nn.Upsample()
is depecated in pytorch version > 0.4.0
in favor of nn.functional.interpolate()
I’m not able to use interpolate()
inside nn.Sequential()
:
Below is my network:
class MeeDecoder(torch.nn.Module):
def __init__(self):
super(MeeDecoder, self).__init__()
self.de_layer1 = torch.nn.Conv2d(in_channels=40, out_channels=30, kernel_size=(1,1), stride=1, bias=True)
self.de_layer2 = torch.nn.Conv2d(in_channels=30, out_channels=20, kernel_size=(1,1), stride=1, bias=True)
self.de_layer3 = torch.nn.functional.interpolate(size=(205, 5), mode='bilinear')
self.de_layer4 = torch.nn.Conv2d(in_channels=20, out_channels=12, kernel_size=(3,3), stride=1, bias=True)
self.de_layer5 = torch.nn.Upsample(size=(1025, 15), mode='bilinear')
self.de_layer6 = torch.nn.Conv2d(in_channels=12, out_channels=1, kernel_size=(1,1), stride=1, bias=True)
self.de_layerReLU = torch.nn.ReLU()
self.decoder = torch.nn.Sequential(
self.de_layer1,
self.de_layerReLU,
self.de_layer2,
self.de_layerReLU,
self.de_layer3,
self.de_layer4,
self.de_layerReLU,
self.de_layer5,
self.de_layer6,
self.de_layerReLU
)
def forward(self, x):
return self.decoder(x)
Any help.
Thanks