Comments (4)
你看看是不是這個問題 input layer
layer {
name: "data"
type: "Input"
top: "data"
input_param { shape: { dim: 1 dim: 3 dim: 227 dim: 227 } }
}
https://github.com/Tencent/ncnn/blob/8d984f105b1b8f816654ffa7719e96fbd5885971/docs/how-to-use-and-FAQ/use-ncnn-with-alexnet.md
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input layer是这样的,我看我的param
文件,是ConvolutionDepthWise
层后面没有参数。
我把您原始prototxt
文件中的DepthWiseConv
改成了ConvolutionDepthWise
,不改的话无法转换,这样改有没有什么错误?
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其實改成一般的convolution即可,當group = channel 時,Convolution , DepthWiseConv 與 ConvolutionDepthWise 這三種輸出的結果基本沒有差別或差異小到可以忽視,只差在Caffe traing 和 inference的速度。
from mobilenet-yolo.
好的,多谢,我看了一下caffe2ncnn.cpp,应该是ConvolutionDepthwise
,而不是ConvolutionDepthWise
...大小写改完就转换正常啦
感谢您的工作!
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