mirror of https://git.ffmpeg.org/ffmpeg.git
lavfi/dnn_backend_tf: Return Specific Error Codes
Switch to returning specific error codes or DNN_GENERIC_ERROR when an error is encountered. For TensorFlow C API errors, currently DNN_GENERIC_ERROR is returned. Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit is contained in:
Shubhanshu Saxena
Guo Yejun
parent
91af38f2b3
commit
3fa89bd758
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@ -90,7 +90,7 @@ static const AVOption dnn_tensorflow_options[] = {
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AVFILTER_DEFINE_CLASS(dnn_tensorflow);
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static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queue);
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static int execute_model_tf(TFRequestItem *request, Queue *lltask_queue);
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static void infer_completion_callback(void *args);
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static inline void destroy_request_item(TFRequestItem **arg);
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@ -152,9 +152,10 @@ static TFInferRequest *tf_create_inference_request(void)
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*
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* @param request pointer to the TFRequestItem for inference
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* @retval DNN_SUCCESS if execution is successful
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* @retval DNN_ERROR if execution fails
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* @retval AVERROR(EINVAL) if request is NULL
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* @retval DNN_GENERIC_ERROR if execution fails
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*/
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static DNNReturnType tf_start_inference(void *args)
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static int tf_start_inference(void *args)
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{
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TFRequestItem *request = args;
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TFInferRequest *infer_request = request->infer_request;
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@ -164,7 +165,7 @@ static DNNReturnType tf_start_inference(void *args)
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if (!request) {
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av_log(&tf_model->ctx, AV_LOG_ERROR, "TFRequestItem is NULL\n");
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return DNN_ERROR;
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return AVERROR(EINVAL);
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}
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TF_SessionRun(tf_model->session, NULL,
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@ -178,7 +179,7 @@ static DNNReturnType tf_start_inference(void *args)
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if (ff_safe_queue_push_back(tf_model->request_queue, request) < 0) {
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destroy_request_item(&request);
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}
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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return DNN_SUCCESS;
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}
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@ -202,14 +203,14 @@ static inline void destroy_request_item(TFRequestItem **arg) {
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av_freep(arg);
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}
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static DNNReturnType extract_lltask_from_task(TaskItem *task, Queue *lltask_queue)
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static int extract_lltask_from_task(TaskItem *task, Queue *lltask_queue)
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{
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TFModel *tf_model = task->model;
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TFContext *ctx = &tf_model->ctx;
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LastLevelTaskItem *lltask = av_malloc(sizeof(*lltask));
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if (!lltask) {
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av_log(ctx, AV_LOG_ERROR, "Unable to allocate space for LastLevelTaskItem\n");
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return DNN_ERROR;
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return AVERROR(ENOMEM);
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}
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task->inference_todo = 1;
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task->inference_done = 0;
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@ -217,7 +218,7 @@ static DNNReturnType extract_lltask_from_task(TaskItem *task, Queue *lltask_queu
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if (ff_queue_push_back(lltask_queue, lltask) < 0) {
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av_log(ctx, AV_LOG_ERROR, "Failed to push back lltask_queue.\n");
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av_freep(&lltask);
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return DNN_ERROR;
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return AVERROR(ENOMEM);
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}
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return DNN_SUCCESS;
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}
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@ -277,7 +278,7 @@ static TF_Tensor *allocate_input_tensor(const DNNData *input)
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input_dims[1] * input_dims[2] * input_dims[3] * size);
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}
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static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input_name)
