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lavfi/dnn: Rename InferenceItem to LastLevelTaskItem 

This patch renames the InferenceItem to LastLevelTaskItem in the
three backends to avoid confusion among the meanings of these structs.

The following are the renames done in this patch:

1. extract_inference_from_task -> extract_lltask_from_task
2. InferenceItem -> LastLevelTaskItem
3. inference_queue -> lltask_queue
4. inference -> lltask
5. inference_count -> lltask_count

Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
This commit is contained in:
Shubhanshu Saxena 2021-08-26 02:40:48 +05:30 committed by Guo Yejun
parent 1544d6fa0a
commit 660a205b05
5 changed files with 125 additions and 125 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
libavfilter/dnn/dnn_backend_common.h
View File

@ -47,10 +47,10 @@ typedef struct TaskItem {
} TaskItem;
// one task might have multiple inferences
typedef struct InferenceItem {
typedef struct LastLevelTaskItem {
TaskItem *task;
uint32_t bbox_index;
} InferenceItem;
} LastLevelTaskItem;
/**
* Common Async Execution Mechanism for the DNN Backends.

58
libavfilter/dnn/dnn_backend_native.c
View File

@ -46,25 +46,25 @@ static const AVClass dnn_native_class = {
.category = AV_CLASS_CATEGORY_FILTER,
};
static DNNReturnType execute_model_native(Queue *inference_queue);
static DNNReturnType execute_model_native(Queue *lltask_queue);
static DNNReturnType extract_inference_from_task(TaskItem *task, Queue *inference_queue)
static DNNReturnType extract_lltask_from_task(TaskItem *task, Queue *lltask_queue)
{
NativeModel *native_model = task->model;
NativeContext *ctx = &native_model->ctx;
InferenceItem *inference = av_malloc(sizeof(*inference));
LastLevelTaskItem *lltask = av_malloc(sizeof(*lltask));
if (!inference) {
av_log(ctx, AV_LOG_ERROR, "Unable to allocate space for InferenceItem\n");
if (!lltask) {
av_log(ctx, AV_LOG_ERROR, "Unable to allocate space for LastLevelTaskItem\n");
return DNN_ERROR;
}
task->inference_todo = 1;
task->inference_done = 0;
inference->task = task;
lltask->task = task;
if (ff_queue_push_back(inference_queue, inference) < 0) {
av_log(ctx, AV_LOG_ERROR, "Failed to push back inference_queue.\n");
av_freep(&inference);
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 DNN_SUCCESS;
@ -116,13 +116,13 @@ static DNNReturnType get_output_native(void *model, const char *input_name, int
goto err;
}
if (extract_inference_from_task(&task, native_model->inference_queue) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
if (extract_lltask_from_task(&task, native_model->lltask_queue) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract last level task from task.\n");
ret = DNN_ERROR;
goto err;
}
ret = execute_model_native(native_model->inference_queue);
ret = execute_model_native(native_model->lltask_queue);
*output_width = task.out_frame->width;
*output_height = task.out_frame->height;
@ -223,8 +223,8 @@ DNNModel *ff_dnn_load_model_native(const char *model_filename, DNNFunctionType f
goto fail;
}
native_model->inference_queue = ff_queue_create();
if (!native_model->inference_queue) {
native_model->lltask_queue = ff_queue_create();
if (!native_model->lltask_queue) {
goto fail;
}
@ -297,24 +297,24 @@ fail:
return NULL;
}
static DNNReturnType execute_model_native(Queue *inference_queue)
static DNNReturnType execute_model_native(Queue *lltask_queue)
{
NativeModel *native_model = NULL;
NativeContext *ctx = NULL;
int32_t layer;
DNNData input, output;
DnnOperand *oprd = NULL;
InferenceItem *inference = NULL;
LastLevelTaskItem *lltask = NULL;
TaskItem *task = NULL;
DNNReturnType ret = 0;
inference = ff_queue_pop_front(inference_queue);
if (!inference) {
av_log(NULL, AV_LOG_ERROR, "Failed to get inference item\n");
lltask = ff_queue_pop_front(lltask_queue);
if (!lltask) {
av_log(NULL, AV_LOG_ERROR, "Failed to get LastLevelTaskItem\n");
ret = DNN_ERROR;
goto err;
}
task = inference->task;
task = lltask->task;
native_model = task->model;
ctx = &native_model->ctx;
@ -428,7 +428,7 @@ static DNNReturnType execute_model_native(Queue *inference_queue)
}
task->inference_done++;
err:
av_freep(&inference);
av_freep(&lltask);
return ret;
}
@ -459,26 +459,26 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel *model, DNNExecBasePara
return DNN_ERROR;
}
if (extract_inference_from_task(task, native_model->inference_queue) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
if (extract_lltask_from_task(task, native_model->lltask_queue) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract last level task from task.\n");
return DNN_ERROR;
}
return execute_model_native(native_model->inference_queue);
return execute_model_native(native_model->lltask_queue);
}
DNNReturnType ff_dnn_flush_native(const DNNModel *model)
{
NativeModel *native_model = model->model;
if (ff_queue_size(native_model->inference_queue) == 0) {
if (ff_queue_size(native_model->lltask_queue) == 0) {
// no pending task need to flush
return DNN_SUCCESS;
}
// for now, use sync node with flush operation
// Switch to async when it is supported
return execute_model_native(native_model->inference_queue);
return execute_model_native(native_model->lltask_queue);
}
DNNAsyncStatusType ff_dnn_get_result_native(const DNNModel *model, AVFrame **in, AVFrame **out)
@ -536,11 +536,11 @@ void ff_dnn_free_model_native(DNNModel **model)
av_freep(&native_model->operands);
}
while (ff_queue_size(native_model->inference_queue) != 0) {
InferenceItem *item = ff_queue_pop_front(native_model->inference_queue);
while (ff_queue_size(native_model->lltask_queue) != 0) {
LastLevelTaskItem *item = ff_queue_pop_front(native_model->lltask_queue);
av_freep(&item);
}
ff_queue_destroy(native_model->inference_queue);
ff_queue_destroy(native_model->lltask_queue);
while (ff_queue_size(native_model->task_queue) != 0) {
TaskItem *item = ff_queue_pop_front(native_model->task_queue);

