samples: hide -we_gen and remove -l options for C++ speech (#5840)

* samples: hide and remove options for C++ speech

* sample: revert -we option

inference-engine/samples/speech_sample/README.md

@@ -10,7 +10,6 @@ Automatic Speech Recognition C++ sample application demonstrates how to use the
 |:---     |:--- |:---
 |Inference Engine Version| `InferenceEngine::GetInferenceEngineVersion` | Get Inference Engine API version
 |Available Devices|`InferenceEngine::Core::GetAvailableDevices`| Get version information of the devices for inference
-|Custom Extension Kernels|`InferenceEngine::Core::AddExtension`| Load extension library to the device plugin
 | Network Operations | `InferenceEngine::CNNNetwork::setBatchSize`, `InferenceEngine::CNNNetwork::getBatchSize` |  Managing of network, operate with its batch size.
 |Network Operations|`InferenceEngine::CNNNetwork::addOutput`| Change names of output layers in the network
 |Import Network|`InferenceEngine::ExecutableNetwork::Export`,`InferenceEngine::Core::ImportNetwork`| Creates an executable network from a previously exported network
@@ -72,8 +71,7 @@ Several execution modes are supported via the `-d` flag:
 
 #### Loading and Saving Models
 
-The GNA plugin supports loading and saving of the GNA-optimized model (non-IR) via the `-rg` and `-wg` flags.  Thereby, it is possible to avoid the cost of full model quantization at run time. The GNA plugin also
-supports export of firmware-compatible embedded model images for the Intel® Speech Enabling Developer Kit and Amazon Alexa* Premium Far-Field Voice Development Kit via the `-we` flag (save only).
+The GNA plugin supports loading and saving of the GNA-optimized model (non-IR) via the `-rg` and `-wg` flags.  Thereby, it is possible to avoid the cost of full model quantization at run time. The GNA plugin also supports export of firmware-compatible embedded model images for the Intel® Speech Enabling Developer Kit and Amazon Alexa* Premium Far-Field Voice Development Kit via the `-we` flag (save only).
 
 In addition to performing inference directly from a GNA model file, these options make it possible to:
 
@@ -104,7 +102,6 @@ Options:
     -i "<path>"             Required. Paths to .ark files. Example of usage: <file1.ark,file2.ark> or <file.ark>.
     -m "<path>"             Required. Path to an .xml file with a trained model (required if -rg is missing).
     -o "<path>"             Optional. Output file name to save ark scores.
-    -l "<absolute_path>"    Required for CPU custom layers. Absolute path to a shared library with the kernel implementations.
     -d "<device>"           Optional. Specify a target device to infer on. CPU, GPU, MYRIAD, GNA_AUTO, GNA_HW, GNA_SW_FP32, GNA_SW_EXACT and HETERO with combination of GNA
      as the primary device and CPU as a secondary (e.g. HETERO:GNA,CPU) are supported. The list of available devices is shown below. The sample will look for a suitable plugin for device specified.
     -pc                     Optional. Enables per-layer performance report.
@@ -160,7 +157,7 @@ Once the IR is created, you can use the following command to do inference on Int
 ```
 
 Here, the floating point Kaldi-generated reference neural network scores (`dev93_scores_10.ark`) corresponding to the input feature file (`dev93_10.ark`) are assumed to be available
-for comparison. 
+for comparison.
 
 All of them can be downloaded from [https://storage.openvinotoolkit.org/models_contrib/speech/2021.2/wsj_dnn5b_smbr](https://storage.openvinotoolkit.org/models_contrib/speech/2021.2/wsj_dnn5b_smbr). Inference Engine Intermediate Representation `wsj_dnn5b.xml` file was generated in the previous [Model Preparation](#model-preparation) section.
 

inference-engine/samples/speech_sample/main.cpp

@@ -663,13 +663,6 @@ int main(int argc, char* argv[]) {
         CNNNetwork network;
         ExecutableNetwork executableNet;
 
-        if (!FLAGS_l.empty()) {
-            // Custom CPU extension is loaded as a shared library and passed as a pointer to base extension
-            IExtensionPtr extension_ptr = std::make_shared<Extension>(FLAGS_l);
-            ie.AddExtension(extension_ptr);
-            slog::info << "Custom Extension loaded: " << FLAGS_l << slog::endl;
-        }
-
         // ------------------------------ Get Available Devices ------------------------------------------------------
         auto isFeature = [&](const std::string xFeature) {
             return FLAGS_d.find(xFeature) != std::string::npos;

inference-engine/samples/speech_sample/speech_sample.hpp

@@ -132,10 +132,6 @@ DEFINE_string(compile_target, "", compile_target_message);
 /// \brief Enable per-layer performance report
 DEFINE_bool(pc, false, performance_counter_message);
 
-/// @brief Absolute path to CPU library with user layers <br>
-/// It is an optional parameter
-DEFINE_string(l, "", custom_cpu_library_message);
-
 /// @brief Write output file to save ark scores
 DEFINE_string(o, "", output_message);
 
@@ -151,7 +147,7 @@ DEFINE_string(wg, "", write_gna_model_message);
 /// @brief Write GNA embedded model to file (model.bin)
 DEFINE_string(we, "", write_embedded_model_message);
 
-/// @brief Optional GNA embedded device generation (default GNA1 aka Sue Creek)
+/// @brief Optional GNA embedded device generation (default GNA1 aka Sue Creek) - hide option
 DEFINE_string(we_gen, "GNA1", write_embedded_model_generation_message);
 
 /// @brief Input quantization mode (default static)
@@ -196,7 +192,6 @@ static void showUsage() {
     std::cout << "    -i \"<path>\"             " << input_message << std::endl;
     std::cout << "    -m \"<path>\"             " << model_message << std::endl;
     std::cout << "    -o \"<path>\"             " << output_message << std::endl;
-    std::cout << "    -l \"<absolute_path>\"    " << custom_cpu_library_message << std::endl;
     std::cout << "    -d \"<device>\"           " << target_device_message << std::endl;
     std::cout << "    -pc                     " << performance_counter_message << std::endl;
     std::cout << "    -q \"<mode>\"             " << quantization_message << std::endl;
@@ -207,7 +202,6 @@ static void showUsage() {
     std::cout << "    -rg \"<path>\"            " << read_gna_model_message << std::endl;
     std::cout << "    -wg \"<path>\"            " << write_gna_model_message << std::endl;
     std::cout << "    -we \"<path>\"            " << write_embedded_model_message << std::endl;
-    std::cout << "    -we_gen \"<generation>\"  " << write_embedded_model_generation_message << std::endl;
     std::cout << "    -nthreads \"<integer>\"   " << infer_num_threads_message << std::endl;
     std::cout << "    -cw_l \"<integer>\"       " << context_window_message_l << std::endl;
     std::cout << "    -cw_r \"<integer>\"       " << context_window_message_r << std::endl;