FTZ and DAZ modes are incorrectly configured for convolution #21046
Description
System information (version)
- OpenCV => 3.4.16/4.5.4
Detailed description
Issue #17259 reported that different weights for the same model architecture showed drastically different performance characteristics. The issue was resolved by enabling FTZ and DAZ for convolution in #17295. The proposed fix is incomplete and incorrect.
- The FPU state is thread-local. The current patch sets the FPU state in the calling thread only. Therefore, most of the worker threads do not have DAZ and FTZ enabled during convolution. (could be responsible for DNN ONNX backend - Slower model when weights are close to 0, trained with Adam Optimizer (Pytorch) #20985)
- It alters the FPU state of the end-user's thread and does not restore it in some cases (early return and exceptions).
Related comment: #17295 (comment)
Steps to reproduce
#include <opencv2/core.hpp>
#include <opencv2/dnn.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <vector>
#include <thread>
#include <xmmintrin.h>
int main ()
{
uint32_t ftzMode = _MM_GET_FLUSH_ZERO_MODE();
uint32_t dazMode = _MM_GET_DENORMALS_ZERO_MODE();
std::cout << "MainThread BEGIN" << std::this_thread::get_id() << " FTZ: " << (ftzMode == _MM_FLUSH_ZERO_ON) << ", DAZ: " << (dazMode == _MM_DENORMALS_ZERO_ON) << std::endl;
auto net = cv::dnn::readNetFromDarknet("yolov4.cfg", "yolov4.weights");
net.setPreferableBackend(cv::dnn::DNN_BACKEND_OPENCV);
net.setPreferableTarget(cv::dnn::DNN_TARGET_OPENCL);
auto frame = cv::imread("dog.jpg");
auto blob = cv::dnn::blobFromImage(frame, 0.00392, cv::Size(608, 608), cv::Scalar(), true, false, CV_32F);
net.setInput(blob);
auto output_names = net.getUnconnectedOutLayersNames();
std::vector<cv::Mat> detections;
net.forward(detections, output_names);
ftzMode = _MM_GET_FLUSH_ZERO_MODE();
dazMode = _MM_GET_DENORMALS_ZERO_MODE();
std::cout << "MainThread END" << std::this_thread::get_id() << "FTZ: " << (ftzMode == _MM_FLUSH_ZERO_ON) << ", DAZ: " << (dazMode == _MM_DENORMALS_ZERO_ON) << std::endl;
return 0;
}
In addition, I have added the following under a lock in operator() of ParallelConv.
std::cout << "ConvThread " << std::this_thread::get_id() << "FTZ: " << (ftzMode == _MM_FLUSH_ZERO_ON) << ", DAZ: " << (dazMode == _MM_DENORMALS_ZERO_ON) << std::endl;
Problem I: FPU state only set in the calling thread
MainThread BEGIN 140152961351680 FTZ: 0, DAZ: 0
ConvThread 140152676220928 FTZ: 0, DAZ: 0
ConvThread 140152567492608 FTZ: 0, DAZ: 0
ConvThread 140152659435520 FTZ: 0, DAZ: 0
ConvThread 140152961351680 FTZ: 1, DAZ: 1
ConvThread 140152559099904 FTZ: 0, DAZ: 0
ConvThread 140152550707200 FTZ: 0, DAZ: 0
ConvThread 140152651042816 FTZ: 0, DAZ: 0
ConvThread 140152667828224 FTZ: 0, DAZ: 0
.
.
.
MainThread END 140152961351680 FTZ: 0, DAZ: 0
Problem 2: net.forward() does not preserve calling thread's FPU state
This issue arises when there is an early return (happens in OCL target) or an exception is thrown. The current mechanism manually manages the FPU state setting and resetting. An RAII-based solution is appropriate here.
I don't have OCL configured to test but I strongly suspect this is the case.
Issue submission checklist
- I report the issue, it's not a question
- I checked the problem with documentation, FAQ, open issues,
forum.opencv.org, Stack Overflow, etc and have not found solution - I updated to latest OpenCV version and the issue is still there
- There is reproducer code and related data files: videos, images, onnx, etc