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LMMMEng / TransXNet

TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition

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A question about throughput

SanmAIGO opened this issue · comments

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When I use the Train.py file in my project to train my dataset, I find that the training speed of TransXNet is much slower than models with similar parameter counts, such as PVT_V2, to the point where I believe my server is stuck. I encounter the same issue when using my own training script. Why is this happening? The data is fine because the timm library can train correctly.