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-rw-r--r--models/auto_encoder.py19
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