2
libavfilter/dnn/dnn_backend_native.h
View File

@ -129,7 +129,7 @@ typedef struct NativeModel{
DnnOperand *operands;
int32_t operands_num;
Queue *task_queue;
Queue *inference_queue;
Queue *lltask_queue;
} NativeModel;
DNNModel *ff_dnn_load_model_native(const char *model_filename, DNNFunctionType func_type, const char *options, AVFilterContext *filter_ctx);

110
libavfilter/dnn/dnn_backend_openvino.c
View File

@ -57,14 +57,14 @@ typedef struct OVModel{
ie_executable_network_t *exe_network;
SafeQueue *request_queue; // holds OVRequestItem
Queue *task_queue; // holds TaskItem
Queue *inference_queue; // holds InferenceItem
Queue *lltask_queue; // holds LastLevelTaskItem
} OVModel;
// one request for one call to openvino
typedef struct OVRequestItem {
ie_infer_request_t *infer_request;
InferenceItem **inferences;
uint32_t inference_count;
LastLevelTaskItem **lltasks;
uint32_t lltask_count;
ie_complete_call_back_t callback;
} OVRequestItem;
@ -121,12 +121,12 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, OVRequestItem *reque
IEStatusCode status;
DNNData input;
ie_blob_t *input_blob = NULL;
InferenceItem *inference;
LastLevelTaskItem *lltask;
TaskItem *task;
inference = ff_queue_peek_front(ov_model->inference_queue);
av_assert0(inference);
task = inference->task;
lltask = ff_queue_peek_front(ov_model->lltask_queue);
av_assert0(lltask);
task = lltask->task;
status = ie_infer_request_get_blob(request->infer_request, task->input_name, &input_blob);
if (status != OK) {
@ -159,13 +159,13 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, OVRequestItem *reque
input.order = DCO_BGR;
for (int i = 0; i < ctx->options.batch_size; ++i) {
inference = ff_queue_pop_front(ov_model->inference_queue);
if (!inference) {
lltask = ff_queue_pop_front(ov_model->lltask_queue);
if (!lltask) {
break;
}
request->inferences[i] = inference;
request->inference_count = i + 1;
task = inference->task;
request->lltasks[i] = lltask;
request->lltask_count = i + 1;
task = lltask->task;
switch (ov_model->model->func_type) {
case DFT_PROCESS_FRAME:
if (task->do_ioproc) {
@ -180,7 +180,7 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, OVRequestItem *reque
ff_frame_to_dnn_detect(task->in_frame, &input, ctx);
break;
case DFT_ANALYTICS_CLASSIFY:
ff_frame_to_dnn_classify(task->in_frame, &input, inference->bbox_index, ctx);
ff_frame_to_dnn_classify(task->in_frame, &input, lltask->bbox_index, ctx);
break;
default:
av_assert0(!"should not reach here");
@ -200,8 +200,8 @@ static void infer_completion_callback(void *args)
precision_e precision;
IEStatusCode status;
OVRequestItem *request = args;
InferenceItem *inference = request->inferences[0];
TaskItem *task = inference->task;
LastLevelTaskItem *lltask = request->lltasks[0];
TaskItem *task = lltask->task;
OVModel *ov_model = task->model;
SafeQueue *requestq = ov_model->request_queue;
ie_blob_t *output_blob = NULL;
@ -248,10 +248,10 @@ static void infer_completion_callback(void *args)
output.dt = precision_to_datatype(precision);
output.data = blob_buffer.buffer;
av_assert0(request->inference_count <= dims.dims[0]);
av_assert0(request->inference_count >= 1);
for (int i = 0; i < request->inference_count; ++i) {
task = request->inferences[i]->task;
av_assert0(request->lltask_count <= dims.dims[0]);
av_assert0(request->lltask_count >= 1);
for (int i = 0; i < request->lltask_count; ++i) {
task = request->lltasks[i]->task;
task->inference_done++;
