diff options
| -rw-r--r-- | models/model.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/models/model.py b/models/model.py index 0b8de50..7bc1da9 100644 --- a/models/model.py +++ b/models/model.py @@ -153,10 +153,10 @@ class Model: self.rgb_pn = nn.DataParallel(self.rgb_pn) self.rgb_pn = self.rgb_pn.to(self.device) self.optimizer = optim.Adam([ - {'params': self.rgb_pn.ae.parameters(), **ae_optim_hp}, - {'params': self.rgb_pn.pn.parameters(), **pn_optim_hp}, - {'params': self.rgb_pn.hpm.parameters(), **hpm_optim_hp}, - {'params': self.rgb_pn.fc_mat, **fc_optim_hp} + {'params': self.rgb_pn.module.ae.parameters(), **ae_optim_hp}, + {'params': self.rgb_pn.module.pn.parameters(), **pn_optim_hp}, + {'params': self.rgb_pn.module.hpm.parameters(), **hpm_optim_hp}, + {'params': self.rgb_pn.module.fc_mat, **fc_optim_hp} ], **optim_hp) sched_gamma = sched_hp.get('gamma', 0.9) sched_step_size = sched_hp.get('step_size', 500) @@ -195,7 +195,7 @@ class Model: x_c2 = batch_c2['clip'].to(self.device) y = batch_c1['label'].to(self.device) # Duplicate labels for each part - y = y.unsqueeze(1).repeat(1, self.rgb_pn.num_total_parts) + y = y.unsqueeze(1).repeat(1, self.rgb_pn.module.num_total_parts) losses, images = self.rgb_pn(x_c1, x_c2, y) losses = torch.stack(( # xrecon cano_cons pose_sim |