[FFmpeg-devel] [PATCH V2 5/8] lavfi/dnn_backend_tf: Return Specific Error Codes
Shubhanshu Saxena
shubhanshu.e01 at gmail.com
Wed Mar 2 20:05:53 EET 2022
Switch to returning specific error codes or DNN_GENERIC_ERROR
when an error is encountered. For TensorFlow C API errors, currently
DNN_GENERIC_ERROR is returned.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01 at gmail.com>
---
libavfilter/dnn/dnn_backend_tf.c | 148 +++++++++++++++++--------------
libavfilter/dnn/dnn_backend_tf.h | 4 +-
2 files changed, 85 insertions(+), 67 deletions(-)
diff --git a/libavfilter/dnn/dnn_backend_tf.c b/libavfilter/dnn/dnn_backend_tf.c
index 7dd48fb612..cede1286c3 100644
--- a/libavfilter/dnn/dnn_backend_tf.c
+++ b/libavfilter/dnn/dnn_backend_tf.c
@@ -90,7 +90,7 @@ static const AVOption dnn_tensorflow_options[] = {
AVFILTER_DEFINE_CLASS(dnn_tensorflow);
-static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queue);
+static int execute_model_tf(TFRequestItem *request, Queue *lltask_queue);
static void infer_completion_callback(void *args);
static inline void destroy_request_item(TFRequestItem **arg);
@@ -152,9 +152,10 @@ static TFInferRequest *tf_create_inference_request(void)
*
* @param request pointer to the TFRequestItem for inference
* @retval DNN_SUCCESS if execution is successful
- * @retval DNN_ERROR if execution fails
+ * @retval AVERROR(EINVAL) if request is NULL
+ * @retval DNN_GENERIC_ERROR if execution fails
*/
-static DNNReturnType tf_start_inference(void *args)
+static int tf_start_inference(void *args)
{
TFRequestItem *request = args;
TFInferRequest *infer_request = request->infer_request;
@@ -164,7 +165,7 @@ static DNNReturnType tf_start_inference(void *args)
if (!request) {
av_log(&tf_model->ctx, AV_LOG_ERROR, "TFRequestItem is NULL\n");
- return DNN_ERROR;
+ return AVERROR(EINVAL);
}
TF_SessionRun(tf_model->session, NULL,
@@ -178,7 +179,7 @@ static DNNReturnType tf_start_inference(void *args)
if (ff_safe_queue_push_back(tf_model->request_queue, request) < 0) {
destroy_request_item(&request);
}
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
return DNN_SUCCESS;
}
@@ -202,14 +203,14 @@ static inline void destroy_request_item(TFRequestItem **arg) {
av_freep(arg);
}
-static DNNReturnType extract_lltask_from_task(TaskItem *task, Queue *lltask_queue)
+static int extract_lltask_from_task(TaskItem *task, Queue *lltask_queue)
{
TFModel *tf_model = task->model;
TFContext *ctx = &tf_model->ctx;
LastLevelTaskItem *lltask = av_malloc(sizeof(*lltask));
if (!lltask) {
av_log(ctx, AV_LOG_ERROR, "Unable to allocate space for LastLevelTaskItem\n");
- return DNN_ERROR;
+ return AVERROR(ENOMEM);
}
task->inference_todo = 1;
task->inference_done = 0;
@@ -217,7 +218,7 @@ static DNNReturnType extract_lltask_from_task(TaskItem *task, Queue *lltask_queu
if (ff_queue_push_back(lltask_queue, lltask) < 0) {
av_log(ctx, AV_LOG_ERROR, "Failed to push back lltask_queue.\n");
av_freep(&lltask);
- return DNN_ERROR;
+ return AVERROR(ENOMEM);
}
return DNN_SUCCESS;
}
@@ -277,7 +278,7 @@ static TF_Tensor *allocate_input_tensor(const DNNData *input)
input_dims[1] * input_dims[2] * input_dims[3] * size);
}
-static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input_name)
+static int get_input_tf(void *model, DNNData *input, const char *input_name)
{
TFModel *tf_model = model;
TFContext *ctx = &tf_model->ctx;
@@ -288,7 +289,7 @@ static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input
tf_output.oper = TF_GraphOperationByName(tf_model->graph, input_name);
if (!tf_output.oper) {
av_log(ctx, AV_LOG_ERROR, "Could not find \"%s\" in model\n", input_name);
- return DNN_ERROR;
+ return AVERROR(EINVAL);
}
tf_output.index = 0;
@@ -300,7 +301,7 @@ static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input
if (TF_GetCode(status) != TF_OK){