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static int get_input_tf(void *model, DNNData *input, const char *input_name)
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{
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TFModel *tf_model = model;
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TFContext *ctx = &tf_model->ctx;
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@ -288,7 +289,7 @@ static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input
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tf_output.oper = TF_GraphOperationByName(tf_model->graph, input_name);
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if (!tf_output.oper) {
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av_log(ctx, AV_LOG_ERROR, "Could not find \"%s\" in model\n", input_name);
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return DNN_ERROR;
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return AVERROR(EINVAL);
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}
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tf_output.index = 0;
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@ -300,7 +301,7 @@ static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input
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if (TF_GetCode(status) != TF_OK){
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TF_DeleteStatus(status);
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av_log(ctx, AV_LOG_ERROR, "Failed to get input tensor shape: number of dimension incorrect\n");
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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TF_DeleteStatus(status);
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@ -313,10 +314,10 @@ static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input
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return DNN_SUCCESS;
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}
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static DNNReturnType get_output_tf(void *model, const char *input_name, int input_width, int input_height,
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static int get_output_tf(void *model, const char *input_name, int input_width, int input_height,
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const char *output_name, int *output_width, int *output_height)
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{
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DNNReturnType ret;
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int ret;
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TFModel *tf_model = model;
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TFContext *ctx = &tf_model->ctx;
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TaskItem task;
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@ -329,20 +330,21 @@ static DNNReturnType get_output_tf(void *model, const char *input_name, int inpu
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.out_frame = NULL,
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};
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if (ff_dnn_fill_gettingoutput_task(&task, &exec_params, tf_model, input_height, input_width, ctx) != DNN_SUCCESS) {
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ret = ff_dnn_fill_gettingoutput_task(&task, &exec_params, tf_model, input_height, input_width, ctx);
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if (ret != DNN_SUCCESS) {
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goto err;
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}
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if (extract_lltask_from_task(&task, tf_model->lltask_queue) != DNN_SUCCESS) {
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ret = extract_lltask_from_task(&task, tf_model->lltask_queue);
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if (ret != DNN_SUCCESS) {
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av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
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ret = DNN_ERROR;
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goto err;
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}
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request = ff_safe_queue_pop_front(tf_model->request_queue);
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if (!request) {
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av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
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ret = DNN_ERROR;
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ret = AVERROR(EINVAL);
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goto err;
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}
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@ -386,7 +388,7 @@ static int hex_to_data(uint8_t *data, const char *p)
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return len;
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}
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static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename)
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static int load_tf_model(TFModel *tf_model, const char *model_filename)
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{
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TFContext *ctx = &tf_model->ctx;
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TF_Buffer *graph_def;
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@ -407,7 +409,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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*/
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if (strncmp(tf_model->ctx.options.sess_config, "0x", 2) != 0) {
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av_log(ctx, AV_LOG_ERROR, "sess_config should start with '0x'\n");
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return DNN_ERROR;
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return AVERROR(EINVAL);
