[FFmpeg-cvslog] libavfilter/dnn: add batch mode for async execution
Guo, Yejun
git at videolan.org
Fri Jan 15 04:11:20 EET 2021
ffmpeg | branch: master | Guo, Yejun <yejun.guo at intel.com> | Thu Jan 7 11:14:10 2021 +0800| [64ea15f05075d58cbd76bdcd5bac9d3b47d891ee] | committer: Guo, Yejun
libavfilter/dnn: add batch mode for async execution
the default number of batch_size is 1
Signed-off-by: Xie, Lin <lin.xie at intel.com>
Signed-off-by: Wu Zhiwen <zhiwen.wu at intel.com>
Signed-off-by: Guo, Yejun <yejun.guo at intel.com>
> http://git.videolan.org/gitweb.cgi/ffmpeg.git/?a=commit;h=64ea15f05075d58cbd76bdcd5bac9d3b47d891ee
---
libavfilter/dnn/dnn_backend_openvino.c | 187 +++++++++++++++++++++++++++------
libavfilter/dnn/dnn_backend_openvino.h | 1 +
libavfilter/dnn/dnn_interface.c | 1 +
libavfilter/dnn_interface.h | 2 +
libavfilter/vf_dnn_processing.c | 40 ++++++-
5 files changed, 196 insertions(+), 35 deletions(-)
diff --git a/libavfilter/dnn/dnn_backend_openvino.c b/libavfilter/dnn/dnn_backend_openvino.c
index d27e451eea..5271d1caa5 100644
--- a/libavfilter/dnn/dnn_backend_openvino.c
+++ b/libavfilter/dnn/dnn_backend_openvino.c
@@ -37,6 +37,7 @@
typedef struct OVOptions{
char *device_type;
int nireq;
+ int batch_size;
} OVOptions;
typedef struct OVContext {
@@ -70,7 +71,8 @@ typedef struct TaskItem {
typedef struct RequestItem {
ie_infer_request_t *infer_request;
- TaskItem *task;
+ TaskItem **tasks;
+ int task_count;
ie_complete_call_back_t callback;
} RequestItem;
@@ -83,6 +85,7 @@ typedef struct RequestItem {
static const AVOption dnn_openvino_options[] = {
{ "device", "device to run model", OFFSET(options.device_type), AV_OPT_TYPE_STRING, { .str = "CPU" }, 0, 0, FLAGS },
{ "nireq", "number of request", OFFSET(options.nireq), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, INT_MAX, FLAGS },
+ { "batch_size", "batch size per request", OFFSET(options.batch_size), AV_OPT_TYPE_INT, { .i64 = 1 }, 1, 1000, FLAGS},
{ NULL }
};
@@ -100,7 +103,19 @@ static DNNDataType precision_to_datatype(precision_e precision)
}
}
-static DNNReturnType fill_model_input_ov(OVModel *ov_model, TaskItem *task, RequestItem *request)
+static int get_datatype_size(DNNDataType dt)
+{
+ switch (dt)
+ {
+ case DNN_FLOAT:
+ return sizeof(float);
+ default:
+ av_assert0(!"not supported yet.");
+ return 1;
+ }
+}
+
+static DNNReturnType fill_model_input_ov(OVModel *ov_model, RequestItem *request)
{
dimensions_t dims;
precision_e precision;
@@ -109,6 +124,7 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, TaskItem *task, Requ
IEStatusCode status;
DNNData input;
ie_blob_t *input_blob = NULL;
+ TaskItem *task = request->tasks[0];
status = ie_infer_request_get_blob(request->infer_request, task->input_name, &input_blob);
if (status != OK) {
@@ -134,12 +150,19 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, TaskItem *task, Requ
input.channels = dims.dims[1];
input.data = blob_buffer.buffer;
input.dt = precision_to_datatype(precision);
- if (task->do_ioproc) {
- if (ov_model->model->pre_proc != NULL) {
- ov_model->model->pre_proc(task->in_frame, &input, ov_model->model->filter_ctx);
- } else {
- proc_from_frame_to_dnn(task->in_frame, &input, ctx);
+
+ av_assert0(request->task_count <= dims.dims[0]);
+ for (int i = 0; i < request->task_count; ++i) {
+ task = request->tasks[i];
+ if (task->do_ioproc) {
+ if (ov_model->model->pre_proc != NULL) {
