Comments (1)
As long as the model structure and the channel number of each split is the same, there is no difference between different code style, and there should be no difference in performance.
I didn't check those third party implementations and cannot guarantee that their codes are right.
Width/baseWidth is just used to control the channel number in each split. We just follow the previous works such as Res2NeXt to use this code style.
from res2net-pretrainedmodels.
Related Issues (20)
- tensorflow,keras预训练版本 HOT 2
- width = int(math.floor(planes * (baseWidth/64.0)))
- Can res2net have a basic block structure? HOT 6
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- 提供的Res2Net-v1b-50预训练模型与mmdetection不完全匹配
- 维度不匹配 HOT 2
- What is baseWidth? HOT 3
- About stype.stage HOT 3
- How to determine the width parameter HOT 1
- About ResNet18? HOT 3
- 张量尺寸不匹配问题 HOT 1
- why don't have the Res2Net-v1b-200-SSLD model code ? HOT 1
- 26是否可以替换成其他更小数值 HOT 2
- res2net50-v1b的训练策略 HOT 2
- About SSLD pretrained model HOT 3
- 对于每一个layer的第一个block,计算方式不是层级的,和论文中描述有差别 HOT 3
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- self-supervised training on Imagenet
- 代码中的残差结构和图像中不一致 HOT 1
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from res2net-pretrainedmodels.