def testMatmul(self):
t1 = tensor([[0, 1, 0], [1, 0, 0]], chunk_size=2).tosparse()
t2 = t1.T
t3 = matmul(t1, t2, out=empty((2, 2), dtype=t1.dtype, order='F'))
self.assertEqual(t3.order.value, 'F')
with self.assertRaises(TypeError):
matmul(t1, t2, out=1)
with self.assertRaises(TypeError):
matmul(t1, t2, out=empty((2, 2), dtype='?'))
with self.assertRaises(ValueError):
matmul(t1, t2, out=empty((3, 2), dtype=t1.dtype))
raw1 = np.asfortranarray(np.random.rand(3, 3))
raw2 = np.asfortranarray(np.random.rand(3, 3))
raw3 = np.random.rand(3, 3)
self.assertEqual(matmul(tensor(raw1), tensor(raw2)).flags['C_CONTIGUOUS'],
np.matmul(raw1, raw2).flags['C_CONTIGUOUS'])
self.assertEqual(matmul(tensor(raw1), tensor(raw2)).flags['F_CONTIGUOUS'],
np.matmul(raw1, raw2).flags['F_CONTIGUOUS'])
self.assertEqual(matmul(tensor(raw1), tensor(raw2), order='A').flags['C_CONTIGUOUS'],
np.matmul(raw1, raw2, order='A').flags['C_CONTIGUOUS'])
self.assertEqual(matmul(tensor(raw1), tensor(raw2), order='A').flags['F_CONTIGUOUS'],
np.matmul(raw1, raw2, order='A').flags['F_CONTIGUOUS'])
self.assertEqual(matmul(tensor(raw1), tensor(raw3), order='A').flags['C_CONTIGUOUS'],
np.matmul(raw1, raw3, order='A').flags['C_CONTIGUOUS'])
self.assertEqual(matmul(tensor(raw1), tensor(raw3), order='A').flags['F_CONTIGUOUS'],
np.matmul(raw1, raw3, order='A').flags['F_CONTIGUOUS'])
def test_matmul():
t1 = tensor([[0, 1, 0], [1, 0, 0]], chunk_size=2).tosparse()
t2 = t1.T
t3 = matmul(t1, t2, out=empty((2, 2), dtype=t1.dtype, order='F'))
assert t3.order.value == 'F'
with pytest.raises(TypeError):
matmul(t1, t2, out=1)
with pytest.raises(TypeError):
matmul(t1, t2, out=empty((2, 2), dtype='?'))
with pytest.raises(ValueError):
matmul(t1, t2, out=empty((3, 2), dtype=t1.dtype))
raw1 = np.asfortranarray(np.random.rand(3, 3))
raw2 = np.asfortranarray(np.random.rand(3, 3))
raw3 = np.random.rand(3, 3)
assert matmul(tensor(raw1), tensor(raw2)).flags['C_CONTIGUOUS'] == \
np.matmul(raw1, raw2).flags['C_CONTIGUOUS']
assert matmul(tensor(raw1), tensor(raw2)).flags['F_CONTIGUOUS'] == \
np.matmul(raw1, raw2).flags['F_CONTIGUOUS']
assert matmul(tensor(raw1), tensor(raw2), order='A').flags['C_CONTIGUOUS'] == \
np.matmul(raw1, raw2, order='A').flags['C_CONTIGUOUS']
assert matmul(tensor(raw1), tensor(raw2), order='A').flags['F_CONTIGUOUS'] == \
np.matmul(raw1, raw2, order='A').flags['F_CONTIGUOUS']
assert matmul(tensor(raw1), tensor(raw3), order='A').flags['C_CONTIGUOUS'] == \
np.matmul(raw1, raw3, order='A').flags['C_CONTIGUOUS']
assert matmul(tensor(raw1), tensor(raw3), order='A').flags['F_CONTIGUOUS'] == \
np.matmul(raw1, raw3, order='A').flags['F_CONTIGUOUS']
def testDot(self):
t1 = tensor([[0, 1, 0], [1, 0, 0]], chunk_size=2).tosparse()
t2 = t1.T
self.assertTrue(t1.dot(t2).issparse())
self.assertIs(type(t1.dot(t2)), SparseTensor)
self.assertFalse(t1.dot(t2, sparse=False).issparse())
self.assertIs(type(t1.dot(t2, sparse=False)), Tensor)
with self.assertRaises(TypeError):
dot(t1, t2, out=1)
with self.assertRaises(ValueError):
dot(t1, t2, empty((3, 6)))
with self.assertRaises(ValueError):
dot(t1, t2, empty((3, 3), dtype='i4'))
with self.assertRaises(ValueError):
dot(t1, t2, empty((3, 3), order='F'))
t1.dot(t2, out=empty((2, 2), dtype=t1.dtype))
def test_dot():
t1 = tensor([[0, 1, 0], [1, 0, 0]], chunk_size=2).tosparse()
t2 = t1.T
assert t1.dot(t2).issparse() is True
assert type(t1.dot(t2)) is SparseTensor
assert t1.dot(t2, sparse=False).issparse() is False
assert type(t1.dot(t2, sparse=False)) is Tensor
with pytest.raises(TypeError):
dot(t1, t2, out=1)
with pytest.raises(ValueError):
dot(t1, t2, empty((3, 6)))
with pytest.raises(ValueError):
dot(t1, t2, empty((3, 3), dtype='i4'))
with pytest.raises(ValueError):
dot(t1, t2, empty((3, 3), order='F'))
t1.dot(t2, out=empty((2, 2), dtype=t1.dtype))