+ ov_model->model->pre_proc(task->in_frame, &input, ov_model->model->filter_ctx);
+ } else {
+ proc_from_frame_to_dnn(task->in_frame, &input, ctx);
+ }
}
+ input.data = (uint8_t *)input.data
+ + input.width * input.height * input.channels * get_datatype_size(input.dt);
}
ie_blob_free(&input_blob);
@@ -152,7 +175,7 @@ static void infer_completion_callback(void *args)
precision_e precision;
IEStatusCode status;
RequestItem *request = args;
- TaskItem *task = request->task;
+ TaskItem *task = request->tasks[0];
ie_blob_t *output_blob = NULL;
ie_blob_buffer_t blob_buffer;
DNNData output;
@@ -194,41 +217,56 @@ static void infer_completion_callback(void *args)
output.width = dims.dims[3];
output.dt = precision_to_datatype(precision);
output.data = blob_buffer.buffer;
- if (task->do_ioproc) {
- if (task->ov_model->model->post_proc != NULL) {
- task->ov_model->model->post_proc(task->out_frame, &output, task->ov_model->model->filter_ctx);
+
+ av_assert0(request->task_count <= dims.dims[0]);
+ av_assert0(request->task_count >= 1);
+ for (int i = 0; i < request->task_count; ++i) {
+ task = request->tasks[i];
+ if (task->do_ioproc) {
+ if (task->ov_model->model->post_proc != NULL) {
+ task->ov_model->model->post_proc(task->out_frame, &output, task->ov_model->model->filter_ctx);
+ } else {
+ proc_from_dnn_to_frame(task->out_frame, &output, ctx);
+ }
} else {
- proc_from_dnn_to_frame(task->out_frame, &output, ctx);
+ task->out_frame->width = output.width;
+ task->out_frame->height = output.height;
}
- } else {
- task->out_frame->width = output.width;
- task->out_frame->height = output.height;
+ task->done = 1;
+ output.data = (uint8_t *)output.data
+ + output.width * output.height * output.channels * get_datatype_size(output.dt);
}
ie_blob_free(&output_blob);
+ request->task_count = 0;
+
if (task->async) {
- request->task = NULL;
if (ff_safe_queue_push_back(task->ov_model->request_queue, request) < 0) {
av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
return;
}
}
-
- task->done = 1;
}
-static DNNReturnType execute_model_ov(TaskItem *task, RequestItem *request)
+static DNNReturnType execute_model_ov(RequestItem *request)
{
IEStatusCode status;
+ DNNReturnType ret;
+ TaskItem *task = request->tasks[0];
OVContext *ctx = &task->ov_model->ctx;
- DNNReturnType ret = fill_model_input_ov(task->ov_model, task, request);
- if (ret != DNN_SUCCESS) {
- return ret;
- }
-
if (task->async) {
- request->task = task;
+ if (request->task_count < ctx->options.batch_size) {
+ if (ff_safe_queue_push_front(task->ov_model->request_queue, request) < 0) {
+ av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
+ return DNN_ERROR;
+ }
+ return DNN_SUCCESS;
+ }
+ ret = fill_model_input_ov(task->ov_model, request);
+ if (ret != DNN_SUCCESS) {
+ return ret;
+ }
status = ie_infer_set_completion_callback(request->infer_request, &request->callback);
if (status != OK) {
av_log(ctx, AV_LOG_ERROR, "Failed to set completion callback for inference\n");
@@ -241,12 +279,15 @@ static DNNReturnType execute_model_ov(TaskItem *task, RequestItem *request)
}
return DNN_SUCCESS;
} else {
+ ret = fill_model_input_ov(task->ov_model, request);
+ if (ret != DNN_SUCCESS) {
+ return ret;
+ }
status = ie_infer_request_infer(request->infer_request);
if (status != OK) {
av_log(ctx, AV_LOG_ERROR, "Failed to start synchronous model inference\n");
return DNN_ERROR;
}
- request->task = task;
infer_completion_callback(request);
