Comments (5)
使用2个1080ti的情况下
只有调整batch_size=4
input size=378*378
才不会出现这个问题。。
但是效果就不好
from cosnet.
有同样的问题,你是怎莫解决的
from cosnet.
有同样的问题,你是怎莫解决的
我就用了4个1080ti,把batchsize设置成8 但是效果还是比作者batchsize=16的模型差了约2%
顺便问一下你调整reference frame和使用crf结果会有差距吗?我测试的结果没有差距 很奇怪
from cosnet.
有同样的问题,你是怎莫解决的
我就用了4个1080ti,把batchsize设置成8 但是效果还是比作者batchsize=16的模型差了约2%
顺便问一下你调整reference frame和使用crf结果会有差距吗?我测试的结果没有差距 很奇怪
能加个qq交流一下吗,我猜是因为你的4路1080ti的问题。作者应该是用了两个24gram的Titan,因为你这样训练相当于每个GPU上只有两个在做BN,一般至少四个。没看见作者代码里写了跨GPU的BN。而且1080ti的图片size必须得限制到378以下。我的qq是2667004002
from cosnet.
@NoaHimesaka 您好,方便询问一些训练细节吗。我的qq是61758265
from cosnet.
Related Issues (20)
- About sample_range parameter
- AttributeError: 'CoattentionModel' object has no attribute 'main_classifier' HOT 5
- Error after filling a val_seqs.txt HOT 1
- about the attention in CoattentionModel HOT 2
- 关于训练得到的co_attention.pth问题 HOT 2
- 测试代码问题 HOT 4
- 训练阶段创建的saliency_data.txt问题 HOT 4
- why don't the test code correspondes to paper HOT 1
- Can you provide the source image and GT of The Youtube-Objects?
- 数据集文件夹结构
- CRF postprocessing code
- Could you upload pretrained weight again onto BaiduNetdisk?
- 测试输出异常
- A BIG final LOSS value HOT 1
- Using Group attention get worse result
- Segmentation result
- About FBMS evaluation
- Hi! Where is the pretrained model of your MATNet?
- where is saliency_data.txt
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from cosnet.