diff --git a/libavfilter/dnn/dnn_backend_tf.c b/libavfilter/dnn/dnn_backend_tf.c
index 7923e1db69..76cc037b94 100644
--- a/libavfilter/dnn/dnn_backend_tf.c
+++ b/libavfilter/dnn/dnn_backend_tf.c
@@ -29,14 +29,20 @@
 #include "dnn_backend_native_layer_depth2space.h"
 #include "libavformat/avio.h"
 #include "libavutil/avassert.h"
+#include "../internal.h"
 #include "dnn_backend_native_layer_pad.h"
 #include "dnn_backend_native_layer_maximum.h"
 #include "dnn_io_proc.h"
 
 #include <tensorflow/c/c_api.h>
 
+typedef struct TFOptions{
+    char *sess_config;
+} TFOptions;
+
 typedef struct TFContext {
     const AVClass *class;
+    TFOptions options;
 } TFContext;
 
 typedef struct TFModel{
@@ -47,14 +53,15 @@ typedef struct TFModel{
     TF_Status *status;
 } TFModel;
 
-static const AVClass dnn_tensorflow_class = {
-    .class_name = "dnn_tensorflow",
-    .item_name  = av_default_item_name,
-    .option     = NULL,
-    .version    = LIBAVUTIL_VERSION_INT,
-    .category   = AV_CLASS_CATEGORY_FILTER,
+#define OFFSET(x) offsetof(TFContext, x)
+#define FLAGS AV_OPT_FLAG_FILTERING_PARAM
+static const AVOption dnn_tensorflow_options[] = {
+    { "sess_config", "config for SessionOptions", OFFSET(options.sess_config), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS },
+    { NULL }
 };
 
+AVFILTER_DEFINE_CLASS(dnn_tensorflow);
+
 static DNNReturnType execute_model_tf(const DNNModel *model, const char *input_name, AVFrame *in_frame,
                                       const char **output_names, uint32_t nb_output, AVFrame *out_frame,
                                       int do_ioproc);
@@ -194,10 +201,64 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
     TF_ImportGraphDefOptions *graph_opts;
     TF_SessionOptions *sess_opts;
     const TF_Operation *init_op;
+    uint8_t *sess_config = NULL;
+    int sess_config_length = 0;
+
+    // prepare the sess config data
+    if (tf_model->ctx.options.sess_config != NULL) {
+        /*
+        tf_model->ctx.options.sess_config is hex to present the serialized proto
+        required by TF_SetConfig below, so we need to first generate the serialized
+        proto in a python script, the following is a script example to generate
+        serialized proto which specifies one GPU, we can change the script to add
+        more options.
+
+        import tensorflow as tf
+        gpu_options = tf.GPUOptions(visible_device_list='0')
+        config = tf.ConfigProto(gpu_options=gpu_options)
+        s = config.SerializeToString()
+        b = ''.join("%02x" % int(ord(b)) for b in s[::-1])
+        print('0x%s' % b)
+
+        the script output looks like: 0xab...cd, and then pass 0xab...cd to sess_config.
+        */
+        char tmp[3];
+        tmp[2] = '\0';
+
+        if (strncmp(tf_model->ctx.options.sess_config, "0x", 2) != 0) {
+            av_log(ctx, AV_LOG_ERROR, "sess_config should start with '0x'\n");
+            return DNN_ERROR;
+        }
+
+        sess_config_length = strlen(tf_model->ctx.options.sess_config);
+        if (sess_config_length % 2 != 0) {
+            av_log(ctx, AV_LOG_ERROR, "the length of sess_config is not even (%s), "
+                                      "please re-generate the config.\n",
+                                      tf_model->ctx.options.sess_config);
+            return DNN_ERROR;
+        }
+
+        sess_config_length -= 2; //ignore the first '0x'
+        sess_config_length /= 2; //get the data length in byte
+
+        sess_config = av_malloc(sess_config_length);
+        if (!sess_config) {
+            av_log(ctx, AV_LOG_ERROR, "failed to allocate memory\n");
+            return DNN_ERROR;
+        }
+
+        for (int i = 0; i < sess_config_length; i++) {
+            int index = 2 + (sess_config_length - 1 - i) * 2;
+            tmp[0] = tf_model->ctx.options.sess_config[index];
+            tmp[1] = tf_model->ctx.options.sess_config[index + 1];
+            sess_config[i] = strtol(tmp, NULL, 16);
+        }
+    }
 
     graph_def = read_graph(model_filename);
     if (!graph_def){
         av_log(ctx, AV_LOG_ERROR, "Failed to read model \"%s\" graph\n", model_filename);
+        av_freep(&sess_config);
         return DNN_ERROR;
     }
     tf_model->graph = TF_NewGraph();
@@ -210,11 +271,23 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
         TF_DeleteGraph(tf_model->graph);
         TF_DeleteStatus(tf_model->status);
         av_log(ctx, AV_LOG_ERROR, "Failed to import serialized graph to model graph\n");
+        av_freep(&sess_config);
         return DNN_ERROR;
     }
 
     init_op = TF_GraphOperationByName(tf_model->graph, "init");
     sess_opts = TF_NewSessionOptions();
+
+    if (sess_config) {
+        TF_SetConfig(sess_opts, sess_config, sess_config_length,tf_model->status);
+        av_freep(&sess_config);
+        if (TF_GetCode(tf_model->status) != TF_OK) {
+            av_log(ctx, AV_LOG_ERROR, "Failed to set config for sess options with %s\n",
+                                      tf_model->ctx.options.sess_config);
+            return DNN_ERROR;
+        }
+    }
+
     tf_model->session = TF_NewSession(tf_model->graph, sess_opts, tf_model->status);
     TF_DeleteSessionOptions(sess_opts);
     if (TF_GetCode(tf_model->status) != TF_OK)
@@ -609,6 +682,15 @@ DNNModel *ff_dnn_load_model_tf(const char *model_filename, const char *options,
     tf_model->ctx.class = &dnn_tensorflow_class;
     tf_model->model = model;
 
+    //parse options
+    av_opt_set_defaults(&tf_model->ctx);
+    if (av_opt_set_from_string(&tf_model->ctx, options, NULL, "=", "&") < 0) {
+        av_log(&tf_model->ctx, AV_LOG_ERROR, "Failed to parse options \"%s\"\n", options);
+        av_freep(&tf_model);
+        av_freep(&model);
+        return NULL;
+    }
+
     if (load_tf_model(tf_model, model_filename) != DNN_SUCCESS){
         if (load_native_model(tf_model, model_filename) != DNN_SUCCESS){
             av_freep(&tf_model);