Raise an exception when inplace and intermediate are True (OnnxInference.run)

_unittests/ut_onnxrt/test_onnx_inference.py

@@ -139,7 +139,7 @@ def test_onnx_inference_verbose_intermediate(self):
  model_def = to_onnx(clr, X_train.astype(numpy.float32))
  for runtime in ['python', 'python_compiled']:
  with self.subTest(runtime=runtime):
- oinf = OnnxInference(model_def)
+ oinf = OnnxInference(model_def, inplace=False)
  buf = BufferedPrint()
  got = oinf.run({'X': X_test.astype(numpy.float32)},
  verbose=15, fLOG=buf.fprint,

_unittests/ut_onnxrt/test_onnxrt_onnxruntime_runtime_.py

@@ -42,7 +42,7 @@ def test_onnxt_runtime_add(self):
  self.assertEqual(list(sorted(got)), ['Y1'])
  self.assertEqualArray(idi + X, got['Y1'], decimal=6)
 
- oinf = OnnxInference(model_def, runtime='onnxruntime1')
+ oinf = OnnxInference(model_def, runtime='onnxruntime1', inplace=False)
  got = oinf.run({'X': X}, intermediate=True)
  self.assertEqual(list(sorted(got)), ['Ad_Addcst', 'X', 'Y1'])
  self.assertEqualArray(idi + X, got['Y1'], decimal=6)

_unittests/ut_onnxrt/test_onnxrt_side_by_side.py

@@ -84,7 +84,7 @@ def test_kernel_ker2_def(self):
  inputs=[('X', FloatTensorType([None, None]))],
  outputs=[('Y', FloatTensorType([None, None]))],
  target_opset=get_opset_number_from_onnx())
- sess = OnnxInference(model_onnx.SerializeToString())
+ sess = OnnxInference(model_onnx.SerializeToString(), inplace=False)
 
  res = sess.run({'X': Xtest_.astype(numpy.float32)})
  m1 = res['Y']
@@ -182,8 +182,9 @@ def myprint(*args, **kwargs):
  self.assertEqual(sbs[1]['order[0]'], 0)
 
  sess3 = _capture_output(
- lambda: OnnxInference(model_onnx.SerializeToString(),
- runtime="onnxruntime2"), 'c')[0]
+ lambda: OnnxInference(
+ model_onnx.SerializeToString(), runtime="onnxruntime2",
+ inplace=False), 'c')[0]
  try:
  sbs = side_by_side_by_values(
  [cpu, sess, sess3], inputs={'X': Xtest_.astype(numpy.float32)})

_unittests/ut_tools/test_onnx_manipulations.py

@@ -361,8 +361,8 @@ def test_insert_results_into_onnx(self):
  # with open('debug.onnx', 'wb') as f:
  # f.write(new_graph.SerializeToString())
 
- oinf1 = OnnxInference(model_def)
- oinf2 = OnnxInference(new_graph)
+ oinf1 = OnnxInference(model_def, inplace=False)
+ oinf2 = OnnxInference(new_graph, inplace=False)
  cst = numpy.array([[5.6, 7.8]])
  self.assertEqualArray(oinf1.run({'X': cst})['Z'],
  oinf2.run({'X': cst})['Z'])

_unittests/ut_tools/test_zoo.py

@@ -45,7 +45,7 @@ def test_verify_side_by_side(self):
  return
  oinf2 = OnnxInference(link, runtime="python", inplace=False)
  oinf2 = oinf2.build_intermediate('474')['474']
- oinf1 = OnnxInference(link, runtime="onnxruntime1")
+ oinf1 = OnnxInference(link, runtime="onnxruntime1", inplace=False)
  oinf1 = oinf1.build_intermediate('474')['474']
  inputs ={'input': data['test_data_set_0']['in']['input_0']}
  rows = side_by_side_by_values([oinf1, oinf2], inputs=inputs)

mlprodict/onnx_tools/onnx2py_helper.py

@@ -50,7 +50,21 @@ def from_array(value, name=None):
  :return: ONNX tensor
  """
  if isinstance(value, numpy.ndarray):
- pb = onnx_from_array(value, name=name)
+ try:
+ pb = onnx_from_array(value, name=name)
+ except NotImplementedError as e:
+ if value.dtype == numpy.dtype('O'):
+ pb = TensorProto()
+ pb.data_type = TensorProto.STRING # pylint: disable=E1101
+ if name is not None:
+ pb.name = name
+ pb.dims.extend(value.shape) # pylint: disable=E1101
+ pb.string_data.extend( # pylint: disable=E1101
+ list(map(lambda o: str(o).encode('utf-8'), value.ravel())))
+ else:
+ raise NotImplementedError(
+ "Unable to convert type %r (dtype=%r) into an ONNX tensor "
+ "due to %r." % (type(value), value.dtype, e)) from e
  return pb
  if isinstance(value, TensorProto):
  return value

mlprodict/onnxrt/onnx_inference.py

@@ -693,6 +693,10 @@ def retype(col_array):
  name, retype(numpy.expand_dims(inputs[name].values, axis=1)))
  for name in inputs.columns)
  if intermediate:
+ if self.inplace:
+ raise RuntimeError( # pragma: no cover
+ "inplace must be False if intermediate is True, a container "
+ "might be used by several nodes.")
  return self._run(inputs, clean_right_away=False,
  intermediate=intermediate,
  verbose=verbose, node_time=node_time,

mlprodict/onnxrt/ops_cpu/op_string_normalizer.py

@@ -61,7 +61,11 @@ def _run_column(self, cin, cout):
  cout[:] = cin[:]
 
  for i in range(0, cin.shape[0]):
- cout[i] = self.strip_accents_unicode(cout[i])
+ if isinstance(cout[i], float):
+ # nan
+ cout[i] = ''
+ else:
+ cout[i] = self.strip_accents_unicode(cout[i])
 
  if self.is_case_sensitive and len(stops) > 0:
  for i in range(0, cin.shape[0]):