diff --git a/libavfilter/dnn_backend_native.c b/libavfilter/dnn_backend_native.c
index 70d857f..fe43116 100644
--- a/libavfilter/dnn_backend_native.c
+++ b/libavfilter/dnn_backend_native.c
@@ -25,7 +25,7 @@
 
 #include "dnn_backend_native.h"
 
-static DNNReturnType set_input_output_native(void *model, DNNData *input, DNNData *output)
+static DNNReturnType set_input_output_native(void *model, DNNData *input, const char *input_name, DNNData *output, const char *output_name)
 {
     ConvolutionalNetwork *network = (ConvolutionalNetwork *)model;
     InputParams *input_params;
diff --git a/libavfilter/dnn_backend_tf.c b/libavfilter/dnn_backend_tf.c
index 9e0c127..a838907 100644
--- a/libavfilter/dnn_backend_tf.c
+++ b/libavfilter/dnn_backend_tf.c
@@ -76,7 +76,7 @@ static TF_Buffer *read_graph(const char *model_filename)
     return graph_buf;
 }
 
-static DNNReturnType set_input_output_tf(void *model, DNNData *input, DNNData *output)
+static DNNReturnType set_input_output_tf(void *model, DNNData *input, const char *input_name, DNNData *output, const char *output_name)
 {
     TFModel *tf_model = (TFModel *)model;
     int64_t input_dims[] = {1, input->height, input->width, input->channels};
@@ -84,8 +84,8 @@ static DNNReturnType set_input_output_tf(void *model, DNNData *input, DNNData *o
     const TF_Operation *init_op = TF_GraphOperationByName(tf_model->graph, "init");
     TF_Tensor *output_tensor;
 
-    // Input operation should be named 'x'
-    tf_model->input.oper = TF_GraphOperationByName(tf_model->graph, "x");
+    // Input operation
+    tf_model->input.oper = TF_GraphOperationByName(tf_model->graph, input_name);
     if (!tf_model->input.oper){
         return DNN_ERROR;
     }
@@ -100,8 +100,8 @@ static DNNReturnType set_input_output_tf(void *model, DNNData *input, DNNData *o
     }
     input->data = (float *)TF_TensorData(tf_model->input_tensor);
 
-    // Output operation should be named 'y'
-    tf_model->output.oper = TF_GraphOperationByName(tf_model->graph, "y");
+    // Output operation
+    tf_model->output.oper = TF_GraphOperationByName(tf_model->graph, output_name);
     if (!tf_model->output.oper){
         return DNN_ERROR;
     }
diff --git a/libavfilter/dnn_interface.h b/libavfilter/dnn_interface.h
index e367343..0390e39 100644
--- a/libavfilter/dnn_interface.h
+++ b/libavfilter/dnn_interface.h
@@ -40,7 +40,7 @@ typedef struct DNNModel{
     void *model;
     // Sets model input and output, while allocating additional memory for intermediate calculations.
     // Should be called at least once before model execution.
-    DNNReturnType (*set_input_output)(void *model, DNNData *input, DNNData *output);
+    DNNReturnType (*set_input_output)(void *model, DNNData *input, const char *input_name, DNNData *output, const char *output_name);
 } DNNModel;
 
 // Stores pointers to functions for loading, executing, freeing DNN models for one of the backends.
diff --git a/libavfilter/vf_sr.c b/libavfilter/vf_sr.c
index 9bb0fc5..085ac19 100644
--- a/libavfilter/vf_sr.c
+++ b/libavfilter/vf_sr.c
@@ -122,7 +122,7 @@ static int config_props(AVFilterLink *inlink)
     sr_context->input.height = inlink->h * sr_context->scale_factor;
     sr_context->input.channels = 1;
 
-    result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, &sr_context->output);
+    result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, "x", &sr_context->output, "y");
     if (result != DNN_SUCCESS){
         av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n");
         return AVERROR(EIO);
@@ -131,7 +131,7 @@ static int config_props(AVFilterLink *inlink)
     if (sr_context->input.height != sr_context->output.height || sr_context->input.width != sr_context->output.width){
         sr_context->input.width = inlink->w;
         sr_context->input.height = inlink->h;
-        result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, &sr_context->output);
+        result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, "x", &sr_context->output, "y");
         if (result != DNN_SUCCESS){
             av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n");
             return AVERROR(EIO);
