test_nn.py 文件源码

def test_MaxUnpool2d_output_size(self):
        m = nn.MaxPool2d(3, stride=2, return_indices=True)
        mu = nn.MaxUnpool2d(3, stride=2)
        big_t = torch.rand(1, 1, 6, 6)
        big_t[0][0][4][4] = 100
        output_big, indices_big = m(Variable(big_t))
        self.assertRaises(RuntimeError, lambda: mu(output_big, indices_big))

        small_t = torch.rand(1, 1, 5, 5)
        for i in range(0, 4, 2):
            for j in range(0, 4, 2):
                small_t[:,:,i,j] = 100
        output_small, indices_small = m(Variable(small_t))
        for h in range(3, 10):
            for w in range(3, 10):
                if 4 <= h <= 6 and 4 <= w <= 6:
                    size = (h, w)
                    if h == 5:
                        size = torch.LongStorage(size)
                    elif h == 6:
                        size = torch.LongStorage((1, 1) + size)
                    mu(output_small, indices_small, output_size=size)
                else:
                    self.assertRaises(ValueError, lambda:
                            mu(output_small, indices_small, (h, w)))