Need some help. I don't understand some code.

[KeyKy]

Due to my poor skill of pytorch. I found this code in your encodenet.py

# Conv_1
model += [nn.Conv2d(3, self.inplanes, kernel_size=3, padding=1),
					nn.BatchNorm2d(self.inplanes),
					nn.ReLU(inplace=True)]
# Residual units
for i in range(4):
	model += [self._residual_unit(block, num_planes[i], num_blocks[i],
						strides[i])]
# Last conv layer
# TODO norm layer, instance norm?
model += [nn.BatchNorm2d(self.inplanes),
			nn.ReLU(inplace=True),
			Encoding(D=512*self.expansion,K=16),
			nn.BatchNorm1d(16),
			nn.ReLU(inplace=True),
			nn2.View(-1, 512*self.expansion*16),
			nn.Linear(512*self.expansion*16, num_classes)]
self.model = nn.Sequential(*model)

What's the input of Encoding(D=512*self.expansion,K=16). I found your encode kernel which only accept 2 tensor(A,R) and where are the X, C and A?
Although R = X - C, I don't find the X - C in your model

[zhanghang1989]

Please see the module file:
https://github.com/zhanghang1989/PyTorch-Encoding-Layer/blob/master/encoding/__init__.py#L68

[KeyKy]

Thx!