TF_DeleteStatus(status);
av_log(ctx, AV_LOG_ERROR, "Failed to get input tensor shape: number of dimension incorrect\n");
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
TF_DeleteStatus(status);
@@ -313,10 +314,10 @@ static DNNReturnType get_input_tf(void *model, DNNData *input, const char *input
return DNN_SUCCESS;
}
-static DNNReturnType get_output_tf(void *model, const char *input_name, int input_width, int input_height,
+static int get_output_tf(void *model, const char *input_name, int input_width, int input_height,
const char *output_name, int *output_width, int *output_height)
{
- DNNReturnType ret;
+ int ret;
TFModel *tf_model = model;
TFContext *ctx = &tf_model->ctx;
TaskItem task;
@@ -329,20 +330,21 @@ static DNNReturnType get_output_tf(void *model, const char *input_name, int inpu
.out_frame = NULL,
};
- if (ff_dnn_fill_gettingoutput_task(&task, &exec_params, tf_model, input_height, input_width, ctx) != DNN_SUCCESS) {
+ ret = ff_dnn_fill_gettingoutput_task(&task, &exec_params, tf_model, input_height, input_width, ctx);
+ if (ret != DNN_SUCCESS) {
goto err;
}
- if (extract_lltask_from_task(&task, tf_model->lltask_queue) != DNN_SUCCESS) {
+ ret = extract_lltask_from_task(&task, tf_model->lltask_queue);
+ if (ret != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
- ret = DNN_ERROR;
goto err;
}
request = ff_safe_queue_pop_front(tf_model->request_queue);
if (!request) {
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
- ret = DNN_ERROR;
+ ret = AVERROR(EINVAL);
goto err;
}
@@ -386,7 +388,7 @@ static int hex_to_data(uint8_t *data, const char *p)
return len;
}
-static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename)
+static int load_tf_model(TFModel *tf_model, const char *model_filename)
{
TFContext *ctx = &tf_model->ctx;
TF_Buffer *graph_def;
@@ -407,7 +409,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
*/
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;
+ return AVERROR(EINVAL);
}
config = tf_model->ctx.options.sess_config + 2;
sess_config_length = hex_to_data(NULL, config);
@@ -415,11 +417,11 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
sess_config = av_mallocz(sess_config_length + AV_INPUT_BUFFER_PADDING_SIZE);
if (!sess_config) {
av_log(ctx, AV_LOG_ERROR, "failed to allocate memory\n");
- return DNN_ERROR;
+ return AVERROR(ENOMEM);
}
if (hex_to_data(sess_config, config) < 0) {
av_log(ctx, AV_LOG_ERROR, "failed to convert hex to data\n");
- return DNN_ERROR;
+ return AVERROR(EINVAL);
}
}
@@ -427,7 +429,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *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;
+ return AVERROR(EINVAL);
}
tf_model->graph = TF_NewGraph();
tf_model->status = TF_NewStatus();
@@ -440,7 +442,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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;
+ return DNN_GENERIC_ERROR;
}
init_op = TF_GraphOperationByName(tf_model->graph, "init");
@@ -455,7 +457,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
TF_DeleteSessionOptions(sess_opts);
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;
+ return DNN_GENERIC_ERROR;
}
}
@@ -466,7 +468,7 @@ 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 create new session with model graph\n");
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
// Run initialization operation with name "init" if it is present in graph
@@ -481,7 +483,7 @@ 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 run session when initializing\n");
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
}
@@ -490,7 +492,7 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
#define NAME_BUFFER_SIZE 256
-static DNNReturnType add_conv_layer(TFModel *tf_model, TF_Operation *transpose_op, TF_Operation **cur_op,
