I downloaded tlt-converter the DLA enabled version in order to generate an engine to utilize DLAs in the AGX.
I used maskrcnn that i retrained with COCO dataset using TLT v3.0.
The engine generation process failed and resulted in segmentation fault. I attached the log for the error
log.txt (61.1 KB)
Also, according to this blog here , Using the DLAs along with the GPU should give a performance boost, but when i attempted the DLA engine creation, alot of layers were not DLA enabled and fell back to the GPU and as far as i understand, this should actually hinder the GPU. So is there a certain way the benchmark in the blog was done?
Any help would be appreciated,
• Hardware: AGX Xavier
• Network Type: Mask_rcnn
• TLT Version: docker v3.0-py3