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#
# MIT No Attribution
#
# Copyright (C) 2010-2023 Joel Andersson, Joris Gillis, Moritz Diehl, KU Leuven.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of this
# software and associated documentation files (the "Software"), to deal in the Software
# without restriction, including without limitation the rights to use, copy, modify,
# merge, publish, distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
# INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
# PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
#
import numpy as np
import time
print("importing casadi...")
from casadi import *
# number of inputs to evaluate in parallel
N = 300
# dummy input
dummyInput = np.linspace(0.0, 2.0*np.pi, N)
# make a dummy function that's moderately expensive to evaluate
print("creating dummy function....")
x = SX.sym('x')
y = x
for k in range(100000):
y = sin(y)
f0 = Function('f', [x], [y])
# evaluate it serially, the old-fasioned way
X = MX.sym('x',N)
Y = vertcat(*[f0(X[k]) for k in range(N)])
fNaiveParallel = Function('fParallel', [X], [Y])
print("evaluating naive parallel function...")
t0 = time.time()
outNaive = fNaiveParallel(dummyInput)
t1 = time.time()
print("evaluated naive parallel function in %.3f seconds" % (t1 - t0))
# evaluate it using new serial map construct
fMap = f0.map(N)
print("evaluating serial map function...")
t0 = time.time()
outMap = fMap(dummyInput)
t1 = time.time()
print("evaluated serial map function in %.3f seconds" % (t1 - t0))
# the following has different shaped outputs, so it's commented out
#print outNaive == outMap
# evaluate it using new parallel map construct
fMap = f0.map(N, "openmp")
print("evaluating parallel map function...")
t0 = time.time()
outMap = fMap(dummyInput)
t1 = time.time()
print("evaluated parallel map function in %.3f seconds" % (t1 - t0))
# the following has different shaped outputs, so it's commented out
#print outNaive == outMap
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