diff options
Diffstat (limited to 'models/auto_encoder.py')
| -rw-r--r-- | models/auto_encoder.py | 19 |
1 files changed, 10 insertions, 9 deletions
diff --git a/models/auto_encoder.py b/models/auto_encoder.py index 64c52e3..befd2d3 100644 --- a/models/auto_encoder.py +++ b/models/auto_encoder.py @@ -134,15 +134,16 @@ class AutoEncoder(nn.Module): # x_c1_t2 is the frame for later module (f_a_c1_t2, f_c_c1_t2, f_p_c1_t2) = self.encoder(x_c1_t2) - # Decode canonical features for HPM - x_c_c1_t2 = self.decoder( - torch.zeros_like(f_a_c1_t2), f_c_c1_t2, torch.zeros_like(f_p_c1_t2), - no_trans_conv=True - ) - # Decode pose features for Part Net - x_p_c1_t2 = self.decoder( - torch.zeros_like(f_a_c1_t2), torch.zeros_like(f_c_c1_t2), f_p_c1_t2 - ) + with torch.no_grad(): + # Decode canonical features for HPM + x_c_c1_t2 = self.decoder( + torch.zeros_like(f_a_c1_t2), f_c_c1_t2, torch.zeros_like(f_p_c1_t2), + no_trans_conv=True + ) + # Decode pose features for Part Net + x_p_c1_t2 = self.decoder( + torch.zeros_like(f_a_c1_t2), torch.zeros_like(f_c_c1_t2), f_p_c1_t2 + ) if self.training: # t1 is random time step, c2 is another condition |