MobileNetv2优化问题

LinearBottleneck

优化时，把卷积层2去掉时，执行速度1.2s，加上卷积层2时，执行速度是0.2s，

加卷积后；

torch.Size([1, 960, 7, 7])

去掉卷积层2后；shape

torch.Size([1, 960, 112, 112])

导致了速度变慢。

class LinearBottleneck(nn.Module):
    def __init__(self, inplanes, outplanes, stride=1, t=6, activation=nn.ReLU6):
        super(LinearBottleneck, self).__init__()
        self.conv1 = nn.Conv2d(inplanes, inplanes * t, kernel_size=1, bias=False)
        self.bn1 = nn.BatchNorm2d(inplanes * t)
        self.conv2 = nn.Conv2d(inplanes * t, inplanes * t, kernel_size=3, stride=stride, padding=1, bias=False,
                               groups=inplanes * t)
        self.bn2 = nn.BatchNorm2d(inplanes * t)
        self.conv3 = nn.Conv2d(inplanes * t, outplanes, kernel_size=1, bias=False)
        self.bn3 = nn.BatchNorm2d(outplanes)
        self.activation = activation(inplace=True)
        self.stride = stride
        self.t = t
        self.inplanes = inplanes
        self.outplanes = outplanes

    def forward(self, x):
        residual = x

        out = self.conv1(x)
        out = self.bn1(out)
        out = self.activation(out)

        out = self.conv2(out)
        out = self.bn2(out)
        out = self.activation(out)

        out = self.conv3(out)
        out = self.bn3(out)

        if self.stride == 1 and self.inplanes == self.outplanes:
            out += residual

        return out