inline void run_inference()

in models/01_YoloV5/01_Pytorch/processing_cpp/include/dlrclient.hpp [93:120]

• 28 lines of code
• 8 McCabe index (conditional complexity)

        inline void run_inference(const std::vector<std::vector<float>>& input, std::vector<std::vector<float>>& output) {
            if (output.size() != 0 ) {
                throw std::runtime_error("You need to provide an empty output vector");
            } // if
            if (this->num_inputs != input.size()) {
                throw std::runtime_error("Invalid input elements. Expected: " + std::to_string(this->num_inputs) + " Received: " + std::to_string(input.size()));
            } // if
            for ( int i=0; i < this->num_inputs; ++i ) {
                const std::vector<int64_t>& shape = this->input_shapes[i];
            	if (SetDLRInput(handle, this->input_names[i].c_str(), shape.data(), input[i].data(), shape.size()) != 0) {
            		const char* err = DLRGetLastError();
            	 	throw std::runtime_error(err);
            	} // if
            } // for
        	if (RunDLRModel(handle) != 0) {
        		const char* err = DLRGetLastError();
        	 	throw std::runtime_error(err);
        	} // if
            for ( int i=0; i < this->num_outputs; ++i ) {
                std::vector<float> buf;
                output.push_back(buf);
                output[i].resize(this->output_sizes[i], 0);
            	if (GetDLROutput(handle, i, output[i].data()) != 0) {
            		const char* err = DLRGetLastError();
            	 	throw std::runtime_error(err);
            	} // if
            } // for
        }