pytorch Sequential的使用

class Model_test(nn.Module):
	def __init__(self):
		super(Model_test, self).__init__()
		self.conv1 = Conv2d(3, 32,5，padding=2)  # in_C， out_c， kernel_size
		self.maxpool1 = MaxPool2d(2)
		self.conv2 = Conv2d(32, 32,5，padding=2)  # in_C， out_c， kernel_size
		self.maxpool2 = MaxPool2d(2)
		self.conv3 = Conv2d(32, 64,5，padding=2)  # in_C， out_c， kernel_size
		self.maxpool3 = MaxPool2d(2)
		self.flatten = Flatten()
		self.liear1 = Linear(1024, 64)
		self.liear2 = Linear(64, 10)
		
		self.model1 = Sequential(
		Conv2d(3, 32,5，padding=2),
		MaxPool2d(2),
		Conv2d(32, 32,5，padding=2),
		MaxPool2d(2),
		Flatten(),
		Linear(1024, 64),
		Linear(64, 10))
		
	def forward(self, x):
		x = self.conv1(x)
		x = self.maxpool1 (x)
		x = self.conv2(x)
		x = self.maxpool2 (x)
		x = self.conv3(x)
		x = self.flatten(x)
		x = self.liear1(x)
		x = self.liear2(x)
		
		x = self.model1(x)
		return x

model_test = Module_test()
input = torch.ones(64,3,32,32)
output = model_test(input)
	


writer = SummaryWriter("logs_Sequential")	
writer.add_graph(model_test, input)
writer.close()

#terminal :tensorboard --logdir=logs_Sequential