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}
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config = tf_model->ctx.options.sess_config + 2;
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sess_config_length = hex_to_data(NULL, config);
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@ -415,11 +417,11 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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sess_config = av_mallocz(sess_config_length + AV_INPUT_BUFFER_PADDING_SIZE);
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if (!sess_config) {
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av_log(ctx, AV_LOG_ERROR, "failed to allocate memory\n");
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return DNN_ERROR;
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return AVERROR(ENOMEM);
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}
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if (hex_to_data(sess_config, config) < 0) {
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av_log(ctx, AV_LOG_ERROR, "failed to convert hex to data\n");
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return DNN_ERROR;
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return AVERROR(EINVAL);
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}
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}
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@ -427,7 +429,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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if (!graph_def){
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av_log(ctx, AV_LOG_ERROR, "Failed to read model \"%s\" graph\n", model_filename);
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av_freep(&sess_config);
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return DNN_ERROR;
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return AVERROR(EINVAL);
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}
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tf_model->graph = TF_NewGraph();
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tf_model->status = TF_NewStatus();
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@ -440,7 +442,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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TF_DeleteStatus(tf_model->status);
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av_log(ctx, AV_LOG_ERROR, "Failed to import serialized graph to model graph\n");
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av_freep(&sess_config);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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init_op = TF_GraphOperationByName(tf_model->graph, "init");
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@ -455,7 +457,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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TF_DeleteSessionOptions(sess_opts);
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av_log(ctx, AV_LOG_ERROR, "Failed to set config for sess options with %s\n",
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tf_model->ctx.options.sess_config);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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}
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@ -466,7 +468,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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TF_DeleteGraph(tf_model->graph);
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TF_DeleteStatus(tf_model->status);
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av_log(ctx, AV_LOG_ERROR, "Failed to create new session with model graph\n");
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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// Run initialization operation with name "init" if it is present in graph
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@ -481,7 +483,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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TF_DeleteGraph(tf_model->graph);
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TF_DeleteStatus(tf_model->status);
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av_log(ctx, AV_LOG_ERROR, "Failed to run session when initializing\n");
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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}
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@ -490,7 +492,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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#define NAME_BUFFER_SIZE 256
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static DNNReturnType add_conv_layer(TFModel *tf_model, TF_Operation *transpose_op, TF_Operation **cur_op,
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static int add_conv_layer(TFModel *tf_model, TF_Operation *transpose_op, TF_Operation **cur_op,
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ConvolutionalParams* params, const int layer)
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{
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TFContext *ctx = &tf_model->ctx;
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@ -594,7 +596,7 @@ static DNNReturnType add_conv_layer(TFModel *tf_model, TF_Operation *transpose_o
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break;
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default:
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avpriv_report_missing_feature(ctx, "convolutional activation function %d", params->activation);
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return DNN_ERROR;
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return AVERROR(ENOSYS);
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}
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input.oper = *cur_op;
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TF_AddInput(op_desc, input);
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@ -609,10 +611,10 @@ err:
