VA = A_data[:, :, :, 1:]
tic = time()
out = AP.forward([A], [VA])
toc = time()
runtime_pyadolc_push_forward = toc - tic
adolc_Q = out[0][0]
adolc_R = out[0][1]
adolc_VQ = out[1][0]
adolc_VR = out[1][1]
# compute pullback
WQ = Qbar_data
WR = Rbar_data
tic = time()
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()
VA = A_data[:,:,:,1:]
tic = time()
out = AP.forward([A],[VA])
toc = time()
runtime_pyadolc_push_forward = toc - tic
adolc_Q = out[0][0]
adolc_R = out[0][1]
adolc_VQ = out[1][0]
adolc_VR = out[1][1]
# compute pullback
WQ = Qbar_data
WR = Rbar_data
tic = time()
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))
# time PYADOLC hov_reverse
W = numpy.random.rand(1, 1, D)
start_time = time.time()
V = numpy.random.rand(N, P, D - 1)
for rep in range(reps):
for p in range(P):
adolc.hos_forward(1, x, V[:, p, :], keep=D)
adolc.hov_ti_reverse(1, W)
end_time = time.time()
time_hov_reverse_adolc = end_time - start_time
# time PYADOLC.cgraph hov_reverse
W = numpy.random.rand(1, 1, P, D)
for rep in range(reps):
ap.reverse([W])
end_time = time.time()
time_hov_reverse_cgraph = end_time - start_time
print "----------------"
print time_trace_algopy
print time_trace_adolc
print time_trace_cgraph
print "----------------"
print time_hos_forward_algopy
print time_hos_forward_adolc
print time_hos_forward_cgraph
print "----------------"
print time_hov_forward_algopy
print time_hov_forward_adolc
print time_hov_forward_cgraph
# time PYADOLC hov_reverse
W = numpy.random.rand(1, 1, D)
start_time = time.time()
V = numpy.random.rand(N, P, D - 1)
for rep in range(reps):
for p in range(P):
adolc.hos_forward(1, x, V[:, p, :], keep=D)
adolc.hov_ti_reverse(1, W)
end_time = time.time()
time_hov_reverse_adolc = end_time - start_time
# time PYADOLC.cgraph hov_reverse
W = numpy.random.rand(1, 1, P, D)
for rep in range(reps):
ap.reverse([W])
end_time = time.time()
time_hov_reverse_cgraph = end_time - start_time
print('----------------')
print(time_trace_algopy)
print(time_trace_adolc)
print(time_trace_cgraph)
print('----------------')
print(time_hos_forward_algopy)
print(time_hos_forward_adolc)
print(time_hos_forward_cgraph)
print('----------------')
print(time_hov_forward_algopy)
print(time_hov_forward_adolc)
print(time_hov_forward_cgraph)
