[IE PYTHON] optimize blob creation with numpy (#7813)

* Optimize blob constructor and remove user blobs

* restore user_blobs

* Rename helper function

* add test

* Remove empty line

* Fix code style

* add const

* Add test for SCALAR layout

inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx

@@ -206,10 +206,9 @@ cdef class Blob:
         elif tensor_desc is not None and self._array_data is not None:
             c_tensor_desc = tensor_desc.impl
             precision = tensor_desc.precision
-            size_arr = np.prod(array.shape)
-            size_td = np.prod(tensor_desc.dims)
-            if size_arr != size_td:
-                raise AttributeError(f"Number of elements in provided numpy array {size_arr} and "
+            size_td = C.product(c_tensor_desc.getDims())
+            if array.size != size_td:
+                raise AttributeError(f"Number of elements in provided numpy array {array.size} and "
                                      f"required by TensorDesc {size_td} are not equal")
             if self._array_data.dtype != format_map[precision]:
                 raise ValueError(f"Data type {self._array_data.dtype} of provided numpy array "

inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.cpp

@@ -682,3 +682,7 @@ InferenceEngine::Blob::Ptr InferenceEnginePython::CVariableState::getState() {
 void InferenceEnginePython::CVariableState::setState(InferenceEngine::Blob::Ptr state) {
     variableState.SetState(state);
 }
+
+const size_t InferenceEnginePython::product(const InferenceEngine::SizeVector& dims) {
+    return std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<size_t>{});
+}

inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.hpp

@@ -7,11 +7,13 @@
 #include <algorithm>
 #include <chrono>
 #include <condition_variable>
+#include <functional>
 #include <iostream>
 #include <iterator>
 #include <list>
 #include <map>
 #include <mutex>
+#include <numeric>
 #include <queue>
 #include <set>
 #include <sstream>
@@ -203,4 +205,6 @@ InferenceEnginePython::IENetwork read_network(std::string path_to_xml, std::stri
 
 PyObject* getPartialShape_capsule(InferenceEngine::CDataPtr data);
 
+const size_t product(const InferenceEngine::SizeVector& dims);
+
 };  // namespace InferenceEnginePython

inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl_defs.pxd

@@ -230,3 +230,5 @@ cdef extern from "ie_api_impl.hpp" namespace "InferenceEnginePython":
     cdef IENetwork read_network(string path_to_xml, string path_to_bin)
 
     cdef object getPartialShape_capsule(DataPtr)
+
+    cdef const size_t product(const SizeVector& dims)

inference-engine/ie_bridges/python/tests/test_Blob.py

@@ -21,11 +21,16 @@ def test_init_with_tensor_desc():
     assert blob.tensor_desc == tensor_desc
 
 
-def test_init_with_numpy():
-    tensor_desc = TensorDesc("FP32", [1, 3, 127, 127], "NCHW")
-    array = np.ones(shape=(1, 3, 127, 127), dtype=np.float32)
+@pytest.mark.parametrize("shape, layout", [
+    ([1, 3, 127, 127], "NCHW"),
+    ([], "SCALAR"),
+])
+def test_init_with_numpy(shape, layout):
+    tensor_desc = TensorDesc("FP32", shape, layout)
+    array = np.ones(shape=shape, dtype=np.float32)
     blob = Blob(tensor_desc, array)
     assert isinstance(blob.buffer, np.ndarray)
+    assert np.shares_memory(blob.buffer, array)
     assert blob.tensor_desc == tensor_desc