+static int add_conv_layer(TFModel *tf_model, TF_Operation *transpose_op, TF_Operation **cur_op,
ConvolutionalParams* params, const int layer)
{
TFContext *ctx = &tf_model->ctx;
@@ -594,7 +596,7 @@ static DNNReturnType add_conv_layer(TFModel *tf_model, TF_Operation *transpose_o
break;
default:
avpriv_report_missing_feature(ctx, "convolutional activation function %d", params->activation);
- return DNN_ERROR;
+ return AVERROR(ENOSYS);
}
input.oper = *cur_op;
TF_AddInput(op_desc, input);
@@ -609,10 +611,10 @@ err:
TF_DeleteTensor(kernel_tensor);
TF_DeleteTensor(biases_tensor);
av_log(ctx, AV_LOG_ERROR, "Failed to add conv layer %d\n", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
-static DNNReturnType add_depth_to_space_layer(TFModel *tf_model, TF_Operation **cur_op,
+static int add_depth_to_space_layer(TFModel *tf_model, TF_Operation **cur_op,
DepthToSpaceParams *params, const int layer)
{
TFContext *ctx = &tf_model->ctx;
@@ -630,13 +632,13 @@ static DNNReturnType add_depth_to_space_layer(TFModel *tf_model, TF_Operation **
*cur_op = TF_FinishOperation(op_desc, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
av_log(ctx, AV_LOG_ERROR, "Failed to add depth_to_space to layer %d\n", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
return DNN_SUCCESS;
}
-static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
+static int add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
LayerPadParams *params, const int layer)
{
TFContext *ctx = &tf_model->ctx;
@@ -666,13 +668,13 @@ static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteTensor(tensor);
av_log(ctx, AV_LOG_ERROR, "Failed to set value for pad of layer %d\n", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
op = TF_FinishOperation(op_desc, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteTensor(tensor);
av_log(ctx, AV_LOG_ERROR, "Failed to add pad to layer %d\n", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
op_desc = TF_NewOperation(tf_model->graph, "MirrorPad", "mirror_pad");
@@ -688,13 +690,13 @@ static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteTensor(tensor);
av_log(ctx, AV_LOG_ERROR, "Failed to add mirror_pad to layer %d\n", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
return DNN_SUCCESS;
}
-static DNNReturnType add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
+static int add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
DnnLayerMaximumParams *params, const int layer)
{
TFContext *ctx = &tf_model->ctx;
@@ -716,13 +718,13 @@ static DNNReturnType add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteTensor(tensor);
av_log(ctx, AV_LOG_ERROR, "Failed to set value for maximum/y of layer %d", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
op = TF_FinishOperation(op_desc, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteTensor(tensor);
av_log(ctx, AV_LOG_ERROR, "Failed to add maximum/y to layer %d\n", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
snprintf(name_buffer, NAME_BUFFER_SIZE, "maximum%d", layer);
@@ -737,13 +739,13 @@ static DNNReturnType add_maximum_layer(TFModel *tf_model, TF_Operation **cur_op,
if (TF_GetCode(tf_model->status) != TF_OK){
TF_DeleteTensor(tensor);
av_log(ctx, AV_LOG_ERROR, "Failed to add maximum to layer %d\n", layer);
- return DNN_ERROR;
+ return DNN_GENERIC_ERROR;
}
return DNN_SUCCESS;
}
-static DNNReturnType load_native_model(TFModel *tf_model, const char *model_filename)
+static int load_native_model(TFModel *tf_model, const char *model_filename)
{
TFContext *ctx = &tf_model->ctx;
int32_t layer;
@@ -755,14 +757,14 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
int32_t *transpose_perm;
int64_t transpose_perm_shape[] = {4};
int64_t input_shape[] = {1, -1, -1, -1};
- DNNReturnType layer_add_res;
+ int layer_add_res;
DNNModel *model = NULL;
NativeModel *native_model;
