(self, X)
| 149 | param.requires_grad = False |
| 150 | |
| 151 | def forward(self, X): |
| 152 | h = self.slice1(X) |
| 153 | h_relu1_2 = h |
| 154 | h = self.slice2(h) |
| 155 | h_relu2_2 = h |
| 156 | h = self.slice3(h) |
| 157 | h_relu3_3 = h |
| 158 | h = self.slice4(h) |
| 159 | h_relu4_3 = h |
| 160 | h = self.slice5(h) |
| 161 | h_relu5_3 = h |
| 162 | vgg_outputs = namedtuple( |
| 163 | "VggOutputs", ["relu1_2", "relu2_2", "relu3_3", "relu4_3", "relu5_3"] |
| 164 | ) |
| 165 | out = vgg_outputs(h_relu1_2, h_relu2_2, h_relu3_3, h_relu4_3, h_relu5_3) |
| 166 | return out |
| 167 | |
| 168 | |
| 169 | def normalize_tensor(x, eps=1e-10): |
nothing calls this directly
no outgoing calls
no test coverage detected