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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.
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
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System information (version)
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.
Related comment: #17295 (comment)
Steps to reproduce
In addition, I have added the following under a lock in
operator()
ofParallelConv
.Problem I: FPU state only set in the calling thread
Problem 2:
net.forward()
does not preserve calling thread's FPU stateThis 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
forum.opencv.org, Stack Overflow, etc and have not found solution
The text was updated successfully, but these errors were encountered: