[FFmpeg-cvslog] lavfi/dnn: DNNAsyncExecModule Execution Failure Handling

[Shubhanshu Saxena]

ffmpeg | branch: master | Shubhanshu Saxena <shubhanshu.e01 at gmail.com> | Sun Aug  8 16:43:39 2021 +0530| [2063745a93f3a17ee14ffd01905878b8fdc17023] | committer: Guo Yejun

lavfi/dnn: DNNAsyncExecModule Execution Failure Handling

This commit adds the case handling if the asynchronous execution
of a request fails by checking the exit status of the thread when
joining before starting another execution. On failure, it does the
cleanup as well.

Signed-off-by: Shubhanshu Saxena <shubhanshu.e01 at gmail.com>

> http://git.videolan.org/gitweb.cgi/ffmpeg.git/?a=commit;h=2063745a93f3a17ee14ffd01905878b8fdc17023
---

 libavfilter/dnn/dnn_backend_common.c | 23 +++++++++++++++++++----
 libavfilter/dnn/dnn_backend_tf.c     | 10 +++++++++-
 2 files changed, 28 insertions(+), 5 deletions(-)

diff --git a/libavfilter/dnn/dnn_backend_common.c b/libavfilter/dnn/dnn_backend_common.c
index 470fffa2ae..426683b73d 100644
--- a/libavfilter/dnn/dnn_backend_common.c
+++ b/libavfilter/dnn/dnn_backend_common.c
@@ -23,6 +23,9 @@
 
 #include "dnn_backend_common.h"
 
+#define DNN_ASYNC_SUCCESS (void *)0
+#define DNN_ASYNC_FAIL (void *)-1
+
 int ff_check_exec_params(void *ctx, DNNBackendType backend, DNNFunctionType func_type, DNNExecBaseParams *exec_params)
 {
     if (!exec_params) {
@@ -79,18 +82,25 @@ static void *async_thread_routine(void *args)
     DNNAsyncExecModule *async_module = args;
     void *request = async_module->args;
 
-    async_module->start_inference(request);
+    if (async_module->start_inference(request) != DNN_SUCCESS) {
+        return DNN_ASYNC_FAIL;
+    }
     async_module->callback(request);
-    return NULL;
+    return DNN_ASYNC_SUCCESS;
 }
 
 DNNReturnType ff_dnn_async_module_cleanup(DNNAsyncExecModule *async_module)
 {
+    void *status = 0;
     if (!async_module) {
         return DNN_ERROR;
     }
 #if HAVE_PTHREAD_CANCEL
-    pthread_join(async_module->thread_id, NULL);
+    pthread_join(async_module->thread_id, &status);
+    if (status == DNN_ASYNC_FAIL) {
+        av_log(NULL, AV_LOG_ERROR, "Last Inference Failed.\n");
+        return DNN_ERROR;
+    }
 #endif
     async_module->start_inference = NULL;
     async_module->callback = NULL;
@@ -101,6 +111,7 @@ DNNReturnType ff_dnn_async_module_cleanup(DNNAsyncExecModule *async_module)
 DNNReturnType ff_dnn_start_inference_async(void *ctx, DNNAsyncExecModule *async_module)
 {
     int ret;
+    void *status = 0;
 
     if (!async_module) {
         av_log(ctx, AV_LOG_ERROR, "async_module is null when starting async inference.\n");
@@ -108,7 +119,11 @@ DNNReturnType ff_dnn_start_inference_async(void *ctx, DNNAsyncExecModule *async_
     }
 
 #if HAVE_PTHREAD_CANCEL
-    pthread_join(async_module->thread_id, NULL);
+    pthread_join(async_module->thread_id, &status);
+    if (status == DNN_ASYNC_FAIL) {
+        av_log(ctx, AV_LOG_ERROR, "Unable to start inference as previous inference failed.\n");
+        return DNN_ERROR;
+    }
     ret = pthread_create(&async_module->thread_id, NULL, async_thread_routine, async_module);
     if (ret != 0) {
         av_log(ctx, AV_LOG_ERROR, "Unable to start async inference.\n");
diff --git a/libavfilter/dnn/dnn_backend_tf.c b/libavfilter/dnn/dnn_backend_tf.c
index fb3f6f5ea6..ffec1b1328 100644
--- a/libavfilter/dnn/dnn_backend_tf.c
+++ b/libavfilter/dnn/dnn_backend_tf.c
@@ -91,6 +91,7 @@ AVFILTER_DEFINE_CLASS(dnn_tensorflow);
 
 static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *inference_queue);
 static void infer_completion_callback(void *args);
+static inline void destroy_request_item(TFRequestItem **arg);
 
 static void free_buffer(void *data, size_t length)
 {
@@ -172,6 +173,10 @@ static DNNReturnType tf_start_inference(void *args)
                   request->status);
     if (TF_GetCode(request->status) != TF_OK) {
         av_log(&tf_model->ctx, AV_LOG_ERROR, "%s", TF_Message(request->status));
+        tf_free_request(infer_request);
+        if (ff_safe_queue_push_back(tf_model->request_queue, request) < 0) {
+            destroy_request_item(&request);
+        }
         return DNN_ERROR;
     }
     return DNN_SUCCESS;
@@ -1095,7 +1100,10 @@ static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *inference_q
     }
 
     if (task->async) {
-        return ff_dnn_start_inference_async(ctx, &request->exec_module);
+        if (ff_dnn_start_inference_async(ctx, &request->exec_module) != DNN_SUCCESS) {
+            goto err;
+        }
+        return DNN_SUCCESS;
     } else {
         if (tf_start_inference(request) != DNN_SUCCESS) {
             goto err;