更改网络结构后该如何进行剪枝

[Hazel-Xiang]

作者大大，我想试着在yolov5结构的head和backbone里加入一些小的优化结构，在稀疏训练后，进行prune.py的时候报了错，按照错误修改yolo.py时遇见一些问题，请问作者大大def parse_pruned_model应该怎么修改呢？拜托作者大大了，请指教一下应该怎么修改和修改的思路！万分感谢！ ![Uploading image.png…]()

commom.py中Concat_bifpn结构如下： ![Uploading image.png…]()

[Hazel-Xiang]

def parse_pruned_model

[Hazel-Xiang]

commom.py中Concat_bifpn结构如下：

[Hazel-Xiang]

yolov5s_bifpn.yaml结构如下：

parameters

nc: 2 # number of classes depth_multiple: 0.33 # model depth multiple width_multiple: 0.50 # layer channel multiple

anchors

anchors:

• [10,13, 16,30, 33,23] # P3/8
• [30,61, 62,45, 59,119] # P4/16
• [116,90, 156,198, 373,326] # P5/32

YOLOv5 backbone

backbone:

[from, number, module, args]

[[-1, 1, Focus, [64, 3]], # 0-P1/2 [-1, 1, Conv, [128, 3, 2]], # 1-P2/4 [-1, 3, C3, [128]], [-1, 1, Conv, [256, 3, 2]], # 3-P3/8 [-1, 9, C3, [256]], [-1, 1, Conv, [512, 3, 2]], # 5-P4/16 [-1, 9, C3, [512]], [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32 [-1, 1, SPP, [1024, [5, 9, 13]]], [-1, 3, C3, [1024, False]], # 9 ]

YOLOv5 head

head: [[-1, 1, Conv, [512, 1, 1]], [-1, 1, nn.Upsample, [None, 2, 'nearest']], [[-1,6], 1, Concat_bifpn, [256,256]], # cat backbone P4 [-1, 3, C3, [512, False]], # 13

[-1, 1, Conv, [256, 1, 1]], [-1, 1, nn.Upsample, [None, 2, 'nearest']], [[-1, 4], 1, Concat_bifpn, [128,128]], # cat backbone P3 [-1, 3, C3, [256, False]], # 17 (P3/8-small)

[-1, 1, Conv, [512, 3, 2]], # 320, 640 # [[-1, 6, 13], 1, Concat_bifpn, [256,256]], # cat head P4 [-1, 3, C3, [512, False]], # 20 (P4/16-medium)

[-1, 1, Conv, [1024, 3, 2]], # 640, 1280 # [[-1, 9], 1, Concat_bifpn, [512, 512]], # cat head P5 cat 20,20 #22 [-1, 3, C3, [1024, False]], # 25 (P5/32-large) # 1280, 1280 #23

[[17, 20, 23], 1, Detect, [nc, anchors]] # Detect(P3, P4, P5) ]

[zxsitu]

Hello @Hazel-Xiang , how did you finish the pruning? What is the code modification idea?

[hahaqiu123]

你好，请问你有解决方法了吗？我现在也困在这里