这个ConvNet网络是怎么设计的啊,为什么要这么设计,有参考文献吗? #2

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2020-07-21T14:53:57+08:00

FredyVia commented

2020-07-21 14:53:57 +08:00

(Migrated from github.com)

class ConvNet(nn.Module):
def init(self, num_classes):
super(ConvNet, self).init()
self.conv1 = conv_bn(3, 8, 1) # 64x64x1
self.conv2 = conv_bn(8, 16, 1) # 64x64x16
self.conv3 = conv_dw(16, 32, 1) # 64x64x32
self.conv4 = conv_dw(32, 32, 2) # 32x32x32
self.conv5 = conv_dw(32, 64, 1) # 32x32x64
self.conv6 = conv_dw(64, 64, 2) # 16x16x64
self.conv7 = conv_dw(64, 128, 1) # 16x16x128
self.conv8 = conv_dw(128, 128, 1) # 16x16x128
self.conv9 = conv_dw(128, 128, 1) # 16x16x128
self.conv10 = conv_dw(128, 128, 1) # 16x16x128
self.conv11 = conv_dw(128, 128, 1) # 16x16x128
self.conv12 = conv_dw(128, 256, 2) # 8x8x256
self.conv13 = conv_dw(256, 256, 1) # 8x8x256
self.conv14 = conv_dw(256, 256, 1) # 8x8x256
self.conv15 = conv_dw(256, 512, 2) # 4x4x512
self.conv16 = conv_dw(512, 512, 1) # 4x4x512

class ConvNet(nn.Module): def __init__(self, num_classes): super(ConvNet, self).__init__() self.conv1 = conv_bn(3, 8, 1) # 64x64x1 self.conv2 = conv_bn(8, 16, 1) # 64x64x16 self.conv3 = conv_dw(16, 32, 1) # 64x64x32 self.conv4 = conv_dw(32, 32, 2) # 32x32x32 self.conv5 = conv_dw(32, 64, 1) # 32x32x64 self.conv6 = conv_dw(64, 64, 2) # 16x16x64 self.conv7 = conv_dw(64, 128, 1) # 16x16x128 self.conv8 = conv_dw(128, 128, 1) # 16x16x128 self.conv9 = conv_dw(128, 128, 1) # 16x16x128 self.conv10 = conv_dw(128, 128, 1) # 16x16x128 self.conv11 = conv_dw(128, 128, 1) # 16x16x128 self.conv12 = conv_dw(128, 256, 2) # 8x8x256 self.conv13 = conv_dw(256, 256, 1) # 8x8x256 self.conv14 = conv_dw(256, 256, 1) # 8x8x256 self.conv15 = conv_dw(256, 512, 2) # 4x4x512 self.conv16 = conv_dw(512, 512, 1) # 4x4x512

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Reference: dearsky/hand-writing-recognition#2