fixes

.gitignore

@@ -4,6 +4,9 @@ compile_commands.json
 # Visual Studio Code configs.
 .vscode/
 
+# Pycharm
+.idea
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

examples/simple_trainer_scaffold.py

@@ -910,8 +910,12 @@ def train(self):
 
             # eval the full set
             if step in [i - 1 for i in cfg.eval_steps]:
-                self.eval(step)
-            #     self.render_traj(step)
+                self.eval(
+                    step,
+                    n_feat_offsets=self.cfg.n_feat_offsets,
+                    feat_dim=self.cfg.feat_dim,
+                )
+                self.render_traj(step)
 
             if not cfg.disable_viewer:
                 self.viewer.lock.release()

gsplat/strategy/ops.py

@@ -4,7 +4,6 @@
 import torch
 import torch.nn.functional as F
 from torch import Tensor
-from torch_scatter import scatter_max
 
 from gsplat import quat_scale_to_covar_preci
 from gsplat.relocation import compute_relocation
@@ -417,8 +416,8 @@ def grow_anchors(
     selected_features = repeated_features[gradient_mask]  # [N_selected, feat_dim]
 
     # Use inverse_indices to aggregate features
-    scattered_features, _ = scatter_max(
-        selected_features, inv_idx.unsqueeze(1).expand(-1, feat_dim), dim=0
+    scattered_features = torch.segment_reduce(
+        data=selected_features, reduce="amax", lengths=torch.bincount(inv_idx)
     )
     feat = scattered_features[remove_duplicates_mask]  # [N_new, feat_dim]
 

setup.py

@@ -118,7 +118,6 @@ def get_extensions():
         "jaxtyping",
         "rich>=12",
         "torch",
-        "torch_scatter",
         "typing_extensions; python_version<'3.8'",
     ],
     extras_require={