pytorch 训练数据以及测试 全部代码(7) 网络

ASPP网络

[code]class ASPP_module(nn.Module):
def __init__(self, inplanes, planes, rate):
pass
def forward(self, x):
pass
def _init_weight(self):
pass

第一个函数

[code]    def __init__(self, inplanes, planes, rate):
super(ASPP_module, self).__init__()
if rate == 1:
kernel_size = 1
padding = 0
else:
kernel_size = 3
padding = rate
self.atrous_convolution = nn.Conv2d(inplanes, planes, kernel_size=kernel_size,
stride=1, padding=padding, dilation=rate, bias=False)
self.bn = nn.BatchNorm2d(planes)
self.relu = nn.ReLU()

self._init_weight()

里面的_init_weight()如下：初始化

[code]    def _init_weight(self):
for m in self.modules():
if isinstance(m, nn.Conv2d):
# n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
# m.weight.data.normal_(0, math.sqrt(2. / n))
torch.nn.init.kaiming_normal_(m.weight)
elif isinstance(m, nn.BatchNorm2d):
m.weight.data.fill_(1)
m.bias.data.zero_()

然后是forward函数：

[code]    def forward(self, x):
x = self.atrous_convolution(x)
x = self.bn(x)

return self.relu(x)

上述就是ASPP网络