lavfi/dnn_backend_tf: Add TF_Status to TFRequestItem

Since requests are running in parallel, there is inconsistency in
the status of the execution. To resolve it, we avoid using mutex
as it would result in single TF_Session running at a time. So add
TF_Status to the TFRequestItem

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

1 files changed, 6 insertions, 3 deletions

diff --git a/libavfilter/dnn/dnn_backend_tf.c b/libavfilter/dnn/dnn_backend_tf.c
index ad5f1e633e..935a2618a1 100644
--- a/libavfilter/dnn/dnn_backend_tf.c
+++ b/libavfilter/dnn/dnn_backend_tf.c
@@ -75,6 +75,7 @@ typedef struct TFInferRequest {
 typedef struct TFRequestItem {
     TFInferRequest *infer_request;
     InferenceItem *inference;
+    TF_Status *status;
     DNNAsyncExecModule exec_module;
 } TFRequestItem;
 
@@ -165,9 +166,9 @@ static DNNReturnType tf_start_inference(void *args)
                   infer_request->tf_input, &infer_request->input_tensor, 1,
                   infer_request->tf_outputs, infer_request->output_tensors,
                   task->nb_output, NULL, 0, NULL,
-                  tf_model->status);
-    if (TF_GetCode(tf_model->status) != TF_OK) {
-        av_log(&tf_model->ctx, AV_LOG_ERROR, "%s", TF_Message(tf_model->status));
+                  request->status);
+    if (TF_GetCode(request->status) != TF_OK) {
+        av_log(&tf_model->ctx, AV_LOG_ERROR, "%s", TF_Message(request->status));
         return DNN_ERROR;
     }
     return DNN_SUCCESS;
@@ -187,6 +188,7 @@ static inline void destroy_request_item(TFRequestItem **arg) {
     tf_free_request(request->infer_request);
     av_freep(&request->infer_request);
     av_freep(&request->inference);
+    TF_DeleteStatus(request->status);
     ff_dnn_async_module_cleanup(&request->exec_module);
     av_freep(arg);
 }
@@ -906,6 +908,7 @@ DNNModel *ff_dnn_load_model_tf(const char *model_filename, DNNFunctionType func_
             av_freep(&item);
             goto err;
         }
+        item->status = TF_NewStatus();
         item->exec_module.start_inference = &tf_start_inference;
         item->exec_module.callback = &infer_completion_callback;
         item->exec_module.args = item;