return task->done ? DNN_SUCCESS : DNN_ERROR;
}
@@ -319,6 +360,7 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
RequestItem request;
AVFrame *in_frame = av_frame_alloc();
AVFrame *out_frame = NULL;
+ TaskItem *ptask = &task;
if (!in_frame) {
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input frame\n");
@@ -343,8 +385,10 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
task.ov_model = ov_model;
request.infer_request = ov_model->infer_request;
+ request.task_count = 1;
+ request.tasks = &ptask;
- ret = execute_model_ov(&task, &request);
+ ret = execute_model_ov(&request);
*output_width = out_frame->width;
*output_height = out_frame->height;
@@ -393,6 +437,24 @@ DNNModel *ff_dnn_load_model_ov(const char *model_filename, const char *options,
if (status != OK)
goto err;
+ // batch size
+ if (ctx->options.batch_size <= 0) {
+ ctx->options.batch_size = 1;
+ }
+
+ if (ctx->options.batch_size > 1) {
+ input_shapes_t input_shapes;
+ status = ie_network_get_input_shapes(ov_model->network, &input_shapes);
+ if (status != OK)
+ goto err;
+ for (int i = 0; i < input_shapes.shape_num; i++)
+ input_shapes.shapes[i].shape.dims[0] = ctx->options.batch_size;
+ status = ie_network_reshape(ov_model->network, input_shapes);
+ ie_network_input_shapes_free(&input_shapes);
+ if (status != OK)
+ goto err;
+ }
+
status = ie_core_load_network(ov_model->core, ov_model->network, ctx->options.device_type, &config, &ov_model->exe_network);
if (status != OK) {
av_log(ctx, AV_LOG_ERROR, "Failed to init OpenVINO model\n");
@@ -426,17 +488,24 @@ DNNModel *ff_dnn_load_model_ov(const char *model_filename, const char *options,
}
for (int i = 0; i < ctx->options.nireq; i++) {
- ie_infer_request_t *request;
RequestItem *item = av_mallocz(sizeof(*item));
if (!item) {
goto err;
}
- status = ie_exec_network_create_infer_request(ov_model->exe_network, &request);
+
+ status = ie_exec_network_create_infer_request(ov_model->exe_network, &item->infer_request);
if (status != OK) {
av_freep(&item);
goto err;
}
- item->infer_request = request;
+
+ item->tasks = av_malloc_array(ctx->options.batch_size, sizeof(*item->tasks));
+ if (!item->tasks) {
+ av_freep(&item);
+ goto err;
+ }
+ item->task_count = 0;
+
item->callback.completeCallBackFunc = infer_completion_callback;
item->callback.args = item;
if (ff_safe_queue_push_back(ov_model->request_queue, item) < 0) {
@@ -469,6 +538,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
OVContext *ctx = &ov_model->ctx;
TaskItem task;
RequestItem request;
+ TaskItem *ptask = &task;
if (!in_frame) {
av_log(ctx, AV_LOG_ERROR, "in frame is NULL when execute model.\n");
@@ -487,6 +557,11 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
return DNN_ERROR;
}
+ if (ctx->options.batch_size > 1) {
+ av_log(ctx, AV_LOG_ERROR, "do not support batch mode for sync execution.\n");
+ return DNN_ERROR;
+ }
+
task.done = 0;
task.do_ioproc = 1;
task.async = 0;
@@ -497,8 +572,10 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
task.ov_model = ov_model;
request.infer_request = ov_model->infer_request;
+ request.task_count = 1;
+ request.tasks = &ptask;
- return execute_model_ov(&task, &request);
+ return execute_model_ov(&request);
}
DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char *input_name, AVFrame *in_frame,
@@ -545,7 +622,8 @@ DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char *i
return DNN_ERROR;
}
