def test_sqnorm_array_multi_gpu(self):
x0 = cuda.to_gpu(self.x, device=0)
x1 = cuda.to_gpu(self.x, device=1)
a0 = cuda.to_gpu(self.a, device=0)
a1 = cuda.to_gpu(self.a, device=1)
self.assertAlmostEqual(optimizer._sum_sqnorm(
[self.x, self.a, x0, a0, x1, a1]), 8.75 * 3)
def test_sqnorm_array_multi_gpu(self):
x0 = cuda.to_gpu(self.x, device=0)
x1 = cuda.to_gpu(self.x, device=1)
a0 = cuda.to_gpu(self.a, device=0)
a1 = cuda.to_gpu(self.a, device=1)
self.assertAlmostEqual(
optimizer._sum_sqnorm([self.x, self.a, x0, a0, x1, a1]), 8.75 * 3)
def test_sqnorm_array(self):
x = cuda.to_gpu(self.x)
a = cuda.to_gpu(self.a)
self.assertAlmostEqual(optimizer._sum_sqnorm(
[self.x, self.a, x, a]), 8.75 * 2)
def test_sqnorm_scalar_gpu(self):
a = cuda.to_gpu(self.a)
self.assertAlmostEqual(optimizer._sum_sqnorm([a]), 4)
def test_sqnorm_gpu(self):
x = cuda.to_gpu(self.x)
self.assertAlmostEqual(optimizer._sum_sqnorm([x]), 4.75)
def test_sqnorm_scalar_cpu(self):
self.assertAlmostEqual(optimizer._sum_sqnorm([self.a]), 4)
def test_sqnorm_cpu(self):
# \Sum_{n=0}^{5} (-1.0+0.5n)**2 = 4.75
self.assertAlmostEqual(optimizer._sum_sqnorm([self.x]), 4.75)
def test_sqnorm_array(self):
x = cuda.to_gpu(self.x)
a = cuda.to_gpu(self.a)
self.assertAlmostEqual(optimizer._sum_sqnorm([self.x, self.a, x, a]),
8.75 * 2)
def test_sqnorm_scalar_gpu(self):
a = cuda.to_gpu(self.a)
self.assertAlmostEqual(optimizer._sum_sqnorm([a]), 4)
def test_sqnorm_gpu(self):
x = cuda.to_gpu(self.x)
self.assertAlmostEqual(optimizer._sum_sqnorm([x]), 4.75)
def test_sqnorm_scalar_cpu(self):
self.assertAlmostEqual(optimizer._sum_sqnorm([self.a]), 4)
def test_sqnorm_cpu(self):
# \Sum_{n=0}^{5} (-1.0+0.5n)**2 = 4.75
self.assertAlmostEqual(optimizer._sum_sqnorm([self.x]), 4.75)
