involution卷积替换问题

[right135]

up，最近看了一些论文显示involution卷积效果不错，想来替换试试，但是involution官方代码，参数和yolox的不太匹配，调整了好久都一直报错，能麻烦up指点一下 参数该如何修改呢qwq？
import torch.nn as nn
from mmcv.cnn import ConvModule

class involution(nn.Module):

def __init__(self,
             channels,
             kernel_size,
             stride):
    super(involution, self).__init__()
    self.kernel_size = kernel_size
    self.stride = stride
    self.channels = channels
    reduction_ratio = 4
    self.group_channels = 16
    self.groups = self.channels // self.group_channels
    self.conv1 = ConvModule(
        in_channels=channels,
        out_channels=channels // reduction_ratio,
        kernel_size=1,
        conv_cfg=None,
        norm_cfg=dict(type='BN'),
        act_cfg=dict(type='ReLU'))
    self.conv2 = ConvModule(
        in_channels=channels // reduction_ratio,
        out_channels=kernel_size**2 * self.groups,
        kernel_size=1,
        stride=1,
        conv_cfg=None,
        norm_cfg=None,
        act_cfg=None)
    if stride > 1:
        self.avgpool = nn.AvgPool2d(stride, stride)
    self.unfold = nn.Unfold(kernel_size, 1, (kernel_size-1)//2, stride)

def forward(self, x):
    weight = self.conv2(self.conv1(x if self.stride == 1 else self.avgpool(x)))
    b, c, h, w = weight.shape
    weight = weight.view(b, self.groups, self.kernel_size**2, h, w).unsqueeze(2)
    out = self.unfold(x).view(b, self.groups, self.group_channels, self.kernel_size**2, h, w)
    out = (weight * out).sum(dim=3).view(b, self.channels, h, w)
    return out

[right135]

就只有一个参数不一样，那就是involution只有一个channels，而up的代码有in_channels和out_channels，我尝试的时候是把out_channels去掉了，然后就报错了。

[bubbliiiing]

通道写错了而已

[right135]

嘶，是我的通道写错了吗？没太懂qwq，那应该写成什么呀，out_channels?