switch (ov_model->model->func_type) {
@ -279,20 +279,20 @@ static void infer_completion_callback(void *args)
av_log(ctx, AV_LOG_ERROR, "classify filter needs to provide post proc\n");
return;
}
ov_model->model->classify_post_proc(task->in_frame, &output, request->inferences[i]->bbox_index, ov_model->model->filter_ctx);
ov_model->model->classify_post_proc(task->in_frame, &output, request->lltasks[i]->bbox_index, ov_model->model->filter_ctx);
break;
default:
av_assert0(!"should not reach here");
break;
}
av_freep(&request->inferences[i]);
av_freep(&request->lltasks[i]);
output.data = (uint8_t *)output.data
+ output.width * output.height * output.channels * get_datatype_size(output.dt);
}
ie_blob_free(&output_blob);
request->inference_count = 0;
request->lltask_count = 0;
if (ff_safe_queue_push_back(requestq, request) < 0) {
ie_infer_request_free(&request->infer_request);
av_freep(&request);
@ -399,11 +399,11 @@ static DNNReturnType init_model_ov(OVModel *ov_model, const char *input_name, co
goto err;
}
item->inferences = av_malloc_array(ctx->options.batch_size, sizeof(*item->inferences));
if (!item->inferences) {
item->lltasks = av_malloc_array(ctx->options.batch_size, sizeof(*item->lltasks));
if (!item->lltasks) {
goto err;
}
item->inference_count = 0;
item->lltask_count = 0;
}
ov_model->task_queue = ff_queue_create();
@ -411,8 +411,8 @@ static DNNReturnType init_model_ov(OVModel *ov_model, const char *input_name, co
goto err;
}
ov_model->inference_queue = ff_queue_create();
if (!ov_model->inference_queue) {
ov_model->lltask_queue = ff_queue_create();
if (!ov_model->lltask_queue) {
goto err;
}
@ -427,7 +427,7 @@ static DNNReturnType execute_model_ov(OVRequestItem *request, Queue *inferenceq)
{
IEStatusCode status;
DNNReturnType ret;
InferenceItem *inference;
LastLevelTaskItem *lltask;
TaskItem *task;
OVContext *ctx;
OVModel *ov_model;
@ -438,8 +438,8 @@ static DNNReturnType execute_model_ov(OVRequestItem *request, Queue *inferenceq)
return DNN_SUCCESS;
}
inference = ff_queue_peek_front(inferenceq);
task = inference->task;
lltask = ff_queue_peek_front(inferenceq);
task = lltask->task;
ov_model = task->model;
ctx = &ov_model->ctx;
@ -567,21 +567,21 @@ static int contain_valid_detection_bbox(AVFrame *frame)
return 1;
}
static DNNReturnType extract_inference_from_task(DNNFunctionType func_type, TaskItem *task, Queue *inference_queue, DNNExecBaseParams *exec_params)
static DNNReturnType extract_lltask_from_task(DNNFunctionType func_type, TaskItem *task, Queue *lltask_queue, DNNExecBaseParams *exec_params)
{
switch (func_type) {
case DFT_PROCESS_FRAME:
case DFT_ANALYTICS_DETECT:
{
InferenceItem *inference = av_malloc(sizeof(*inference));
if (!inference) {
LastLevelTaskItem *lltask = av_malloc(sizeof(*lltask));
if (!lltask) {
return DNN_ERROR;
}
task->inference_todo = 1;
task->inference_done = 0;
inference->task = task;
if (ff_queue_push_back(inference_queue, inference) < 0) {
av_freep(&inference);
lltask->task = task;
if (ff_queue_push_back(lltask_queue, lltask) < 0) {
av_freep(&lltask);
return DNN_ERROR;
}
return DNN_SUCCESS;
@ -604,7 +604,7 @@ static DNNReturnType extract_inference_from_task(DNNFunctionType func_type, Task
header = (const AVDetectionBBoxHeader *)sd->data;
for (uint32_t i = 0; i < header->nb_bboxes; i++) {
InferenceItem *inference;
LastLevelTaskItem *lltask;
const AVDetectionBBox *bbox = av_get_detection_bbox(header, i);
if (params->target) {