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TF_DeleteTensor(kernel_tensor);
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TF_DeleteTensor(biases_tensor);
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av_log(ctx, AV_LOG_ERROR, "Failed to add conv layer %d\n", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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static DNNReturnType add_depth_to_space_layer(TFModel *tf_model, TF_Operation **cur_op,
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static int add_depth_to_space_layer(TFModel *tf_model, TF_Operation **cur_op,
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DepthToSpaceParams *params, const int layer)
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{
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TFContext *ctx = &tf_model->ctx;
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@ -630,13 +632,13 @@ static DNNReturnType add_depth_to_space_layer(TFModel *tf_model, TF_Operation **
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*cur_op = TF_FinishOperation(op_desc, tf_model->status);
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if (TF_GetCode(tf_model->status) != TF_OK){
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av_log(ctx, AV_LOG_ERROR, "Failed to add depth_to_space to layer %d\n", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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return DNN_SUCCESS;
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}
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static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
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static int add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
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LayerPadParams *params, const int layer)
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{
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TFContext *ctx = &tf_model->ctx;
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@ -666,13 +668,13 @@ static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
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if (TF_GetCode(tf_model->status) != TF_OK){
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TF_DeleteTensor(tensor);
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av_log(ctx, AV_LOG_ERROR, "Failed to set value for pad of layer %d\n", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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op = TF_FinishOperation(op_desc, tf_model->status);
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if (TF_GetCode(tf_model->status) != TF_OK){
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TF_DeleteTensor(tensor);
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av_log(ctx, AV_LOG_ERROR, "Failed to add pad to layer %d\n", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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op_desc = TF_NewOperation(tf_model->graph, "MirrorPad", "mirror_pad");
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@ -688,13 +690,13 @@ static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
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if (TF_GetCode(tf_model->status) != TF_OK){
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TF_DeleteTensor(tensor);
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av_log(ctx, AV_LOG_ERROR, "Failed to add mirror_pad to layer %d\n", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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return DNN_SUCCESS;
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}
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static DNNReturnType add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
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static int add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
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DnnLayerMaximumParams *params, const int layer)
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{
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TFContext *ctx = &tf_model->ctx;
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@ -716,13 +718,13 @@ static DNNReturnType add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
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if (TF_GetCode(tf_model->status) != TF_OK){
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TF_DeleteTensor(tensor);
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av_log(ctx, AV_LOG_ERROR, "Failed to set value for maximum/y of layer %d", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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op = TF_FinishOperation(op_desc, tf_model->status);
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if (TF_GetCode(tf_model->status) != TF_OK){
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TF_DeleteTensor(tensor);
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av_log(ctx, AV_LOG_ERROR, "Failed to add maximum/y to layer %d\n", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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snprintf(name_buffer, NAME_BUFFER_SIZE, "maximum%d", layer);
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@ -737,13 +739,13 @@ static DNNReturnType add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
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if (TF_GetCode(tf_model->status) != TF_OK){
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TF_DeleteTensor(tensor);
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av_log(ctx, AV_LOG_ERROR, "Failed to add maximum to layer %d\n", layer);
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return DNN_ERROR;
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return DNN_GENERIC_ERROR;
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}
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return DNN_SUCCESS;
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}
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static DNNReturnType load_native_model(TFModel *tf_model, const char *model_filename)
