def forward(self, x: Tensor) -> Tensor:
if self.stride == 1:
x1, x2 = x.chunk(2, dim=1)
out = self.cat.cat([x1, self.branch2(x2)], dim=1)
else:
out = self.cat.cat([self.branch1(x), self.branch2(x)], dim=1)
out = shufflenetv2.channel_shuffle(out, 2)
return out
def forward(self, x):
if self.stride == 1:
x1, x2 = x.chunk(2, dim=1)
out = self.cat.cat((x1, self.branch2(x2)), dim=1)
else:
out = self.cat.cat((self.branch1(x), self.branch2(x)), dim=1)
out = shufflenetv2.channel_shuffle(out, 2)
return out
def forward(self, x):
skip = x
x = self.conv(x)
x = channel_shuffle(x, self.num_groups)
result = []
for s2_block in self.s2_blocks:
result.append(s2_block(x))
x = torch.cat(result, 1)
if self.skip:
x = x + skip
x = self.bn(x)
x = self.prelu(x)
return x
