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-rw-r--r--models/rgb_part_net.py5
1 files changed, 3 insertions, 2 deletions
diff --git a/models/rgb_part_net.py b/models/rgb_part_net.py
index fc1406c..4d7ba7f 100644
--- a/models/rgb_part_net.py
+++ b/models/rgb_part_net.py
@@ -76,8 +76,8 @@ class RGBPartNet(nn.Module):
def _disentangle(self, x_c1_t2, x_c2_t2=None):
n, t, c, h, w = x_c1_t2.size()
device = x_c1_t2.device
- x_c1_t1 = x_c1_t2[:, torch.randperm(t), :, :, :]
if self.training:
+ x_c1_t1 = x_c1_t2[:, torch.randperm(t), :, :, :]
((f_a_, f_c_, f_p_), losses) = self.ae(x_c1_t2, x_c1_t1, x_c2_t2)
# Decode features
x_c = self._decode_cano_feature(f_c_, n, t, device)
@@ -100,7 +100,8 @@ class RGBPartNet(nn.Module):
else: # evaluating
f_c_, f_p_ = self.ae(x_c1_t2)
x_c = self._decode_cano_feature(f_c_, n, t, device)
- x_p = self._decode_pose_feature(f_p_, n, t, c, h, w, device)
+ x_p_ = self._decode_pose_feature(f_p_, n, t, c, h, w, device)
+ x_p = x_p_.view(n, t, self.pn_in_channels, self.h // 4, self.w // 4)
return (x_c, x_p), None, None
def _decode_appr_feature(self, f_a_, n, t, device):