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static int load_native_model(TFModel *tf_model, const char *model_filename)
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{
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TFContext *ctx = &tf_model->ctx;
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int32_t layer;
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@ -755,14 +757,14 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
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int32_t *transpose_perm;
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int64_t transpose_perm_shape[] = {4};
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int64_t input_shape[] = {1, -1, -1, -1};
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DNNReturnType layer_add_res;
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int layer_add_res;
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DNNModel *model = NULL;
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NativeModel *native_model;
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model = ff_dnn_load_model_native(model_filename, DFT_PROCESS_FRAME, NULL, NULL);
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if (!model){
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av_log(ctx, AV_LOG_ERROR, "Failed to load native model\n");
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return DNN_ERROR;
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return AVERROR(EINVAL);
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}
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native_model = model->model;
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@ -775,7 +777,7 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
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TF_DeleteGraph(tf_model->graph); \
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TF_DeleteStatus(tf_model->status); \
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av_log(ctx, AV_LOG_ERROR, "Failed to set value or add operator to layer\n"); \
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return DNN_ERROR; \
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return DNN_GENERIC_ERROR; \
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}
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op_desc = TF_NewOperation(tf_model->graph, "Placeholder", "x");
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@ -942,19 +944,21 @@ err:
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return NULL;
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}
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static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *request) {
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static int fill_model_input_tf(TFModel *tf_model, TFRequestItem *request) {
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DNNData input;
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LastLevelTaskItem *lltask;
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TaskItem *task;
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TFInferRequest *infer_request;
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TFContext *ctx = &tf_model->ctx;
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int ret = 0;
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lltask = ff_queue_pop_front(tf_model->lltask_queue);
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av_assert0(lltask);
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task = lltask->task;
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request->lltask = lltask;
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if (get_input_tf(tf_model, &input, task->input_name) != DNN_SUCCESS) {
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ret = get_input_tf(tf_model, &input, task->input_name);
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if (ret != DNN_SUCCESS) {
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goto err;
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}
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@ -965,12 +969,14 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
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infer_request->tf_input = av_malloc(sizeof(TF_Output));
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if (!infer_request->tf_input) {
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av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input tensor\n");
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ret = AVERROR(ENOMEM);
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goto err;
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}
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infer_request->tf_input->oper = TF_GraphOperationByName(tf_model->graph, task->input_name);
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if (!infer_request->tf_input->oper){
|
||||
av_log(ctx, AV_LOG_ERROR, "Could not find \"%s\" in model\n", task->input_name);
|
||||
ret = DNN_GENERIC_ERROR;
|
||||
goto err;
|
||||
}
|
||||
infer_request->tf_input->index = 0;
|
||||
|
|
@ -978,6 +984,7 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
|
|||
infer_request->input_tensor = allocate_input_tensor(&input);
|
||||
if (!infer_request->input_tensor){
|
||||
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input tensor\n");
|
||||
ret = AVERROR(ENOMEM);
|
||||
goto err;
|
||||
}
|
||||
input.data = (float *)TF_TensorData(infer_request->input_tensor);
|
||||
|
|
@ -1003,12 +1010,14 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
|
|||
infer_request->tf_outputs = av_malloc_array(task->nb_output, sizeof(TF_Output));
|
||||
if (infer_request->tf_outputs == NULL) {
|
||||
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for *tf_outputs\n");
|
||||
ret = AVERROR(ENOMEM);
|
||||
goto err;
|
||||
}
|
||||
|
||||
infer_request->output_tensors = av_calloc(task->nb_output, sizeof(*infer_request->output_tensors));
|
