def testMatmulExecution(self):
data_a = np.random.randn(10, 20)
data_b = np.random.randn(20)
a = tensor(data_a, chunk_size=2)
b = tensor(data_b, chunk_size=3)
c = matmul(a, b)
res = self.executor.execute_tensor(c, concat=True)[0]
expected = np.matmul(data_a, data_b)
np.testing.assert_allclose(res, expected)
data_a = np.random.randn(10, 20)
data_b = np.random.randn(10)
a = tensor(data_a, chunk_size=2)
b = tensor(data_b, chunk_size=3)
c = matmul(b, a)
res = self.executor.execute_tensor(c, concat=True)[0]
expected = np.matmul(data_b, data_a)
np.testing.assert_allclose(res, expected)
data_a = np.random.randn(15, 1, 20, 30)
data_b = np.random.randn(1, 11, 30, 20)
a = tensor(data_a, chunk_size=12)
b = tensor(data_b, chunk_size=13)
c = matmul(a, b)
res = self.executor.execute_tensor(c, concat=True)[0]
expected = np.matmul(data_a, data_b)
np.testing.assert_allclose(res, expected, atol=.0001)
a = arange(2 * 2 * 4, chunk_size=1).reshape((2, 2, 4))
b = arange(2 * 2 * 4, chunk_size=1).reshape((2, 4, 2))
c = matmul(a, b)
res = self.executor.execute_tensor(c, concat=True)[0]
expected = np.matmul(
np.arange(2 * 2 * 4).reshape(2, 2, 4),
np.arange(2 * 2 * 4).reshape(2, 4, 2))
np.testing.assert_allclose(res, expected, atol=.0001)
data_a = sps.random(10, 20)
data_b = sps.random(20, 5)
a = tensor(data_a, chunk_size=2)
b = tensor(data_b, chunk_size=3)
c = matmul(a, b)
res = self.executor.execute_tensor(c, concat=True)[0]
expected = np.matmul(data_a.toarray(), data_b.toarray())
np.testing.assert_allclose(res.toarray(), expected)
def testMatmul(self):
a_data = [[1, 0], [0, 1]]
b_data = [[4, 1], [2, 2]]
a = tensor(a_data, chunk_size=1)
b = tensor(b_data, chunk_size=1)
t = matmul(a, b)
self.assertEqual(t.shape, (2, 2))
self.assertEqual(calc_shape(t), t.shape)
t.tiles()
self.assertEqual(t.shape, tuple(sum(s) for s in t.nsplits))
self.assertEqual(calc_shape(t.chunks[0]), t.chunks[0].shape)
b_data = [1, 2]
b = tensor(b_data, chunk_size=1)
t = matmul(a, b)
self.assertEqual(t.shape, (2, ))
self.assertEqual(calc_shape(t), t.shape)
t.tiles()
self.assertEqual(t.shape, tuple(sum(s) for s in t.nsplits))
self.assertEqual(calc_shape(t.chunks[0]), t.chunks[0].shape)
t = matmul(b, a)
self.assertEqual(t.shape, (2, ))
self.assertEqual(calc_shape(t), t.shape)
t.tiles()
self.assertEqual(t.shape, tuple(sum(s) for s in t.nsplits))
self.assertEqual(calc_shape(t.chunks[0]), t.chunks[0].shape)
a_data = np.arange(2 * 2 * 4).reshape((2, 2, 4))
b_data = np.arange(2 * 2 * 4).reshape((2, 4, 2))
a = tensor(a_data, chunk_size=1)
b = tensor(b_data, chunk_size=1)
t = matmul(a, b)
self.assertEqual(t.shape, (2, 2, 2))
self.assertEqual(calc_shape(t), t.shape)
t.tiles()
self.assertEqual(t.shape, tuple(sum(s) for s in t.nsplits))
self.assertEqual(calc_shape(t.chunks[0]), t.chunks[0].shape)
t = matmul(tensor([2j, 3j], chunk_size=1),
tensor([2j, 3j], chunk_size=1))
self.assertEqual(t.shape, ())
self.assertEqual(calc_shape(t), t.shape)
t.tiles()
self.assertEqual(t.shape, tuple(sum(s) for s in t.nsplits))
self.assertEqual(calc_shape(t.chunks[0]), t.chunks[0].shape)
with self.assertRaises(ValueError):
matmul([1, 2], 3)
with self.assertRaises(ValueError):
matmul(np.random.randn(2, 3, 4), np.random.randn(3, 4, 3))
t = matmul(tensor(np.random.randn(2, 3, 4), chunk_size=2),
tensor(np.random.randn(3, 1, 4, 3), chunk_size=3))
self.assertEqual(t.shape, (3, 2, 3, 3))
v = ones((100, 100), chunk_size=10)
tv = matmul(v, v)
self.assertEqual(tv.shape, (100, 100))
self.assertEqual(calc_shape(tv), tv.shape)
tv.tiles()
self.assertEqual(tv.shape, tuple(sum(s) for s in tv.nsplits))
self.assertEqual(calc_shape(tv.chunks[0]), tv.chunks[0].shape)