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About low training speed with fewer gpus. #6

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wenhe-jia opened this issue Aug 12, 2019 · 0 comments
Open

About low training speed with fewer gpus. #6

wenhe-jia opened this issue Aug 12, 2019 · 0 comments

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@wenhe-jia
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wenhe-jia commented Aug 12, 2019

I tried to train Grid R-CNN with grid_rcnn_r50_fpn_2x.py, I used 4 gpus, setting lr=0.01 and warmup_iters=14660(2 epochs) 。The training goes well for now except that the training speed is very slow, about 2.2s/iter.

2019-08-12 23:29:06,094 - INFO - Epoch [2][4350/14659]  lr: 0.01000, eta: 8 days, 9:38:37, time: 2.414, data_time: 0.129, memory: 4836, loss_rpn_cls: 0.0598, loss_rpn_reg: 0.0411, loss_cls: 0.3345, acc: 89.5898, loss_grid: 0.6875, loss: 1.1229
2019-08-12 23:31:04,507 - INFO - Epoch [2][4400/14659]  lr: 0.01000, eta: 8 days, 9:41:07, time: 2.369, data_time: 0.134, memory: 4836, loss_rpn_cls: 0.0570, loss_rpn_reg: 0.0407, loss_cls: 0.3127, acc: 90.7246, loss_grid: 0.6755, loss: 1.0860
2019-08-12 23:32:52,252 - INFO - Epoch [2][4450/14659]  lr: 0.01000, eta: 8 days, 9:40:22, time: 2.155, data_time: 0.120, memory: 4836, loss_rpn_cls: 0.0632, loss_rpn_reg: 0.0409, loss_cls: 0.3332, acc: 90.3809, loss_grid: 0.6859, loss: 1.1231

My virtual environment is based on Anaconda 4.7, other system settings are as below:
Ubuntu 14.04
Pytorch 1.1
Python 3.7
CUDA 10.0
GCC 5.4
Need some help, thx.

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