toc = time()
runtime_pyadolc_pullback = toc - tic
#----------------------------------------------
# STEP 2:
# QR decomposition using LAPACK
# using algopy for the differentiation
#----------------------------------------------
# comute push forward
A = UTPM(
numpy.ascontiguousarray(A_data.transpose((3, 2, 0, 1))))
Q = UTPM(numpy.zeros((D, P, N, N)))
R = UTPM(numpy.zeros((D, P, N, N)))
tic = time()
Q, R = UTPM.qr(A, out=(Q, R))
toc = time()
runtime_algopy_push_forward = toc - tic
# compute pullback
Qbar = UTPM(
numpy.ascontiguousarray(Qbar_data[0, ...].transpose(
(3, 2, 0, 1))))
Rbar = UTPM(
numpy.ascontiguousarray(Rbar_data[0, ...].transpose(
(3, 2, 0, 1))))
tic = time()
Q, R = UTPM.qr(A)
Abar = UTPM.pb_qr(Qbar, Rbar, A, Q, R)
toc = time()
runtime_algopy_pullback = toc - tic
out = AP.reverse([WQ, WR])
toc = time()
runtime_pyadolc_pullback = toc - tic
#----------------------------------------------
# STEP 2:
# QR decomposition using LAPACK
# using algopy for the differentiation
#----------------------------------------------
# comute push forward
A = UTPM(numpy.ascontiguousarray(A_data.transpose((3,2,0,1))))
Q = UTPM(numpy.zeros((D,P,N,N)))
R = UTPM(numpy.zeros((D,P,N,N)))
tic = time()
Q,R = UTPM.qr(A, out = (Q,R))
toc = time()
runtime_algopy_push_forward = toc - tic
# compute pullback
Qbar = UTPM(numpy.ascontiguousarray(Qbar_data[0,...].transpose((3,2,0,1))))
Rbar = UTPM(numpy.ascontiguousarray(Rbar_data[0,...].transpose((3,2,0,1))))
tic = time()
Q,R = UTPM.qr(A)
Abar = UTPM.pb_qr(Qbar, Rbar, A, Q, R)
toc = time()
runtime_algopy_pullback = toc - tic
push_forward_ratio = runtime_algopy_push_forward/runtime_pyadolc_push_forward
pullback_ratio = runtime_algopy_pullback/runtime_pyadolc_pullback
print 'relative runtime of the push forward: algopy/pyadolc =', push_forward_ratio
