def testOrtValueDlPack_bool(self):
numpy_arr_input = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=np.bool)
ortvalue = onnxrt.OrtValue.ortvalue_from_numpy(numpy_arr_input)
self.assertEqual(numpy_arr_input.shape, tuple(ortvalue.shape()))
ptr = ortvalue._ortvalue.data_ptr()
dlp = ortvalue._ortvalue.to_dlpack()
self.assertTrue(C.is_dlpack_uint8_tensor(dlp))
ortvalue2 = C_OrtValue.from_dlpack(dlp, True)
self.assertEqual(ptr, ortvalue2.data_ptr())
new_array = ortvalue2.numpy()
assert_almost_equal(numpy_arr_input, new_array)
dlp = ortvalue._ortvalue.__dlpack__()
self.assertTrue(C.is_dlpack_uint8_tensor(dlp))
ortvalue2 = C_OrtValue.from_dlpack(dlp, True)
self.assertEqual(ptr, ortvalue2.data_ptr())
new_array = ortvalue2.numpy()
assert_almost_equal(numpy_arr_input, new_array)
device = ortvalue._ortvalue.__dlpack_device__()
self.assertEqual((1, 0), device)
def OrtValueVectorDlPackOrtValue(self,
my_to_tensor,
tensor_type,
device,
dtype=np.float32):
narrays = [
np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=dtype),
np.array([[6.0, 7.0], [8.0, 9.0], [1.0, 6.0]], dtype=dtype)
]
vect = OrtValueVector()
ptr = []
for a in narrays:
ortvalue = onnxrt.OrtValue.ortvalue_from_numpy(a, device)
vect.push_back(ortvalue._ortvalue)
ptr.append(ortvalue.data_ptr())
self.assertEqual(len(vect), 2)
converted_values = vect.to_dlpacks(my_to_tensor)
self.assertEqual(len(converted_values), len(vect))
if my_to_tensor is None:
self.assertIn("PyCapsule", str(type(converted_values[0])))
converted_values = [
C_OrtValue.from_dlpack(o, False) for o in converted_values
]
else:
assert all(
map(lambda v: isinstance(v, tensor_type), converted_values))
# We make sure the function does not leak any python object.
cf = [sys.getrefcount(o) for o in converted_values]
dummy = [np.array([[0, 1]]), dict(a=3)]
cf2 = [sys.getrefcount(o) for o in dummy]
self.assertEqual(cf, cf2) # it should be [3, 3]
ptr2 = []
for av1, v2 in zip(narrays, converted_values):
ptr2.append(v2.data_ptr())
if hasattr(v2, 'cpu'):
av2 = v2.cpu().numpy()
else:
av2 = v2.numpy()
assert_almost_equal(av1, av2)
self.assertEqual(ptr, ptr2)
def my_to_tensor(dlpack_structure):
return C_OrtValue.from_dlpack(dlpack_structure, False)