dnn_backend_native_layer_conv2d.c: refine code with av_malloc_array and av_freep
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
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@ -70,7 +70,7 @@ int dnn_load_layer_conv2d(Layer *layer, AVIOContext *model_file_context, int fil
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return 0;
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return 0;
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}
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}
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conv_params->kernel = av_malloc(kernel_size * sizeof(float));
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conv_params->kernel = av_malloc_array(kernel_size, sizeof(*conv_params->kernel));
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if (!conv_params->kernel) {
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if (!conv_params->kernel) {
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av_freep(&conv_params);
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av_freep(&conv_params);
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return 0;
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return 0;
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@ -81,7 +81,7 @@ int dnn_load_layer_conv2d(Layer *layer, AVIOContext *model_file_context, int fil
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conv_params->biases = NULL;
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conv_params->biases = NULL;
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if (conv_params->has_bias) {
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if (conv_params->has_bias) {
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conv_params->biases = av_malloc(conv_params->output_num * sizeof(float));
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conv_params->biases = av_malloc_array(conv_params->output_num, sizeof(*conv_params->biases));
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if (!conv_params->biases){
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if (!conv_params->biases){
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av_freep(&conv_params->kernel);
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av_freep(&conv_params->kernel);
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av_freep(&conv_params);
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av_freep(&conv_params);
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@ -187,10 +187,10 @@ int dnn_execute_layer_conv2d(DnnOperand *operands, const int32_t *input_operand_
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int thread_num = (ctx->options.conv2d_threads <= 0 || ctx->options.conv2d_threads > av_cpu_count())
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int thread_num = (ctx->options.conv2d_threads <= 0 || ctx->options.conv2d_threads > av_cpu_count())
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? (av_cpu_count() + 1) : (ctx->options.conv2d_threads);
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? (av_cpu_count() + 1) : (ctx->options.conv2d_threads);
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#if HAVE_PTHREAD_CANCEL
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#if HAVE_PTHREAD_CANCEL
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pthread_t *thread_id = av_malloc(thread_num * sizeof(pthread_t));
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pthread_t *thread_id = av_malloc_array(thread_num, sizeof(*thread_id));
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int thread_stride;
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int thread_stride;
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#endif
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#endif
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ThreadParam **thread_param = av_malloc(thread_num * sizeof(*thread_param));
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ThreadParam **thread_param = av_malloc_array(thread_num, sizeof(*thread_param));
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ThreadCommonParam thread_common_param;
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ThreadCommonParam thread_common_param;
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const ConvolutionalParams *conv_params = (const ConvolutionalParams *)(parameters);
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const ConvolutionalParams *conv_params = (const ConvolutionalParams *)(parameters);
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int height = operands[input_operand_indexes[0]].dims[1];
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int height = operands[input_operand_indexes[0]].dims[1];
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@ -224,7 +224,7 @@ int dnn_execute_layer_conv2d(DnnOperand *operands, const int32_t *input_operand_
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thread_stride = (height - pad_size * 2) / thread_num;
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thread_stride = (height - pad_size * 2) / thread_num;
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//create threads
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//create threads
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for (int i = 0; i < thread_num; i++){
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for (int i = 0; i < thread_num; i++){
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thread_param[i] = av_malloc(sizeof(**thread_param));
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thread_param[i] = av_malloc(sizeof(*thread_param[0]));
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thread_param[i]->thread_common_param = &thread_common_param;
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thread_param[i]->thread_common_param = &thread_common_param;
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thread_param[i]->thread_start = thread_stride * i + pad_size;
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thread_param[i]->thread_start = thread_stride * i + pad_size;
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thread_param[i]->thread_end = (i == thread_num - 1) ? (height - pad_size) : (thread_param[i]->thread_start + thread_stride);
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thread_param[i]->thread_end = (i == thread_num - 1) ? (height - pad_size) : (thread_param[i]->thread_start + thread_stride);
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@ -237,20 +237,20 @@ int dnn_execute_layer_conv2d(DnnOperand *operands, const int32_t *input_operand_
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}
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}
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//release memory
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//release memory
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av_free(thread_id);
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av_freep(&thread_id);
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for (int i = 0; i < thread_num; i++){
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for (int i = 0; i < thread_num; i++){
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av_free(thread_param[i]);
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av_freep(&thread_param[i]);
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}
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}
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#else
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#else
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thread_param[0] = av_malloc(sizeof(**thread_param));
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thread_param[0] = av_malloc(sizeof(*thread_param[0]));
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thread_param[0]->thread_common_param = &thread_common_param;
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thread_param[0]->thread_common_param = &thread_common_param;
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thread_param[0]->thread_start = pad_size;
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thread_param[0]->thread_start = pad_size;
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thread_param[0]->thread_end = height - pad_size;
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thread_param[0]->thread_end = height - pad_size;
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dnn_execute_layer_conv2d_thread((void *)thread_param[0]);
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dnn_execute_layer_conv2d_thread((void *)thread_param[0]);
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av_free(thread_param[0]);
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av_freep(&thread_param[0]);
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#endif
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#endif
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av_free(thread_param);
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av_freep(&thread_param);
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return DNN_SUCCESS;
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return DNN_SUCCESS;
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}
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}
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