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The larger tile shape results lower speed in finetuning. #73
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Factor 10 slower is expected with factor 10 larger input, everything above is overhead from data augmentation and transfer. The number of iterations may be affected by input shape but I would not in general say the bigger the better. I usually train with relatively small tiles and batch size one to increase randomness. Curves become wiggly but output is quite robust. |
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Hello, my GPU is Tesla V100-32G, when I use 508x508 tile shape as you did in the tutorial video, the speed is somewhat well, but when I use 1500x1500 tile shape, the estimated memory is about 18G, less than my GPU's limit, but the speed is quite slow. I'm not familar with caffe, so I thought larger tile shape is good for accelerating the finetuning, is it right?
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