Remove stale DeMemWM pose debug comments

algorithms/dememwm/pose_prediction.py

@@ -223,7 +223,6 @@ class PosePrediction(BasePytorchAlgo):
                         # _, r_idx = torch.topk(overlap_ratio / tensor_max_with_number((frame_idx[curr_frame] - frame_idx[:curr_frame]), 10), k=1, dim=0)
 
                         # if curr_frame >=93:
-                        #     import pdb;pdb.set_trace()
 
                         # start_time = time.time()
                         cos_sim = F.cosine_similarity(xs_pred.to(r_idx.device)[r_idx[:, range(in_fov1.shape[1])], 
@@ -256,7 +255,6 @@ class PosePrediction(BasePytorchAlgo):
                         # _, r_idx = torch.topk(overlap_ratio / tensor_max_with_number((frame_idx[curr_frame] - frame_idx[:curr_frame]), 10), k=1, dim=0)
 
                         # if curr_frame >=93:
-                        #     import pdb;pdb.set_trace()
 
                         # start_time = time.time()
                         cos_sim = F.cosine_similarity(xs_pred.to(r_idx.device)[r_idx[:, range(in_fov1.shape[1])], 
@@ -274,7 +272,6 @@ class PosePrediction(BasePytorchAlgo):
                 xs_pred = torch.cat([xs_pred, xs_pred[random_idx[:,range(xs_pred.shape[1])], range(xs_pred.shape[1])].clone()], 0)
 
             if condition_similar_length:
-                # import pdb;pdb.set_trace()
                 padding = torch.zeros((condition_similar_length,) + conditions.shape[1:], device=conditions.device, dtype=conditions.dtype)
                 input_condition = torch.cat([conditions[start_frame : curr_frame + horizon], padding], dim=0)
                 if self.pose_cond_dim:
@@ -295,7 +292,6 @@ class PosePrediction(BasePytorchAlgo):
                     else:
                         # print(curr_frame-start_frame)
                         # input_pose_condition = torch.cat([c2w_mat[start_frame : curr_frame + horizon], c2w_mat[random_idx[:,range(xs_pred.shape[1])], range(xs_pred.shape[1])]], dim=0).clone()
-                        # import pdb;pdb.set_trace()
                         if self.last_frame_refer:
                             input_pose_condition = torch.cat([c2w_mat[start_frame : curr_frame + horizon], c2w_mat[-1:]], dim=0).clone()
                         else:
@@ -354,12 +350,10 @@ class PosePrediction(BasePytorchAlgo):
                 )
 
                 # if curr_frame > 14:
-                #     import pdb;pdb.set_trace()
 
                 # if xs_pred_back is not None:
                 #     xs_pred = torch.cat([xs_pred[:6], xs_pred_back[6:12], xs_pred[6:]], dim=0)
         
-            # import pdb;pdb.set_trace()
             if condition_similar_length: # and curr_frame+1!=n_frames:
                 xs_pred = xs_pred[:-condition_similar_length]