def test_exp2(self):
elements = 10
comparison = np.exp2(torch.arange(elements, dtype=torch.float64))
# exponential of float32
float32_tensor = ht.arange(elements, dtype=ht.float32)
float32_exp2 = ht.exp2(float32_tensor)
self.assertIsInstance(float32_exp2, ht.tensor)
self.assertEqual(float32_exp2.dtype, ht.float32)
self.assertEqual(float32_exp2.dtype, ht.float32)
in_range = (float32_exp2._tensor__array - comparison.type(torch.float32)) < FLOAT_EPSILON
self.assertTrue(in_range.all())
# exponential of float64
float64_tensor = ht.arange(elements, dtype=ht.float64)
float64_exp2 = ht.exp2(float64_tensor)
self.assertIsInstance(float64_exp2, ht.tensor)
self.assertEqual(float64_exp2.dtype, ht.float64)
self.assertEqual(float64_exp2.dtype, ht.float64)
in_range = (float64_exp2._tensor__array - comparison) < FLOAT_EPSILON
self.assertTrue(in_range.all())
# exponential of ints, automatic conversion to intermediate floats
int32_tensor = ht.arange(elements, dtype=ht.int32)
int32_exp2 = ht.exp2(int32_tensor)
self.assertIsInstance(int32_exp2, ht.tensor)
self.assertEqual(int32_exp2.dtype, ht.float64)
self.assertEqual(int32_exp2.dtype, ht.float64)
in_range = (int32_exp2._tensor__array - comparison) < FLOAT_EPSILON
self.assertTrue(in_range.all())
# exponential of longs, automatic conversion to intermediate floats
int64_tensor = ht.arange(elements, dtype=ht.int64)
int64_exp2 = ht.exp2(int64_tensor)
self.assertIsInstance(int64_exp2, ht.tensor)
self.assertEqual(int64_exp2.dtype, ht.float64)
self.assertEqual(int64_exp2.dtype, ht.float64)
in_range = (int64_exp2._tensor__array - comparison) < FLOAT_EPSILON
self.assertTrue(in_range.all())
# check exceptions
with self.assertRaises(TypeError):
ht.exp2([1, 2, 3])
with self.assertRaises(TypeError):
ht.exp2('hello world')
def test_exp2(self):
elements = 10
tmp = np.exp2(torch.arange(elements, dtype=torch.float64))
comparison = ht.array(tmp)
# exponential of float32
float32_tensor = ht.arange(elements, dtype=ht.float32)
float32_exp2 = ht.exp2(float32_tensor)
self.assertIsInstance(float32_exp2, ht.DNDarray)
self.assertEqual(float32_exp2.dtype, ht.float32)
self.assertEqual(float32_exp2.dtype, ht.float32)
self.assertTrue(
ht.allclose(float32_exp2, comparison.astype(ht.float32)))
# exponential of float64
float64_tensor = ht.arange(elements, dtype=ht.float64)
float64_exp2 = ht.exp2(float64_tensor)
self.assertIsInstance(float64_exp2, ht.DNDarray)
self.assertEqual(float64_exp2.dtype, ht.float64)
self.assertEqual(float64_exp2.dtype, ht.float64)
self.assertTrue(ht.allclose(float64_exp2, comparison))
# exponential of ints, automatic conversion to intermediate floats
int32_tensor = ht.arange(elements, dtype=ht.int32)
int32_exp2 = ht.exp2(int32_tensor)
self.assertIsInstance(int32_exp2, ht.DNDarray)
self.assertEqual(int32_exp2.dtype, ht.float64)
self.assertEqual(int32_exp2.dtype, ht.float64)
self.assertTrue(ht.allclose(int32_exp2, comparison))
# exponential of longs, automatic conversion to intermediate floats
int64_tensor = ht.arange(elements, dtype=ht.int64)
int64_exp2 = int64_tensor.exp2()
self.assertIsInstance(int64_exp2, ht.DNDarray)
self.assertEqual(int64_exp2.dtype, ht.float64)
self.assertEqual(int64_exp2.dtype, ht.float64)
self.assertTrue(ht.allclose(int64_exp2, comparison))
# check exceptions
with self.assertRaises(TypeError):
ht.exp2([1, 2, 3])
with self.assertRaises(TypeError):
ht.exp2("hello world")