@ -613,15 +613,15 @@ static DNNReturnType extract_inference_from_task(DNNFunctionType func_type, Task
}
}
inference = av_malloc(sizeof(*inference));
if (!inference) {
lltask = av_malloc(sizeof(*lltask));
if (!lltask) {
return DNN_ERROR;
}
task->inference_todo++;
inference->task = task;
inference->bbox_index = i;
if (ff_queue_push_back(inference_queue, inference) < 0) {
av_freep(&inference);
lltask->task = task;
lltask->bbox_index = i;
if (ff_queue_push_back(lltask_queue, lltask) < 0) {
av_freep(&lltask);
return DNN_ERROR;
}
}
@ -679,8 +679,8 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
return DNN_ERROR;
}
if (extract_inference_from_task(ov_model->model->func_type, &task, ov_model->inference_queue, NULL) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
if (extract_lltask_from_task(ov_model->model->func_type, &task, ov_model->lltask_queue, NULL) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract last level task from task.\n");
ret = DNN_ERROR;
goto err;
}
@ -692,7 +692,7 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
goto err;
}
ret = execute_model_ov(request, ov_model->inference_queue);
ret = execute_model_ov(request, ov_model->lltask_queue);
*output_width = task.out_frame->width;
*output_height = task.out_frame->height;
err:
@ -794,20 +794,20 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, DNNExecBaseParams *
return DNN_ERROR;
}
if (extract_inference_from_task(model->func_type, task, ov_model->inference_queue, exec_params) != DNN_SUCCESS) {
if (extract_lltask_from_task(model->func_type, task, ov_model->lltask_queue, exec_params) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
return DNN_ERROR;
}
if (ctx->options.async) {
while (ff_queue_size(ov_model->inference_queue) >= ctx->options.batch_size) {
while (ff_queue_size(ov_model->lltask_queue) >= ctx->options.batch_size) {
request = ff_safe_queue_pop_front(ov_model->request_queue);
if (!request) {
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
return DNN_ERROR;
}
ret = execute_model_ov(request, ov_model->inference_queue);
ret = execute_model_ov(request, ov_model->lltask_queue);
if (ret != DNN_SUCCESS) {
return ret;
}
@ -833,7 +833,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, DNNExecBaseParams *
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
return DNN_ERROR;
}
return execute_model_ov(request, ov_model->inference_queue);
return execute_model_ov(request, ov_model->lltask_queue);
}
}
@ -851,7 +851,7 @@ DNNReturnType ff_dnn_flush_ov(const DNNModel *model)
IEStatusCode status;
DNNReturnType ret;
if (ff_queue_size(ov_model->inference_queue) == 0) {
if (ff_queue_size(ov_model->lltask_queue) == 0) {
// no pending task need to flush
return DNN_SUCCESS;
}
@ -890,16 +890,16 @@ void ff_dnn_free_model_ov(DNNModel **model)
if (item && item->infer_request) {
ie_infer_request_free(&item->infer_request);
}
av_freep(&item->inferences);
av_freep(&item->lltasks);
av_freep(&item);
}
ff_safe_queue_destroy(ov_model->request_queue);
while (ff_queue_size(ov_model->inference_queue) != 0) {
InferenceItem *item = ff_queue_pop_front(ov_model->inference_queue);
while (ff_queue_size(ov_model->lltask_queue) != 0) {
LastLevelTaskItem *item = ff_queue_pop_front(ov_model->lltask_queue);
av_freep(&item);
}
ff_queue_destroy(ov_model->inference_queue);
ff_queue_destroy(ov_model->lltask_queue);
while (ff_queue_size(ov_model->task_queue) != 0) {
TaskItem *item = ff_queue_pop_front(ov_model->task_queue);