model = ff_dnn_load_model_native(model_filename, DFT_PROCESS_FRAME, NULL, NULL);
if (!model){
av_log(ctx, AV_LOG_ERROR, "Failed to load native model\n");
- return DNN_ERROR;
+ return AVERROR(EINVAL);
}
native_model = model->model;
@@ -775,7 +777,7 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
TF_DeleteGraph(tf_model->graph); \
TF_DeleteStatus(tf_model->status); \
av_log(ctx, AV_LOG_ERROR, "Failed to set value or add operator to layer\n"); \
- return DNN_ERROR; \
+ return DNN_GENERIC_ERROR; \
}
op_desc = TF_NewOperation(tf_model->graph, "Placeholder", "x");
@@ -942,19 +944,21 @@ err:
return NULL;
}
-static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *request) {
+static int fill_model_input_tf(TFModel *tf_model, TFRequestItem *request) {
DNNData input;
LastLevelTaskItem *lltask;
TaskItem *task;
TFInferRequest *infer_request;
TFContext *ctx = &tf_model->ctx;
+ int ret = 0;
lltask = ff_queue_pop_front(tf_model->lltask_queue);
av_assert0(lltask);
task = lltask->task;
request->lltask = lltask;
- if (get_input_tf(tf_model, &input, task->input_name) != DNN_SUCCESS) {
+ ret = get_input_tf(tf_model, &input, task->input_name);
+ if (ret != DNN_SUCCESS) {
goto err;
}
@@ -965,12 +969,14 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
infer_request->tf_input = av_malloc(sizeof(TF_Output));
if (!infer_request->tf_input) {
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input tensor\n");
+ ret = AVERROR(ENOMEM);
goto err;
}
infer_request->tf_input->oper = TF_GraphOperationByName(tf_model->graph, task->input_name);
if (!infer_request->tf_input->oper){
av_log(ctx, AV_LOG_ERROR, "Could not find \"%s\" in model\n", task->input_name);
+ ret = DNN_GENERIC_ERROR;
goto err;
}
infer_request->tf_input->index = 0;
@@ -978,6 +984,7 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
infer_request->input_tensor = allocate_input_tensor(&input);
if (!infer_request->input_tensor){
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input tensor\n");
+ ret = AVERROR(ENOMEM);
goto err;
}
input.data = (float *)TF_TensorData(infer_request->input_tensor);
@@ -1003,12 +1010,14 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
infer_request->tf_outputs = av_malloc_array(task->nb_output, sizeof(TF_Output));
if (infer_request->tf_outputs == NULL) {
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for *tf_outputs\n");
+ ret = AVERROR(ENOMEM);
goto err;
}
infer_request->output_tensors = av_calloc(task->nb_output, sizeof(*infer_request->output_tensors));
if (!infer_request->output_tensors) {
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for output tensor\n");
+ ret = AVERROR(ENOMEM);
goto err;
}
@@ -1017,6 +1026,7 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
infer_request->tf_outputs[i].oper = TF_GraphOperationByName(tf_model->graph, task->output_names[i]);
if (!infer_request->tf_outputs[i].oper) {
av_log(ctx, AV_LOG_ERROR, "Could not find output \"%s\" in model\n", task->output_names[i]);
+ ret = DNN_GENERIC_ERROR;
goto err;
}
infer_request->tf_outputs[i].index = 0;
@@ -1025,7 +1035,7 @@ static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *reque
return DNN_SUCCESS;
err:
tf_free_request(infer_request);
- return DNN_ERROR;
+ return ret;
}
static void infer_completion_callback(void *args) {
@@ -1086,12 +1096,13 @@ err:
}
}
-static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queue)
+static int execute_model_tf(TFRequestItem *request, Queue *lltask_queue)
{
TFModel *tf_model;
TFContext *ctx;
LastLevelTaskItem *lltask;
TaskItem *task;
+ int ret = 0;
if (ff_queue_size(lltask_queue) == 0) {
destroy_request_item(&request);
@@ -1103,7 +1114,8 @@ static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queu
tf_model = task->model;
ctx = &tf_model->ctx;
- if (fill_model_input_tf(tf_model, request) != DNN_SUCCESS) {
