def forward(self, x):
x = M.activation(x, M.PARAM_RELU)
x1 = self.c1(x)
x2 = self.c2(x[:, 1:, 1:, :])
x = torch.cat([x1, x2], axis=1)
x = self.bn(x)
return x
def forward(self, x): out = [x[0]] out.append(self.c1(x[1], x[0].shape[2:4])) out.append(self.c2(x[2], x[0].shape[2:4])) out.append(self.c3(x[3], x[0].shape[2:4])) out = sum(out) out = M.activation(out, M.PARAM_RELU) return out
def forward(self, x):
x = F.interpolate(x,
size=None,
scale_factor=2,
mode='bilinear',
align_corners=False)
x = M.activation(x, M.PARAM_RELU)
x = self.c1(x)
return x
def forward(self, x): branch = self.c1(x) branch = self.c2(branch) if self.shortcut: sc = self.sc(x) else: sc = x res = branch + sc res = M.activation(res, M.PARAM_RELU) return res
def forward(self, x):
out = self.c1(x)
out = self.c2(out)
out = self.c3(out)
if self.inchn == self.outchn * 4 and self.stride == 1:
sc = x
else:
sc = self.sc(x)
out = out + sc
out = M.activation(out, M.PARAM_RELU)
return out
def forward(self, x): out = [] for i in range(len(self.branches)): # target branch_out = [] for j in range(len(self.branches)): # source if i==j: branch_out.append(x[i]) elif i<j: branch_out.append(self.branches[i][j](x[j] , target_shape=x[i].shape[2:4])) else: branch_out.append(self.branches[i][j](x[j])) branch_out = sum(branch_out) out.append(M.activation(branch_out, M.PARAM_RELU)) return out
def forward(self, x):
short = x
# residual branch
branch = self.bn(x)
branch = M.activation(branch, M.PARAM_LRELU)
branch = self.c1(branch)
branch = self.c2(branch)
# slicing & shortcut
branch_shape = branch.shape[-1]
short_shape = short.shape[-1]
start = (short_shape - branch_shape) // 2
short = short[:, :, start:start + branch_shape]
res = short + branch
res = F.dropout(res, 0.4, self.training, False)
return res
def forward(self, x):
x = M.activation(x, M.PARAM_RELU)
x = self.c1(x)
return x