76
libavfilter/dnn/dnn_backend_tf.c
View File

@ -58,7 +58,7 @@ typedef struct TFModel{
TF_Session *session;
TF_Status *status;
SafeQueue *request_queue;
Queue *inference_queue;
Queue *lltask_queue;
Queue *task_queue;
} TFModel;
@ -75,7 +75,7 @@ typedef struct TFInferRequest {
typedef struct TFRequestItem {
TFInferRequest *infer_request;
InferenceItem *inference;
LastLevelTaskItem *lltask;
TF_Status *status;
DNNAsyncExecModule exec_module;
} TFRequestItem;
@ -90,7 +90,7 @@ static const AVOption dnn_tensorflow_options[] = {
AVFILTER_DEFINE_CLASS(dnn_tensorflow);
static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *inference_queue);
static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queue);
static void infer_completion_callback(void *args);
static inline void destroy_request_item(TFRequestItem **arg);
@ -158,8 +158,8 @@ static DNNReturnType tf_start_inference(void *args)
{
TFRequestItem *request = args;
TFInferRequest *infer_request = request->infer_request;
InferenceItem *inference = request->inference;
TaskItem *task = inference->task;
LastLevelTaskItem *lltask = request->lltask;
TaskItem *task = lltask->task;
TFModel *tf_model = task->model;
if (!request) {
@ -196,27 +196,27 @@ static inline void destroy_request_item(TFRequestItem **arg) {
request = *arg;
tf_free_request(request->infer_request);
av_freep(&request->infer_request);
av_freep(&request->inference);
av_freep(&request->lltask);
TF_DeleteStatus(request->status);
ff_dnn_async_module_cleanup(&request->exec_module);
av_freep(arg);
}
static DNNReturnType extract_inference_from_task(TaskItem *task, Queue *inference_queue)
static DNNReturnType extract_lltask_from_task(TaskItem *task, Queue *lltask_queue)
{
TFModel *tf_model = task->model;
TFContext *ctx = &tf_model->ctx;
InferenceItem *inference = av_malloc(sizeof(*inference));
if (!inference) {
av_log(ctx, AV_LOG_ERROR, "Unable to allocate space for InferenceItem\n");
LastLevelTaskItem *lltask = av_malloc(sizeof(*lltask));
if (!lltask) {
av_log(ctx, AV_LOG_ERROR, "Unable to allocate space for LastLevelTaskItem\n");
return DNN_ERROR;
}
task->inference_todo = 1;
task->inference_done = 0;
inference->task = task;
if (ff_queue_push_back(inference_queue, inference) < 0) {
av_log(ctx, AV_LOG_ERROR, "Failed to push back inference_queue.\n");
av_freep(&inference);
lltask->task = task;
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 DNN_SUCCESS;
@ -333,7 +333,7 @@ static DNNReturnType get_output_tf(void *model, const char *input_name, int inpu
goto err;
}
if (extract_inference_from_task(&task, tf_model->inference_queue) != DNN_SUCCESS) {
if (extract_lltask_from_task(&task, tf_model->lltask_queue) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
ret = DNN_ERROR;
goto err;
@ -346,7 +346,7 @@ static DNNReturnType get_output_tf(void *model, const char *input_name, int inpu
goto err;
}
ret = execute_model_tf(request, tf_model->inference_queue);
ret = execute_model_tf(request, tf_model->lltask_queue);
*output_width = task.out_frame->width;
*output_height = task.out_frame->height;
@ -901,7 +901,7 @@ DNNModel *ff_dnn_load_model_tf(const char *model_filename, DNNFunctionType func_
if (!item) {
goto err;
}
item->inference = NULL;
item->lltask = NULL;
item->infer_request = tf_create_inference_request();
if (!item->infer_request) {
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for TensorFlow inference request\n");