+ ret = fill_model_input_tf(tf_model, request);
+ if (ret != DNN_SUCCESS) {
goto err;
}
@@ -1112,58 +1124,64 @@ static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queu
goto err;
}
return DNN_SUCCESS;
- } else {
- if (tf_start_inference(request) != DNN_SUCCESS) {
+ }
+ else {
+ ret = tf_start_inference(request);
+ if (ret != DNN_SUCCESS) {
goto err;
}
infer_completion_callback(request);
- return (task->inference_done == task->inference_todo) ? DNN_SUCCESS : DNN_ERROR;
+ return (task->inference_done == task->inference_todo) ? DNN_SUCCESS : DNN_GENERIC_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;
+ return ret;
}
-DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params)
+int ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params)
{
TFModel *tf_model = model->model;
TFContext *ctx = &tf_model->ctx;
TaskItem *task;
TFRequestItem *request;
+ int ret = 0;
- if (ff_check_exec_params(ctx, DNN_TF, model->func_type, exec_params) != 0) {
- return DNN_ERROR;
+ ret = ff_check_exec_params(ctx, DNN_TF, model->func_type, exec_params);
+ if (ret != 0) {
+ return ret;
}
task = av_malloc(sizeof(*task));
if (!task) {
av_log(ctx, AV_LOG_ERROR, "unable to alloc memory for task item.\n");
- return DNN_ERROR;
+ return AVERROR(ENOMEM);
}
- if (ff_dnn_fill_task(task, exec_params, tf_model, ctx->options.async, 1) != DNN_SUCCESS) {
+ ret = ff_dnn_fill_task(task, exec_params, tf_model, ctx->options.async, 1);
+ if (ret != DNN_SUCCESS) {
av_freep(&task);
- return DNN_ERROR;
+ return ret;
}
if (ff_queue_push_back(tf_model->task_queue, task) < 0) {
av_freep(&task);
av_log(ctx, AV_LOG_ERROR, "unable to push back task_queue.\n");
- return DNN_ERROR;
+ return AVERROR(ENOMEM);
}
- if (extract_lltask_from_task(task, tf_model->lltask_queue) != DNN_SUCCESS) {
+ ret = extract_lltask_from_task(task, tf_model->lltask_queue);
+ if (ret != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract last level task from task.\n");
- return DNN_ERROR;
+ return ret;
}
request = ff_safe_queue_pop_front(tf_model->request_queue);
if (!request) {
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
- return DNN_ERROR;
+ return AVERROR(EINVAL);
}
return execute_model_tf(request, tf_model->lltask_queue);
}
@@ -1174,12 +1192,12 @@ DNNAsyncStatusType ff_dnn_get_result_tf(const DNNModel *model, AVFrame **in, AVF
return ff_dnn_get_result_common(tf_model->task_queue, in, out);
}
-DNNReturnType ff_dnn_flush_tf(const DNNModel *model)
+int ff_dnn_flush_tf(const DNNModel *model)
{
TFModel *tf_model = model->model;
TFContext *ctx = &tf_model->ctx;
TFRequestItem *request;
- DNNReturnType ret;
+ int ret;
if (ff_queue_size(tf_model->lltask_queue) == 0) {
// no pending task need to flush
@@ -1189,7 +1207,7 @@ DNNReturnType ff_dnn_flush_tf(const DNNModel *model)
request = ff_safe_queue_pop_front(tf_model->request_queue);
if (!request) {
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
- return DNN_ERROR;
+ return AVERROR(EINVAL);
}
ret = fill_model_input_tf(tf_model, request);
diff --git a/libavfilter/dnn/dnn_backend_tf.h b/libavfilter/dnn/dnn_backend_tf.h
index f14ea8c47a..0b63a4b6d2 100644
--- a/libavfilter/dnn/dnn_backend_tf.h
+++ b/libavfilter/dnn/dnn_backend_tf.h
@@ -31,9 +31,9 @@
DNNModel *ff_dnn_load_model_tf(const char *model_filename, DNNFunctionType func_type, const char *options, AVFilterContext *filter_ctx);
-DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params);
+int ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *exec_params);
DNNAsyncStatusType ff_dnn_get_result_tf(const DNNModel *model, AVFrame **in, AVFrame **out);
-DNNReturnType ff_dnn_flush_tf(const DNNModel *model);
+int ff_dnn_flush_tf(const DNNModel *model);
void ff_dnn_free_model_tf(DNNModel **model);
--
2.32.0
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