e25f20f7a3
commit 3f4938648950a7f3bf9a19c320ca9fae7c52de20 Author: sophgo-forum-service <forum_service@sophgo.com> Date: Mon May 13 13:44:23 2024 +0800 [feat] cviruntime opensource for cv18xx soc. - a4b6a3, add cumsum and gatherelements_pt.
115 lines
3.1 KiB
C++
115 lines
3.1 KiB
C++
#include <stdio.h>
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#include <math.h>
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#include <time.h>
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#include <stdlib.h>
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#include <string.h>
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#include <sys/time.h>
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#include <opencv2/opencv.hpp>
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#include "cviruntime.h"
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#include "cnpy.h"
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#include "vocoder_model.hpp"
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VocoderModel::VocoderModel(const char *model_file) {
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int ret = CVI_NN_RegisterModel(model_file, &model);
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if (ret != CVI_RC_SUCCESS) {
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printf("CVI_NN_RegisterModel failed, err %d\n", ret);
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exit(1);
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}
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CVI_NN_SetConfig(model, OPTION_BATCH_SIZE, 1);
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CVI_NN_SetConfig(model, OPTION_PROGRAM_INDEX, 5);
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ret = CVI_NN_GetInputOutputTensors(model, &input_tensors, &input_num,
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&output_tensors, &output_num);
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if (ret != CVI_RC_SUCCESS) {
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printf("CVI_NN_GetInputOutputTensors failed, err %d\n", ret);
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exit(1);
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}
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src = &input_tensors[0];
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output = &output_tensors[0];
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std::cout << "Encoder- tensors:" << src->name
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<< ", " << output->name << "\n";
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}
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VocoderModel::VocoderModel(CVI_MODEL_HANDLE main_model, int32_t pidx) {
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int ret = CVI_NN_CloneModel(main_model, &model);
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if (ret != CVI_RC_SUCCESS) {
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printf("CVI_NN_RegisterModel failed, err %d\n", ret);
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exit(1);
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}
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CVI_NN_SetConfig(model, OPTION_BATCH_SIZE, 1);
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CVI_NN_SetConfig(model, OPTION_PROGRAM_INDEX, pidx);
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ret = CVI_NN_GetInputOutputTensors(model, &input_tensors, &input_num,
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&output_tensors, &output_num);
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if (ret != CVI_RC_SUCCESS) {
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printf("CVI_NN_GetInputOutputTensors failed, err %d\n", ret);
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exit(1);
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}
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src = &input_tensors[0];
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output = &output_tensors[0];
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std::cout << "Encoder- tensors:" << src->name
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<< ", " << output->name << "\n";
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}
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float *VocoderModel::run(float *data, int32_t src_size, int32_t &out_size) {
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// fill src_seq to tensor 0
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assert(CVI_NN_TensorCount(src) == src_size);
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CVI_NN_SetTensorPtr(src, data);
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// memcpy(CVI_NN_TensorPtr(src), data, CVI_NN_TensorSize(src));
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// run inference
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CVI_NN_Forward(model, input_tensors, input_num,
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output_tensors, output_num);
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out_size = CVI_NN_TensorCount(output);
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return (float *)CVI_NN_TensorPtr(output);
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}
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Vocoder::Vocoder(const char *model_file) {
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vc_600 = new VocoderModel(model_file);
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assert(vc_600);
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vc_500 = new VocoderModel(vc_600->model, 4);
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assert(vc_500);
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vc_400 = new VocoderModel(vc_600->model, 3);
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assert(vc_400);
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vc_300 = new VocoderModel(vc_600->model, 2);
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assert(vc_300);
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vc_200 = new VocoderModel(vc_600->model, 1);
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assert(vc_200);
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vc_100 = new VocoderModel(vc_600->model, 0);
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assert(vc_100);
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}
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Vocoder::~Vocoder() {
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delete vc_100;
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delete vc_200;
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delete vc_300;
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delete vc_400;
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delete vc_500;
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delete vc_600;
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}
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float *Vocoder::run(float *data, int32_t src_size,
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int32_t &out_size) {
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VocoderModel *m;
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switch(src_size) {
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case 80 * 100:
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m = vc_100;
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break;
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case 80 * 200:
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m = vc_200;
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break;
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case 80 * 300:
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m = vc_300;
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break;
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case 80 * 400:
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m = vc_400;
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break;
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case 80 * 500:
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m = vc_500;
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break;
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case 80 * 600:
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m = vc_600;
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break;
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default:
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assert(0);
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}
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return m->run(data, src_size, out_size);
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}
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