python version.
"""
if cuda.device_count() > 0:
print('%s GPU found: running CUDA solver' % cuda.device_name())
tm = util.Timer()
with sys_pipes(), util.ContextTimer(tm):
X = cuda.cbpdn(D, sh, lmbda, opt)
t = tm.elapsed()
else:
print('GPU not found: running Python solver')
c = cbpdn.ConvBPDN(D, sh, lmbda, opt)
X = c.solve().squeeze()
t = c.timer.elapsed('solve')
print('Solve time: %.2f s' % t)
"""
Reconstruct the image from the sparse representation.
"""
shr = np.sum(spl.fftconv(D, X), axis=2)
imgr = sl + shr
print("Reconstruction PSNR: %.2fdB\n" % spm.psnr(img, imgr))
'LinSolveCheck': False,
'RelStopTol': 2e-3,
'AuxVarObj': False,
'rho': 1.5e0,
'AutoRho': {
'Enabled': False
}
})
# Initialise and run AddMaskSim/ConvBPDN object
b = cbpdn.AddMaskSim(cbpdn.ConvBPDN, D, shw, msk, lmbda, opt=opt)
X1 = b.solve()
print("AddMaskSim/ConvBPDN solve time: %.2fs" % b.timer.elapsed('solve'))
# Time CUDA AddMaskSim/ConvBPDN solve
t = util.Timer()
with util.ContextTimer(t):
X2 = cucbpdn.cbpdnmsk(D, shw, msk, lmbda, opt)
# Solve time comparison
print("GPU AddMaskSim/ConvBPDN solve time: %.2fs" % t.elapsed())
print("GPU time improvement factor: %.1f" %
(b.timer.elapsed('solve') / t.elapsed()))
# Compare CPU and GPU solutions
print("CPU solution: min: %.4e max: %.4e l1: %.4e" %
(X1.min(), X1.max(), np.sum(np.abs(X1))))
print("GPU solution: min: %.4e max: %.4e l1: %.4e" %
(X2.min(), X2.max(), np.sum(np.abs(X2))))
print("CPU/GPU MSE: %.2e SNR: %.2f dB" % (sm.mse(X1, X2), sm.snr(X1, X2)))
def test_21(self):
t = util.Timer()
with util.ContextTimer(t):
t0 = t.elapsed()
assert t.elapsed() >= 0.0
# Set up ConvBPDN options
lmbda = 1e-2
opt = cbpdn.ConvBPDN.Options({
'Verbose': False,
'MaxMainIter': 0,
'HighMemSolve': True,
'LinSolveCheck': True,
'RelStopTol': 1e-5,
'AuxVarObj': False,
'AutoRho': {
'Enabled': False
}
})
# Compute initialisation time: solve with 0 iterations
t0 = util.Timer()
with util.ContextTimer(t0):
X = cucbpdn.cbpdn(D, sh, lmbda, opt)
# Solve with Niter iterations
Niter = 200
opt['MaxMainIter'] = Niter
t1 = util.Timer()
with util.ContextTimer(t1):
X = cucbpdn.cbpdn(D, sh, lmbda, opt)
# Print run time information
print("GPU ConvBPDN init time: %.3fs" % t0.elapsed())
print("GPU ConvBPDN solve time per iteration: %.3fs" % (t1.elapsed() / Niter))
