[PYTHON API] infer helper (#9478)

* inputs as list in infer

* fix import

* fix import 2

* refactor test

src/bindings/python/src/openvino/runtime/ie_api.py

@@ -22,21 +22,23 @@ def tensor_from_file(path: str) -> Tensor:
     return Tensor(np.fromfile(path, dtype=np.uint8))
 
 
-def normalize_inputs(py_dict: dict, py_types: dict) -> dict:
+def normalize_inputs(inputs: Union[dict, list], py_types: dict) -> dict:
     """Normalize a dictionary of inputs to Tensors."""
-    for k, val in py_dict.items():
+    if isinstance(inputs, list):
+        inputs = {index: input for index, input in enumerate(inputs)}
+    for k, val in inputs.items():
         if not isinstance(k, (str, int)):
             raise TypeError("Incompatible key type for tensor named: {}".format(k))
         try:
             ov_type = py_types[k]
         except KeyError:
             raise KeyError("Port for tensor named {} was not found!".format(k))
-        py_dict[k] = (
+        inputs[k] = (
             val
             if isinstance(val, Tensor)
             else Tensor(np.array(val, get_dtype(ov_type)))
         )
-    return py_dict
+    return inputs
 
 
 def get_input_types(obj: Union[InferRequestBase, CompiledModelBase]) -> dict:
@@ -55,14 +57,14 @@ def get_input_types(obj: Union[InferRequestBase, CompiledModelBase]) -> dict:
 class InferRequest(InferRequestBase):
     """InferRequest wrapper."""
 
-    def infer(self, inputs: dict = None) -> dict:
+    def infer(self, inputs: Union[dict, list] = None) -> dict:
         """Infer wrapper for InferRequest."""
         inputs = (
             {} if inputs is None else normalize_inputs(inputs, get_input_types(self))
         )
         return super().infer(inputs)
 
-    def start_async(self, inputs: dict = None, userdata: Any = None) -> None:
+    def start_async(self, inputs: Union[dict, list] = None, userdata: Any = None) -> None:
         """Asynchronous infer wrapper for InferRequest."""
         inputs = (
             {} if inputs is None else normalize_inputs(inputs, get_input_types(self))
@@ -77,7 +79,7 @@ class CompiledModel(CompiledModelBase):
         """Create new InferRequest object."""
         return InferRequest(super().create_infer_request())
 
-    def infer_new_request(self, inputs: dict = None) -> dict:
+    def infer_new_request(self, inputs: Union[dict, list] = None) -> dict:
         """Infer wrapper for CompiledModel."""
         inputs = (
             {} if inputs is None else normalize_inputs(inputs, get_input_types(self))
@@ -92,7 +94,7 @@ class AsyncInferQueue(AsyncInferQueueBase):
         """Return i-th InferRequest from AsyncInferQueue."""
         return InferRequest(super().__getitem__(i))
 
-    def start_async(self, inputs: dict = None, userdata: Any = None) -> None:
+    def start_async(self, inputs: Union[dict, list] = None, userdata: Any = None) -> None:
         """Asynchronous infer wrapper for AsyncInferQueue."""
         inputs = (
             {}

src/bindings/python/tests/test_inference_engine/test_infer_request.py

@@ -175,6 +175,30 @@ def test_start_async(device):
     assert callbacks_info["finished"] == jobs
 
 
+def test_infer_list_as_inputs(device):
+    num_inputs = 4
+    input_shape = [2, 1]
+    dtype = np.float32
+    params = [ops.parameter(input_shape, dtype) for _ in range(num_inputs)]
+    model = Model(ops.relu(ops.concat(params, 1)), params)
+    core = Core()
+    compiled_model = core.compile_model(model, device)
+
+    def check_fill_inputs(request, inputs):
+        for input_idx in range(len(inputs)):
+            assert np.array_equal(request.get_input_tensor(input_idx).data, inputs[input_idx])
+
+    request = compiled_model.create_infer_request()
+
+    inputs = [np.random.normal(size=input_shape).astype(dtype)]
+    request.infer(inputs)
+    check_fill_inputs(request, inputs)
+
+    inputs = [np.random.normal(size=input_shape).astype(dtype) for _ in range(num_inputs)]
+    request.infer(inputs)
+    check_fill_inputs(request, inputs)
+
+
 def test_infer_mixed_keys(device):
     core = Core()
     func = core.read_model(test_net_xml, test_net_bin)