- return execute_model_ov(task, request);
+ request->tasks[request->task_count++] = task;
+ return execute_model_ov(request);
}
DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame **in, AVFrame **out)
@@ -569,6 +647,48 @@ DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame **i
return DAST_SUCCESS;
}
+DNNReturnType ff_dnn_flush_ov(const DNNModel *model)
+{
+ OVModel *ov_model = (OVModel *)model->model;
+ OVContext *ctx = &ov_model->ctx;
+ RequestItem *request;
+ IEStatusCode status;
+ DNNReturnType ret;
+
+ 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;
+ }
+
+ if (request->task_count == 0) {
+ // no pending task need to flush
+ if (ff_safe_queue_push_back(ov_model->request_queue, request) < 0) {
+ av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
+ return DNN_ERROR;
+ }
+ return DNN_SUCCESS;
+ }
+
+ ret = fill_model_input_ov(ov_model, request);
+ if (ret != DNN_SUCCESS) {
+ av_log(ctx, AV_LOG_ERROR, "Failed to fill model input.\n");
+ return ret;
+ }
+ status = ie_infer_set_completion_callback(request->infer_request, &request->callback);
+ if (status != OK) {
+ av_log(ctx, AV_LOG_ERROR, "Failed to set completion callback for inference\n");
+ return DNN_ERROR;
+ }
+ status = ie_infer_request_infer_async(request->infer_request);
+ if (status != OK) {
+ av_log(ctx, AV_LOG_ERROR, "Failed to start async inference\n");
+ return DNN_ERROR;
+ }
+
+ return DNN_SUCCESS;
+}
+
void ff_dnn_free_model_ov(DNNModel **model)
{
if (*model){
@@ -578,12 +698,15 @@ void ff_dnn_free_model_ov(DNNModel **model)
if (item && item->infer_request) {
ie_infer_request_free(&item->infer_request);
}
+ av_freep(&item->tasks);
av_freep(&item);
}
ff_safe_queue_destroy(ov_model->request_queue);
while (ff_queue_size(ov_model->task_queue) != 0) {
TaskItem *item = ff_queue_pop_front(ov_model->task_queue);
+ av_frame_free(&item->in_frame);
+ av_frame_free(&item->out_frame);
av_freep(&item);
}
ff_queue_destroy(ov_model->task_queue);
diff --git a/libavfilter/dnn/dnn_backend_openvino.h b/libavfilter/dnn/dnn_backend_openvino.h
index 1b70150040..23b819440e 100644
--- a/libavfilter/dnn/dnn_backend_openvino.h
+++ b/libavfilter/dnn/dnn_backend_openvino.h
@@ -36,6 +36,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char *input_name, AVFrame *in_frame,
const char **output_names, uint32_t nb_output, AVFrame *out_frame);
DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame **in, AVFrame **out);
+DNNReturnType ff_dnn_flush_ov(const DNNModel *model);
void ff_dnn_free_model_ov(DNNModel **model);
diff --git a/libavfilter/dnn/dnn_interface.c b/libavfilter/dnn/dnn_interface.c
index e1b41a21e1..02e532fc1b 100644
--- a/libavfilter/dnn/dnn_interface.c
+++ b/libavfilter/dnn/dnn_interface.c
@@ -60,6 +60,7 @@ DNNModule *ff_get_dnn_module(DNNBackendType backend_type)
dnn_module->execute_model = &ff_dnn_execute_model_ov;
dnn_module->execute_model_async = &ff_dnn_execute_model_async_ov;
dnn_module->get_async_result = &ff_dnn_get_async_result_ov;
+ dnn_module->flush = &ff_dnn_flush_ov;
dnn_module->free_model = &ff_dnn_free_model_ov;
#else
av_freep(&dnn_module);
diff --git a/libavfilter/dnn_interface.h b/libavfilter/dnn_interface.h
index 9533c88829..ff338ea084 100644
--- a/libavfilter/dnn_interface.h
+++ b/libavfilter/dnn_interface.h
@@ -82,6 +82,8 @@ typedef struct DNNModule{
const char **output_names, uint32_t nb_output, AVFrame *out_frame);
// Retrieve inference result.
