yangzhikai

@albertpumarola I have try pytorch 0.3.1,but it encounter a error in "display visualizer". Then I modified ganimation.py in Iine-346 def get_current_visuals(self): , and add "np.transpose(image_numpy,(2,0,1))" after numpy of OrderedDict()。 OR...

666，你们看懂程序了没？剪出来一般多大啊。

@hewumars values = torch.sum((activation * grad), dim = 0). sum(dim=2).sum(dim=3)[0, :, 0, 0].data 这个问题怎么解决的啊。我知道要SUM出Channel可以这么写： torch.sum((activation * grad), dim = 0). sum(dim=1).sum(dim=2)。但是后面维度扩展该怎么办啊。

Are you programming the code using python2.7? The usage of ordered dictionaries is not correct. like: x = self.model.features._modules.items()[layer][1][kt].bn1(x)

@eeric Ordered dictionary In python3 cannot execute this operation：new_conv = self.model.features._modules.items()[layer][1][kt].bn1。And I try a command like : new_conv = model._modules['4'][0].conv1 。That may be achieve the same effect. But I'm not...

as I running the code, I found that accuracy useing layers respectively is lower than useing a sequencial model which layers in it. Do you encounter this problem? For instance...