@ -919,8 +919,8 @@ DNNModel *ff_dnn_load_model_tf(const char *model_filename, DNNFunctionType func_
}
}
tf_model->inference_queue = ff_queue_create();
if (!tf_model->inference_queue) {
tf_model->lltask_queue = ff_queue_create();
if (!tf_model->lltask_queue) {
goto err;
}
@ -944,15 +944,15 @@ err:
static DNNReturnType fill_model_input_tf(TFModel *tf_model, TFRequestItem *request) {
DNNData input;
InferenceItem *inference;
LastLevelTaskItem *lltask;
TaskItem *task;
TFInferRequest *infer_request;
TFContext *ctx = &tf_model->ctx;
inference = ff_queue_pop_front(tf_model->inference_queue);
av_assert0(inference);
task = inference->task;
request->inference = inference;
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) {
goto err;
@ -1030,8 +1030,8 @@ err:
static void infer_completion_callback(void *args) {
TFRequestItem *request = args;
InferenceItem *inference = request->inference;
TaskItem *task = inference->task;
LastLevelTaskItem *lltask = request->lltask;
TaskItem *task = lltask->task;
DNNData *outputs;
TFInferRequest *infer_request = request->infer_request;
TFModel *tf_model = task->model;
@ -1086,20 +1086,20 @@ err:
}
}
static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *inference_queue)
static DNNReturnType execute_model_tf(TFRequestItem *request, Queue *lltask_queue)
{
TFModel *tf_model;
TFContext *ctx;
InferenceItem *inference;
LastLevelTaskItem *lltask;
TaskItem *task;
if (ff_queue_size(inference_queue) == 0) {
if (ff_queue_size(lltask_queue) == 0) {
destroy_request_item(&request);
return DNN_SUCCESS;
}
inference = ff_queue_peek_front(inference_queue);
task = inference->task;
lltask = ff_queue_peek_front(lltask_queue);
task = lltask->task;
tf_model = task->model;
ctx = &tf_model->ctx;
@ -1155,8 +1155,8 @@ DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *
return DNN_ERROR;
}
if (extract_inference_from_task(task, tf_model->inference_queue) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n");
if (extract_lltask_from_task(task, tf_model->lltask_queue) != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "unable to extract last level task from task.\n");
return DNN_ERROR;
}
@ -1165,7 +1165,7 @@ DNNReturnType ff_dnn_execute_model_tf(const DNNModel *model, DNNExecBaseParams *
av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
return DNN_ERROR;
}
return execute_model_tf(request, tf_model->inference_queue);
return execute_model_tf(request, tf_model->lltask_queue);
}
DNNAsyncStatusType ff_dnn_get_result_tf(const DNNModel *model, AVFrame **in, AVFrame **out)
@ -1181,7 +1181,7 @@ DNNReturnType ff_dnn_flush_tf(const DNNModel *model)
TFRequestItem *request;
DNNReturnType ret;
if (ff_queue_size(tf_model->inference_queue) == 0) {
if (ff_queue_size(tf_model->lltask_queue) == 0) {
// no pending task need to flush
return DNN_SUCCESS;
}
@ -1216,11 +1216,11 @@ void ff_dnn_free_model_tf(DNNModel **model)
}
ff_safe_queue_destroy(tf_model->request_queue);
while (ff_queue_size(tf_model->inference_queue) != 0) {
InferenceItem *item = ff_queue_pop_front(tf_model->inference_queue);
while (ff_queue_size(tf_model->lltask_queue) != 0) {
LastLevelTaskItem *item = ff_queue_pop_front(tf_model->lltask_queue);
av_freep(&item);
}
ff_queue_destroy(tf_model->inference_queue);
ff_queue_destroy(tf_model->lltask_queue);
while (ff_queue_size(tf_model->task_queue) != 0) {
TaskItem *item = ff_queue_pop_front(tf_model->task_queue);