Hello. I train one network and save it, then load this network and I partition network to three module and give one images to input of first module and take output from end module but the output of this three module has low resolution… I dont understand why this happened?!!
model = ConvAutoencoder()
max_epochs =10
outputs = train(model, num_epochs=max_epochs)
torch.save(model, 'model1.pth')
model1 = torch.load('model1.pth')
imgs3, labels = next(iter(test_loader))
f= model1(imgs3)
plt.imshow(f[13][0].detach().numpy(), cmap="gray")
l1 = nn.Sequential(*list(model1.children())[:3])
print('l1=',l1)
l2 = nn.Sequential(*list(model1.children())[3:4])
print('l2=',l2)
l3 = nn.Sequential(*list(model1.children())[4:])
print('l3=',l3)
imgs2, labels = next(iter(test_loader))
y1= l1(imgs2)
#y1.shape
y2=l2(y1)
y3=l3(y2)
plt.subplot(1, 2, 1)
plt.imshow(imgs2[13][0].detach().numpy(), cmap="gray")
plt.subplot(1, 2, 2)
plt.imshow(y3[13][0].detach().numpy(), cmap="gray")
