Remove legacy Python API (#17674)

src/bindings/python/src/compatibility/openvino/inference_engine/ie_api.pyx

@@ -535,7 +535,7 @@ cdef class IECore:
         
             ie = IECore()
             net = ie.read_network(model=path_to_xml_file, weights=path_to_bin_file)
-            ie.set_config(config={"DYN_BATCH_ENABLED": "YES"}, device_name="CPU")
+            ie.set_config(config={"PERF_COUNT": "YES"}, device_name="CPU")
         """
         cdef map[string, string] c_config = dict_to_c_map(config)
         self.impl.setConfig(c_config, device_name.encode())
@@ -1403,7 +1403,7 @@ cdef class InferRequest:
             mem_state_vec.append(state)
         return mem_state_vec
 
-    def set_blob(self, blob_name : str, blob : Blob, preprocess_info: PreProcessInfo = None):
+    def set_blob(self, blob_name : str, blob : Blob):
         """Sets user defined Blob for the infer request
         
         :param blob_name: A name of input blob
@@ -1423,10 +1423,7 @@ cdef class InferRequest:
             blob = Blob(td, blob_data)
             exec_net.requests[0].set_blob(blob_name="input_blob_name", blob=blob),
         """
-        if preprocess_info:
-            deref(self.impl).setBlob(blob_name.encode(), blob._ptr, deref(preprocess_info._ptr))
-        else:
-            deref(self.impl).setBlob(blob_name.encode(), blob._ptr)
+        deref(self.impl).setBlob(blob_name.encode(), blob._ptr)
         self._user_blobs[blob_name] = blob
 
     cpdef infer(self, inputs=None):

src/bindings/python/src/compatibility/openvino/inference_engine/ie_api_impl.cpp

@@ -363,12 +363,6 @@ void InferenceEnginePython::InferRequestWrap::setBlob(const std::string& blob_na
     request_ptr.SetBlob(blob_name.c_str(), blob_ptr);
 }
 
-void InferenceEnginePython::InferRequestWrap::setBlob(const std::string& blob_name,
-                                                      const InferenceEngine::Blob::Ptr& blob_ptr,
-                                                      const InferenceEngine::PreProcessInfo& info) {
-    request_ptr.SetBlob(blob_name.c_str(), blob_ptr, info);
-}
-
 const InferenceEngine::PreProcessInfo& InferenceEnginePython::InferRequestWrap::getPreProcess(
     const std::string& blob_name) {
     return request_ptr.GetPreProcess(blob_name.c_str());
@@ -378,10 +372,6 @@ InferenceEngine::Blob::Ptr InferenceEnginePython::InferRequestWrap::getBlobPtr(c
     return request_ptr.GetBlob(blob_name.c_str());
 }
 
-void InferenceEnginePython::InferRequestWrap::setBatch(int size) {
-    request_ptr.SetBatch(size);
-}
-
 std::vector<InferenceEnginePython::CVariableState> InferenceEnginePython::InferRequestWrap::queryState() {
     auto queryStateVec = request_ptr.QueryState();
     std::vector<InferenceEnginePython::CVariableState> memoryStates;

src/bindings/python/src/compatibility/openvino/inference_engine/ie_api_impl.hpp

@@ -115,12 +115,6 @@ struct InferRequestWrap {
 
     void setBlob(const std::string& blob_name, const InferenceEngine::Blob::Ptr& blob_ptr);
 
-    void setBlob(const std::string& name,
-                 const InferenceEngine::Blob::Ptr& data,
-                 const InferenceEngine::PreProcessInfo& info);
-
-    void setBatch(int size);
-
     const InferenceEngine::PreProcessInfo& getPreProcess(const std::string& blob_name);
 
     std::map<std::string, InferenceEnginePython::ProfileInfo> getPerformanceCounts();

src/bindings/python/tests_compatibility/test_inference_engine/test_InferRequest.py

@@ -401,23 +401,6 @@ def test_blob_setter(device):
     assert np.allclose(res_1, res_2, atol=1e-2, rtol=1e-2)
 
 
-def test_blob_setter_with_preprocess(device):
-    ie_core = ie.IECore()
-    net = ie_core.read_network(test_net_xml, test_net_bin)
-    exec_net = ie_core.load_network(network=net, device_name=device, num_requests=1)
-
-    img = generate_image()
-    tensor_desc = ie.TensorDesc("FP32", [1, 3, 32, 32], "NCHW")
-    img_blob = ie.Blob(tensor_desc, img)
-    preprocess_info = ie.PreProcessInfo()
-    preprocess_info.mean_variant = ie.MeanVariant.MEAN_IMAGE
-
-    request = exec_net.requests[0]
-    request.set_blob('data', img_blob, preprocess_info)
-    pp = request.preprocess_info["data"]
-    assert pp.mean_variant == ie.MeanVariant.MEAN_IMAGE
-
-
 def test_getting_preprocess(device):
     ie_core = ie.IECore()
     net = ie_core.read_network(test_net_xml, test_net_bin)