def test_full(self):
# simple tensor
data = ht.full((10, 2), 4, device=ht_device)
self.assertIsInstance(data, ht.DNDarray)
self.assertEqual(data.shape, (10, 2))
self.assertEqual(data.lshape, (10, 2))
self.assertEqual(data.dtype, ht.float32)
self.assertEqual(data._DNDarray__array.dtype, torch.float32)
self.assertEqual(data.split, None)
self.assertTrue(ht.allclose(data, ht.float32(4.0, device=ht_device)))
# non-standard dtype tensor
data = ht.full((10, 2), 4, dtype=ht.int32, device=ht_device)
self.assertIsInstance(data, ht.DNDarray)
self.assertEqual(data.shape, (10, 2))
self.assertEqual(data.lshape, (10, 2))
self.assertEqual(data.dtype, ht.int32)
self.assertEqual(data._DNDarray__array.dtype, torch.int32)
self.assertEqual(data.split, None)
self.assertTrue(ht.allclose(data, ht.int32(4, device=ht_device)))
# split tensor
data = ht.full((10, 2), 4, split=0, device=ht_device)
self.assertIsInstance(data, ht.DNDarray)
self.assertEqual(data.shape, (10, 2))
self.assertLessEqual(data.lshape[0], 10)
self.assertEqual(data.lshape[1], 2)
self.assertEqual(data.dtype, ht.float32)
self.assertEqual(data._DNDarray__array.dtype, torch.float32)
self.assertEqual(data.split, 0)
self.assertTrue(ht.allclose(data, ht.float32(4.0, device=ht_device)))
# exceptions
with self.assertRaises(TypeError):
ht.full("(2, 3,)", 4, dtype=ht.float64, device=ht_device)
with self.assertRaises(ValueError):
ht.full((-1, 3), 2, dtype=ht.float64, device=ht_device)
with self.assertRaises(TypeError):
ht.full((2, 3), dtype=ht.float64, split="axis", device=ht_device)
def test_any(self):
# float values, minor axis
x = ht.float32([[2.7, 0, 0], [0, 0, 0], [0, 0.3, 0]], device=ht_device)
any_tensor = x.any(axis=1)
res = ht.uint8([1, 0, 1], device=ht_device)
self.assertIsInstance(any_tensor, ht.DNDarray)
self.assertEqual(any_tensor.shape, (3, ))
self.assertEqual(any_tensor.dtype, ht.bool)
self.assertTrue(ht.equal(any_tensor, res))
# integer values, major axis, output tensor
any_tensor = ht.zeros((2, ), device=ht_device)
x = ht.int32([[0, 0], [0, 0], [0, 1]], device=ht_device)
ht.any(x, axis=0, out=any_tensor)
res = ht.uint8([0, 1], device=ht_device)
self.assertIsInstance(any_tensor, ht.DNDarray)
self.assertEqual(any_tensor.shape, (2, ))
self.assertEqual(any_tensor.dtype, ht.bool)
self.assertTrue(ht.equal(any_tensor, res))
# float values, no axis
x = ht.float64([[0, 0, 0], [0, 0, 0]], device=ht_device)
res = ht.zeros(1, dtype=ht.uint8, device=ht_device)
any_tensor = ht.any(x)
self.assertIsInstance(any_tensor, ht.DNDarray)
self.assertEqual(any_tensor.shape, (1, ))
self.assertEqual(any_tensor.dtype, ht.bool)
self.assertTrue(ht.equal(any_tensor, res))
# split tensor, along axis
x = ht.arange(10, split=0, device=ht_device)
any_tensor = ht.any(x, axis=0)
res = ht.uint8([1], device=ht_device)
self.assertIsInstance(any_tensor, ht.DNDarray)
self.assertEqual(any_tensor.shape, (1, ))
self.assertEqual(any_tensor.dtype, ht.bool)
self.assertTrue(ht.equal(any_tensor, res))
def test_full(self):
# simple tensor
data = ht.full((
10,
2,
), 4)
self.assertIsInstance(data, ht.tensor)
self.assertEqual(data.shape, (
10,
2,
))
self.assertEqual(data.lshape, (
10,
2,
))
self.assertEqual(data.dtype, ht.float32)
self.assertEqual(data._tensor__array.dtype, torch.float32)
self.assertEqual(data.split, None)
self.assertTrue(ht.allclose(data, ht.float32(4.0)))
# non-standard dtype tensor
data = ht.full((
10,
2,
), 4, dtype=ht.int32)
self.assertIsInstance(data, ht.tensor)
self.assertEqual(data.shape, (
10,
2,
))
self.assertEqual(data.lshape, (
10,
2,
))
self.assertEqual(data.dtype, ht.int32)
self.assertEqual(data._tensor__array.dtype, torch.int32)
self.assertEqual(data.split, None)
self.assertTrue(ht.allclose(data, ht.int32(4)))
# split tensor
data = ht.full((
10,
2,
), 4, split=0)
self.assertIsInstance(data, ht.tensor)
self.assertEqual(data.shape, (
10,
2,
))
self.assertLessEqual(data.lshape[0], 10)
self.assertEqual(data.lshape[1], 2)
self.assertEqual(data.dtype, ht.float32)
self.assertEqual(data._tensor__array.dtype, torch.float32)
self.assertEqual(data.split, 0)
self.assertTrue(ht.allclose(data, ht.float32(4.0)))
# exceptions
with self.assertRaises(TypeError):
ht.full('(2, 3,)', 4, dtype=ht.float64)
with self.assertRaises(ValueError):
ht.full((
-1,
3,
), 2, dtype=ht.float64)
with self.assertRaises(TypeError):
ht.full((
2,
3,
), dtype=ht.float64, split='axis')
