def test_bind_input_types(self):
opset = onnx_opset_version()
devices = [(C_OrtDevice(C_OrtDevice.cpu(), C_OrtDevice.default_memory(), 0), ['CPUExecutionProvider'])]
if "CUDAExecutionProvider" in onnxrt.get_all_providers():
devices.append((C_OrtDevice(C_OrtDevice.cuda(), C_OrtDevice.default_memory(), 0), ['CUDAExecutionProvider']))
for device, provider in devices:
for dtype in [np.float32, np.float64, np.int32, np.uint32,
np.int64, np.uint64, np.int16, np.uint16,
np.int8, np.uint8, np.float16, np.bool_]:
with self.subTest(dtype=dtype, device=str(device)):
x = np.arange(8).reshape((-1, 2)).astype(dtype)
proto_dtype = NP_TYPE_TO_TENSOR_TYPE[x.dtype]
X = helper.make_tensor_value_info('X', proto_dtype, [None, x.shape[1]])
Y = helper.make_tensor_value_info('Y', proto_dtype, [None, x.shape[1]])
# inference
node_add = helper.make_node('Identity', ['X'], ['Y'])
# graph
graph_def = helper.make_graph([node_add], 'lr', [X], [Y], [])
model_def = helper.make_model(
graph_def, producer_name='dummy', ir_version=7,
producer_version="0",
opset_imports=[helper.make_operatorsetid('', opset)])
sess = onnxrt.InferenceSession(model_def.SerializeToString(), providers=provider)
bind = SessionIOBinding(sess._sess)
ort_value = C_OrtValue.ortvalue_from_numpy(x, device)
bind.bind_ortvalue_input('X', ort_value)
bind.bind_output('Y', device)
sess._sess.run_with_iobinding(bind, None)
ortvalue = bind.get_outputs()[0]
y = ortvalue.numpy()
assert_almost_equal(x, y)
bind = SessionIOBinding(sess._sess)
bind.bind_input('X', device, dtype, x.shape, ort_value.data_ptr())
bind.bind_output('Y', device)
sess._sess.run_with_iobinding(bind, None)
ortvalue = bind.get_outputs()[0]
y = ortvalue.numpy()
assert_almost_equal(x, y)
# without changing the binding. It assumes that input size
# and output size never change. It copies the data into
# the fixed buffer and returns the same array, modified
# inplace.
print('ort-bind-inplace')
sess = InferenceSession(onx.SerializeToString(),
providers=['CPUExecutionProvider'])
bind = SessionIOBinding(sess._sess)
ort_device = C_OrtDevice(C_OrtDevice.cpu(), C_OrtDevice.default_memory(), 0)
Y = sess.run(None, {'X': X})[0]
bX = X.copy()
bY = Y.copy()
bind.bind_input('X', ort_device, numpy.float32, bX.shape,
bX.__array_interface__['data'][0])
bind.bind_output('variable', ort_device, numpy.float32, bY.shape,
bY.__array_interface__['data'][0])
ortvalues = bind.get_outputs()
def run_with_iobinding(sess, bX, bY, X, bind, ortvalues):
if X.__array_interface__['strides'] is not None:
raise RuntimeError("onnxruntime only supports contiguous arrays.")
bX[:, :] = X[:, :]
sess._sess.run_with_iobinding(bind, None)
return bY
obs = measure_time(
lambda: run_with_iobinding(sess, bX, bY, X, bind, ortvalues),