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fix nan

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This commit is contained in:
hofee 2024-10-31 12:02:48 +00:00
parent 5e8684d149
commit 1123e69bff
1 changed files with 11 additions and 1 deletions
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10
core/pipeline.py
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@ -108,6 +108,9 @@ class NBVReconstructionPipeline(nn.Module):
partial_point_feat_seq = []
for j in range(seq_len):
partial_per_point_feat = per_point_feat[scanned_pts_mask[j]]
if partial_per_point_feat.shape[0] == 0:
partial_point_feat = torch.zeros(per_point_feat.shape[1], device=device)
else:
partial_point_feat = torch.mean(partial_per_point_feat, dim=0) # Tensor(Dp)
partial_point_feat_seq.append(partial_point_feat)
partial_point_feat_seq = torch.stack(partial_point_feat_seq, dim=0) # Tensor(S x Dp)
@ -122,6 +125,13 @@ class NBVReconstructionPipeline(nn.Module):
main_feat = torch.cat([seq_feat, global_scanned_feat], dim=-1) # Tensor(B x (Ds+Dg))
if torch.isnan(main_feat).any():
for i in range(len(main_feat)):
if torch.isnan(main_feat[i]).any():
scanned_pts_mask = scanned_pts_mask_batch[i]
Log.info(f"scanned_pts_mask shape: {scanned_pts_mask.shape}")
Log.info(f"scanned_pts_mask sum: {scanned_pts_mask.sum()}")
import ipdb
ipdb.set_trace()
Log.error("nan in main_feat", True)
return main_feat