@@ -172,6 +172,24 @@ static DNNReturnType tf_start_inference(void *args)
return DNN_SUCCESS;
}
+/**
+ * Free the TFRequestItem completely.
+ *
+ * @param arg Address of the TFInferRequest instance.
+ */
+static inline void destroy_request_item(TFRequestItem **arg) {
+ TFRequestItem *request;
+ if (!arg) {
+ return;
+ }
+ request = *arg;
+ tf_free_request(request->infer_request);
+ av_freep(&request->infer_request);
+ av_freep(&request->inference);
+ ff_dnn_async_module_cleanup(&request->exec_module);
+ av_freep(arg);
+}
+
static DNNReturnType extract_inference_from_task(TaskItem *task, Queue *inference_queue)
{
TFModel *tf_model = task->model;
@@ -880,6 +898,7 @@ DNNModel *ff_dnn_load_model_tf(const char *model_filename, DNNFunctionType func_
if (!item) {
goto err;
}
+ item->inference = NULL;
item->infer_request = tf_create_inference_request();
if (!item->infer_request) {
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for TensorFlow inference request\n");
@@ -891,8 +910,7 @@ DNNModel *ff_dnn_load_model_tf(const char *model_filename, DNNFunctionType func_
item->exec_module.args = item;
if (ff_safe_queue_push_back(tf_model->request_queue, item) < 0) {
- av_freep(&item->infer_request);
- av_freep(&item);
+ destroy_request_item(&item);
goto err;
}
}
@@ -1059,8 +1077,7 @@ err:
av_freep(&outputs);
if (ff_safe_queue_push_back(tf_model->request_queue, request) < 0) {
- av_freep(&request->infer_request);
- av_freep(&request);
+ destroy_request_item(&request);
av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
}
}
@@ -1072,28 +1089,35 @@ static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *inference_q
InferenceItem *inference;
TaskItem *task;
- inference = ff_queue_peek_front(inference_queue);
- if (!inference) {
- av_log(NULL, AV_LOG_ERROR, "Failed to get inference item\n");
- return DNN_ERROR;
+ if (ff_queue_size(inference_queue) == 0) {
+ destroy_request_item(&request);
+ return DNN_SUCCESS;
}
+
+ inference = ff_queue_peek_front(inference_queue);
task = inference->task;
tf_model = task->model;
ctx = &tf_model->ctx;
if (fill_model_input_tf(tf_model, request) != DNN_SUCCESS) {
- return DNN_ERROR;
+ goto err;
}
if (task->async) {
return ff_dnn_start_inference_async(ctx, &request->exec_module);
} else {
if (tf_start_inference(request) != DNN_SUCCESS) {
- return DNN_ERROR;
+ goto err;
}
infer_completion_callback(request);
return (task->inference_done == task->inference_todo) ? DNN_SUCCESS : DNN_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;
}
DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params)
@@ -1193,8 +1217,7 @@ DNNReturnType ff_dnn_flush_tf(const DNNModel *model)
if (ret != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "Failed to fill model input.\n");
if (ff_safe_queue_push_back(tf_model->request_queue, request) < 0) {
- av_freep(&request->infer_request);
- av_freep(&request);
+ destroy_request_item(&request);
}
return ret;
}
@@ -1210,10 +1233,7 @@ void ff_dnn_free_model_tf(DNNModel **model)
tf_model = (*model)->model;
while (ff_safe_queue_size(tf_model->request_queue) != 0) {
TFRequestItem *item = ff_safe_queue_pop_front(tf_model->request_queue);
- ff_dnn_async_module_cleanup(&item->exec_module);
- tf_free_request(item->infer_request);
- av_freep(&item->infer_request);
- av_freep(&item);
+ destroy_request_item(&item);
}
ff_safe_queue_destroy(tf_model->request_queue);
This patch adds error handling for cases where the execute_model_tf fails, clears the used memory in the TFRequestItem and finally pushes it back to the request queue. Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com> --- libavfilter/dnn/dnn_backend_tf.c | 52 ++++++++++++++++++++++---------- 1 file changed, 36 insertions(+), 16 deletions(-)