DNNAsyncStatusType (*get_async_result)(const DNNModel *model, AVFrame **in, AVFrame **out);
+ // Flush all the pending tasks.
+ DNNReturnType (*flush)(const DNNModel *model);
// Frees memory allocated for model.
void (*free_model)(DNNModel **model);
} DNNModule;
diff --git a/libavfilter/vf_dnn_processing.c b/libavfilter/vf_dnn_processing.c
index fff5696a31..240614fe65 100644
--- a/libavfilter/vf_dnn_processing.c
+++ b/libavfilter/vf_dnn_processing.c
@@ -33,6 +33,7 @@
#include "formats.h"
#include "internal.h"
#include "libswscale/swscale.h"
+#include "libavutil/time.h"
typedef struct DnnProcessingContext {
const AVClass *class;
@@ -369,6 +370,37 @@ static int activate_sync(AVFilterContext *filter_ctx)
return FFERROR_NOT_READY;
}
+static int flush_frame(AVFilterLink *outlink, int64_t pts, int64_t *out_pts)
+{
+ DnnProcessingContext *ctx = outlink->src->priv;
+ int ret;
+ DNNAsyncStatusType async_state;
+
+ ret = (ctx->dnn_module->flush)(ctx->model);
+ if (ret != DNN_SUCCESS) {
+ return -1;
+ }
+
+ do {
+ AVFrame *in_frame = NULL;
+ AVFrame *out_frame = NULL;
+ async_state = (ctx->dnn_module->get_async_result)(ctx->model, &in_frame, &out_frame);
+ if (out_frame) {
+ if (isPlanarYUV(in_frame->format))
+ copy_uv_planes(ctx, out_frame, in_frame);
+ av_frame_free(&in_frame);
+ ret = ff_filter_frame(outlink, out_frame);
+ if (ret < 0)
+ return ret;
+ if (out_pts)
+ *out_pts = out_frame->pts + pts;
+ }
+ av_usleep(5000);
+ } while (async_state >= DAST_NOT_READY);
+
+ return 0;
+}
+
static int activate_async(AVFilterContext *filter_ctx)
{
AVFilterLink *inlink = filter_ctx->inputs[0];
@@ -396,7 +428,7 @@ static int activate_async(AVFilterContext *filter_ctx)
av_frame_copy_props(out, in);
if ((ctx->dnn_module->execute_model_async)(ctx->model, ctx->model_inputname, in,
(const char **)&ctx->model_outputname, 1, out) != DNN_SUCCESS) {
- return FFERROR_NOT_READY;
+ return AVERROR(EIO);
}
}
} while (ret > 0);
@@ -423,14 +455,16 @@ static int activate_async(AVFilterContext *filter_ctx)
if (ff_inlink_acknowledge_status(inlink, &status, &pts)) {
if (status == AVERROR_EOF) {
- ff_outlink_set_status(outlink, status, pts);
+ int64_t out_pts = pts;
+ ret = flush_frame(outlink, pts, &out_pts);
+ ff_outlink_set_status(outlink, status, out_pts);
return ret;
}
}
FF_FILTER_FORWARD_WANTED(outlink, inlink);
- return FFERROR_NOT_READY;
+ return 0;
}
static int activate(AVFilterContext *filter_ctx)
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