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dnn_backend_native_layer_conv2d.c: refine code.

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Move thread area allocate out of thread function into
main thread.

Signed-off-by: Xu Jun <xujunzz@sjtu.edu.cn>
This commit is contained in:
Xu Jun 2020-09-16 18:07:19 +08:00 committed by Guo, Yejun
parent 8e67ae2cb4
commit 7d3cd9f956
1 changed files with 14 additions and 16 deletions
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30
libavfilter/dnn/dnn_backend_native_layer_conv2d.c
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@ -33,12 +33,11 @@ typedef struct thread_common_param{
const void *parameters;
NativeContext *ctx;
float *output_data;
int thread_num;
} thread_common_param;
typedef struct thread_param{
thread_common_param *thread_common_param;
int thread_index;
int thread_start, thread_end;
} thread_param;
int dnn_load_layer_conv2d(Layer *layer, AVIOContext *model_file_context, int file_size, int operands_num)
@ -125,16 +124,12 @@ static void * dnn_execute_layer_conv2d_thread(void *threadarg)
int filter_size = conv_params->kernel_size * filter_linesize;
int pad_size = (conv_params->padding_method == VALID) ? (conv_params->kernel_size - 1) / 2 * conv_params->dilation : 0;
int thread_stride = (height - pad_size * 2) / thread_common_param->thread_num;
int thread_start = thread_stride * thread_param->thread_index + pad_size;
int thread_end = (thread_param->thread_index == thread_common_param->thread_num - 1) ? (height - pad_size) : (thread_start + thread_stride);
float *output = thread_common_param->output_data;
output += (conv_params->output_num) * (width - 2 * pad_size) * (thread_start - pad_size);
output += (conv_params->output_num) * (width - 2 * pad_size) * (thread_param->thread_start - pad_size);
av_assert0(channel == conv_params->input_num);
for (int y = thread_start; y < thread_end; ++y) {
for (int y = thread_param->thread_start; y < thread_param->thread_end; ++y) {
for (int x = pad_size; x < width - pad_size; ++x) {
for (int n_filter = 0; n_filter < conv_params->output_num; ++n_filter) {
if (conv_params->has_bias)
@ -193,16 +188,19 @@ int dnn_execute_layer_conv2d(DnnOperand *operands, const int32_t *input_operand_
? (av_cpu_count() + 1) : (ctx->options.conv2d_threads);
#if HAVE_PTHREAD_CANCEL
pthread_t *thread_id = av_malloc(thread_num * sizeof(pthread_t));
int thread_stride;
#endif
thread_param **thread_param = av_malloc(thread_num * sizeof(*thread_param));
thread_common_param thread_common_param;
const ConvolutionalParams *conv_params = (const ConvolutionalParams *)(parameters);
int height = operands[input_operand_indexes[0]].dims[1];
int width = operands[input_operand_indexes[0]].dims[2];
int pad_size = (conv_params->padding_method == VALID) ? (conv_params->kernel_size - 1) / 2 * conv_params->dilation : 0;
DnnOperand *output_operand = &operands[output_operand_index];
output_operand->dims[0] = operands[input_operand_indexes[0]].dims[0];
output_operand->dims[1] = operands[input_operand_indexes[0]].dims[1] - pad_size * 2;
output_operand->dims[2] = operands[input_operand_indexes[0]].dims[2] - pad_size * 2;
output_operand->dims[1] = height - pad_size * 2;
output_operand->dims[2] = width - pad_size * 2;
output_operand->dims[3] = conv_params->output_num;
output_operand->data_type = operands[input_operand_indexes[0]].data_type;
output_operand->length = calculate_operand_data_length(output_operand);
@ -223,13 +221,13 @@ int dnn_execute_layer_conv2d(DnnOperand *operands, const int32_t *input_operand_
thread_common_param.ctx = ctx;
#if HAVE_PTHREAD_CANCEL
thread_common_param.thread_num = thread_num;
thread_stride = (height - pad_size * 2) / thread_num;
//create threads
for (int i = 0; i < thread_num; i++){
thread_param[i] = av_malloc(sizeof(**thread_param));
thread_param[i]->thread_common_param = &thread_common_param;
thread_param[i]->thread_index = i;
thread_param[i]->thread_start = thread_stride * i + pad_size;
thread_param[i]->thread_end = (i == thread_num - 1) ? (height - pad_size) : (thread_param[i]->thread_start + thread_stride);
pthread_create(&thread_id[i], NULL, dnn_execute_layer_conv2d_thread, (void *)thread_param[i]);
}
@ -245,10 +243,10 @@ int dnn_execute_layer_conv2d(DnnOperand *operands, const int32_t *input_operand_
av_free(thread_param[i]);
}
#else
thread_common_param.thread_num = 1;
thread_param[0] = av_malloc(sizeof(thread_param));
thread_param[0] = av_malloc(sizeof(**thread_param));
thread_param[0]->thread_common_param = &thread_common_param;
thread_param[0]->thread_index = 0;
thread_param[0]->thread_start = 0;
thread_param[0]->thread_end = height - pad_size;
dnn_execute_layer_conv2d_thread((void *)thread_param[0]);
av_free(thread_param[0]);
#endif