support packed samples in semantic renderer (#2247)

nerfstudio/model_components/renderers.py

@@ -410,10 +410,17 @@ class SemanticRenderer(nn.Module):
         cls,
         semantics: Float[Tensor, "*bs num_samples num_classes"],
         weights: Float[Tensor, "*bs num_samples 1"],
+        ray_indices: Optional[Int[Tensor, "num_samples"]] = None,
+        num_rays: Optional[int] = None,
     ) -> Float[Tensor, "*bs num_classes"]:
         """Calculate semantics along the ray."""
-        sem = torch.sum(weights * semantics, dim=-2)
-        return sem
+        if ray_indices is not None and num_rays is not None:
+            # Necessary for packed samples from volumetric ray sampler
+            return nerfacc.accumulate_along_rays(
+                weights[..., 0], values=semantics, ray_indices=ray_indices, n_rays=num_rays
+            )
+        else:
+            return torch.sum(weights * semantics, dim=-2)
 
 
 class NormalsRenderer(nn.Module):