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hub / github.com/JunlinHan/DCLGAN / load_networks

Method load_networks

models/base_model.py:196–224  ·  view source on GitHub ↗

Load all the networks from the disk. Parameters: epoch (int) -- current epoch; used in the file name '%s_net_%s.pth' % (epoch, name)

(self, epoch)

Source from the content-addressed store, hash-verified

194 self.__patch_instance_norm_state_dict(state_dict, getattr(module, key), keys, i + 1)
195
196 def load_networks(self, epoch):
197 """Load all the networks from the disk.
198
199 Parameters:
200 epoch (int) -- current epoch; used in the file name '%s_net_%s.pth' % (epoch, name)
201 """
202 for name in self.model_names:
203 if isinstance(name, str):
204 load_filename = '%s_net_%s.pth' % (epoch, name)
205 if self.opt.isTrain and self.opt.pretrained_name is not None:
206 load_dir = os.path.join(self.opt.checkpoints_dir, self.opt.pretrained_name)
207 else:
208 load_dir = self.save_dir
209
210 load_path = os.path.join(load_dir, load_filename)
211 net = getattr(self, 'net' + name)
212 if isinstance(net, torch.nn.DataParallel):
213 net = net.module
214 print('loading the model from %s' % load_path)
215 # if you are using PyTorch newer than 0.4 (e.g., built from
216 # GitHub source), you can remove str() on self.device
217 state_dict = torch.load(load_path, map_location=str(self.device))
218 if hasattr(state_dict, '_metadata'):
219 del state_dict._metadata
220
221 # patch InstanceNorm checkpoints prior to 0.4
222 # for key in list(state_dict.keys()): # need to copy keys here because we mutate in loop
223 # self.__patch_instance_norm_state_dict(state_dict, net, key.split('.'))
224 net.load_state_dict(state_dict)
225
226 def print_networks(self, verbose):
227 """Print the total number of parameters in the network and (if verbose) network architecture

Callers 1

setupMethod · 0.95

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