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spline_cubic_gpu_test.py 2.04 KB
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import unittest

import torch
from numpy.testing import assert_equal, assert_almost_equal

if torch.cuda.is_available():
    from .spline_cubic_gpu import spline_cubic_gpu


class SplineQuadraticGPUTest(unittest.TestCase):
    @unittest.skipIf(not torch.cuda.is_available(), 'no GPU')
    def test_open_spline(self):
        input = torch.FloatTensor([0, 0.05, 0.25, 0.5, 0.75, 0.95, 1])
        kernel_size = torch.LongTensor([7])
        is_open_spline = torch.LongTensor([1])

        a1, i1 = spline_cubic_gpu(input.cuda(),
                                  kernel_size.cuda(), is_open_spline.cuda(), 7)

        a2 = [
            [0.1667, 0.6667, 0.1667, 0],
            [0.0853, 0.6307, 0.2827, 0.0013],
            [0.1667, 0.6667, 0.1667, 0],
            [0.1667, 0.6667, 0.1667, 0],
            [0.1667, 0.6667, 0.1667, 0],
            [0.0013, 0.2827, 0.6307, 0.0853],
            [0.1667, 0.6667, 0.1667, 0],
        ]
        i2 = [[0, 1, 2, 3], [0, 1, 2, 3], [1, 2, 3, 4], [2, 3, 4, 5],
              [3, 4, 5, 6], [3, 4, 5, 6], [4, 5, 6, 0]]

        assert_almost_equal(a1.cpu().numpy(), a2, 4)
        assert_equal(i1.cpu().numpy(), i2)

    @unittest.skipIf(not torch.cuda.is_available(), 'no GPU')
    def test_closed_spline(self):
        input = torch.FloatTensor([0, 0.05, 0.25, 0.5, 0.75, 0.95, 1])
        kernel_size = torch.LongTensor([4])
        is_open_spline = torch.LongTensor([0])

        a1, i1 = spline_cubic_gpu(input.cuda(),
                                  kernel_size.cuda(), is_open_spline.cuda(), 4)

        a2 = [
            [0.1667, 0.6667, 0.1667, 0],
            [0.0853, 0.6307, 0.2827, 0.0013],
            [0.1667, 0.6667, 0.1667, 0],
            [0.1667, 0.6667, 0.1667, 0],
            [0.1667, 0.6667, 0.1667, 0],
            [0.0013, 0.2827, 0.6307, 0.0853],
            [0.1667, 0.6667, 0.1667, 0],
        ]
        i2 = [[0, 1, 2, 3], [0, 1, 2, 3], [1, 2, 3, 0], [2, 3, 0, 1],
              [3, 0, 1, 2], [3, 0, 1, 2], [0, 1, 2, 3]]

        assert_almost_equal(a1.cpu().numpy(), a2, 4)
        assert_equal(i1.cpu().numpy(), i2)