||||
if (!infer_request->output_tensors) {
|
||||
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for output tensor\n");
|
||||
ret = AVERROR(ENOMEM);
|
||||
goto err;
|
||||
}
|
||||
|
||||
|
|
@ -1017,6 +1026,7 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
|
|||
infer_request->tf_outputs[i].oper = TF_GraphOperationByName(tf_model->graph, task->output_names[i]);
|
||||
if (!infer_request->tf_outputs[i].oper) {
|
||||
av_log(ctx, AV_LOG_ERROR, "Could not find output \"%s\" in model\n", task->output_names[i]);
|
||||
ret = DNN_GENERIC_ERROR;
|
||||
goto err;
|
||||
}
|
||||
infer_request->tf_outputs[i].index = 0;
|
||||
|
|
@ -1025,7 +1035,7 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
|
|||
return DNN_SUCCESS;
|
||||
err:
|
||||
tf_free_request(infer_request);
|
||||
return DNN_ERROR;
|
||||
return ret;
|
||||
}
|
||||
|
||||
static void infer_completion_callback(void *args) {
|
||||
|
|
@ -1086,12 +1096,13 @@ err:
|
|||
}
|
||||
}
|
||||
|
||||
static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queue)
|
||||
static int execute_model_tf(TFRequestItem *request, Queue *lltask_queue)
|
||||
{
|
||||
TFModel *tf_model;
|
||||
TFContext *ctx;
|
||||
LastLevelTaskItem *lltask;
|
||||
TaskItem *task;
|
||||
int ret = 0;
|
||||
|
||||
if (ff_queue_size(lltask_queue) == 0) {
|
||||
destroy_request_item(&request);
|
||||
|
|
@ -1103,7 +1114,8 @@ static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queu
|
|||
tf_model = task->model;
|
||||
ctx = &tf_model->ctx;
|
||||
|
||||
if (fill_model_input_tf(tf_model, request) != DNN_SUCCESS) {
|
||||
ret = fill_model_input_tf(tf_model, request);
|
||||
if (ret != DNN_SUCCESS) {
|
||||
goto err;
|
||||
}
|
||||
|
||||
|
|
@ -1112,58 +1124,64 @@ static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queu
|
|||
goto err;
|
||||
}
|
||||
return DNN_SUCCESS;
|
||||
} else {
|
||||
if (tf_start_inference(request) != DNN_SUCCESS) {
|
||||
}
|
||||
else {
|
||||
ret = tf_start_inference(request);
|
||||
if (ret != DNN_SUCCESS) {
|
||||
goto err;
|
||||
}
|
||||
infer_completion_callback(request);
|
||||
return (task->inference_done == task->inference_todo) ? DNN_SUCCESS : DNN_ERROR;
|
||||
return (task->inference_done == task->inference_todo) ? DNN_SUCCESS : DNN_GENERIC_ERROR;
|
||||
}
|
||||
err:
|
||||
tf_free_request(request->infer_request);
|
||||
if (ff_safe_queue_push_back(tf_model->request_queue, request) < 0) {
|
||||
destroy_request_item(&request);
|
||||
}
|
||||
return DNN_ERROR;
|
||||
return ret;
|
||||
}
|
||||
|
||||
DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params)
|
||||
int ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params)
|
||||
{
|
||||
TFModel *tf_model = model->model;
|
||||
TFContext *ctx = &tf_model->ctx;
|
||||
TaskItem *task;
|
||||
TFRequestItem *request;
|
||||
int ret = 0;
|
||||
|
||||
if (ff_check_exec_params(ctx, DNN_TF, model->func_type, exec_params) != 0) {
|
||||
return DNN_ERROR;
|
||||
ret = ff_check_exec_params(ctx, DNN_TF, model->func_type, exec_params);
|
||||
if (ret != 0) {
|
||||
return ret;
|
||||
}
|
||||
|
||||
task = av_malloc(sizeof(*task));
|
||||
if (!task) {
|
||||
av_log(ctx, AV_LOG_ERROR, "unable to alloc memory for task item.\n");
|
||||
return DNN_ERROR;
|
||||
return AVERROR(ENOMEM);
|
||||
}
|
||||
|
||||
if (ff_dnn_fill_task(task, exec_params, tf_model, ctx->options.async, 1) != DNN_SUCCESS) {
|
||||
ret = ff_dnn_fill_task(task, exec_params, tf_model, ctx->options.async, 1);
|
||||
if (ret != DNN_SUCCESS) {
|
||||
av_freep(&task);
|
||||
return DNN_ERROR;
|
||||
return ret;
|
||||
}
|
||||
|
||||
if (ff_queue_push_back(tf_model->task_queue, task) < 0) {
|
||||
av_freep(&task);
|
||||
av_log(ctx, AV_LOG_ERROR, "unable to push back task_queue.\n");
|
||||
return DNN_ERROR;
|
||||
return AVERROR(ENOMEM);
|
||||
}
|
||||
|
||||
if (extract_lltask_from_task(task, tf_model->lltask_queue) != DNN_SUCCESS) {
|
||||
ret = extract_lltask_from_task(task, tf_model->lltask_queue);
|
||||
if (ret != DNN_SUCCESS) {
|
||||
av_log(ctx, AV_LOG_ERROR, "unable to extract last level task from task.\n");
|
||||
return DNN_ERROR;
|
||||
return ret;
|
||||
}
|
||||
|
||||
request = ff_safe_queue_pop_front(tf_model->request_queue);
|
||||
if (!request) {
|
||||
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
|
||||
return DNN_ERROR;
|
||||
return AVERROR(EINVAL);
|
||||
}
|
||||
return execute_model_tf(request, tf_model->lltask_queue);
|
||||
}
|
||||
|
|
@ -1174,12 +1192,12 @@ DNNAsyncStatusType ff_dnn_get_result_tf(const DNNModel *model, AVFrame **in, AVF
|
|||
return ff_dnn_get_result_common(tf_model->task_queue, in, out);
|
||||
}
|
||||
|
||||
DNNReturnType ff_dnn_flush_tf(const DNNModel *model)
|
||||
int ff_dnn_flush_tf(const DNNModel *model)
|
||||
{
|
||||
TFModel *tf_model = model->model;
|
||||
TFContext *ctx = &tf_model->ctx;
|
||||
TFRequestItem *request;
|
||||
DNNReturnType ret;
|
||||
int ret;
|
||||
|
||||
if (ff_queue_size(tf_model->lltask_queue) == 0) {
|
||||
// no pending task need to flush
|
||||
|
|
@ -1189,7 +1207,7 @@ DNNReturnType ff_dnn_flush_tf(const DNNModel *model)
|
|||
request = ff_safe_queue_pop_front(tf_model->request_queue);
|
||||
if (!request) {
|
||||
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
|
||||
return DNN_ERROR;
|
||||
return AVERROR(EINVAL);
|
||||
}
|
||||
|
||||
ret = fill_model_input_tf(tf_model, request);
|
||||
|
|
|
|||
|
|
@ -31,9 +31,9 @@
|
|||
|
||||
DNNModel *ff_dnn_load_model_tf(const char *model_filename, DNNFunctionType func_type, const char *options, AVFilterContext *filter_ctx);
|
||||
|
||||
DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params);
|
||||
int ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params);
|
||||
DNNAsyncStatusType ff_dnn_get_result_tf(const DNNModel *model, AVFrame **in, AVFrame **out);
|
||||
DNNReturnType ff_dnn_flush_tf(const DNNModel *model);
|
||||
int ff_dnn_flush_tf(const DNNModel *model);
|
||||
|
||||
void ff_dnn_free_model_tf(DNNModel **model);
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue