|
| 1 | +#!/usr/bin/python |
| 2 | + |
| 3 | +####################################################### |
| 4 | +# Copyright (c) 2015, ArrayFire |
| 5 | +# All rights reserved. |
| 6 | +# |
| 7 | +# This file is distributed under 3-clause BSD license. |
| 8 | +# The complete license agreement can be obtained at: |
| 9 | +# http://arrayfire.com/licenses/BSD-3-Clause |
| 10 | +######################################################## |
| 11 | + |
| 12 | +import arrayfire as af |
| 13 | +import sys |
| 14 | +from array import array |
| 15 | + |
| 16 | +def af_assert(left, right, eps=1E-6): |
| 17 | + if (af.max(af.abs(left -right)) > eps): |
| 18 | + raise ValueError("Arrays not within dictated precision") |
| 19 | + return |
| 20 | + |
| 21 | +if __name__ == "__main__": |
| 22 | + if (len(sys.argv) > 1): |
| 23 | + af.set_device(int(sys.argv[1])) |
| 24 | + af.info() |
| 25 | + |
| 26 | + h_dx = array('f', (1.0/12, -8.0/12, 0, 8.0/12, 1.0/12)) |
| 27 | + h_spread = array('f', (1.0/5, 1.0/5, 1.0/5, 1.0/5, 1.0/5)) |
| 28 | + |
| 29 | + img = af.randu(640, 480) |
| 30 | + dx = af.Array(h_dx, (5,1)) |
| 31 | + spread = af.Array(h_spread, (1, 5)) |
| 32 | + kernel = af.matmul(dx, spread) |
| 33 | + |
| 34 | + full_res = af.convolve2(img, kernel) |
| 35 | + sep_res = af.convolve2_separable(dx, spread, img) |
| 36 | + |
| 37 | + af_assert(full_res, sep_res) |
| 38 | + |
| 39 | + print("full 2D convolution time: %.5f ms" % |
| 40 | + (1000 * af.timeit(af.convolve2, img, kernel))) |
| 41 | + print("separable 2D convolution time: %.5f ms" % |
| 42 | + (1000 * af.timeit(af.convolve2_separable, dx, spread, img))) |
0 commit comments