Warning for notimplemented error and patch_size fix

nerfstudio/data/datamanagers/base_datamanager.py

@@ -461,7 +461,7 @@ class VanillaDataManager(DataManager, Generic[TDataset]):
 
     def _get_pixel_sampler(self, dataset: TDataset, num_rays_per_batch: int) -> PixelSampler:
         """Infer pixel sampler to use."""
-        if self.config.patch_size > 1:
+        if self.config.patch_size > 1 and isinstance(self.config.pixel_sampler, PixelSamplerConfig):
             return PatchPixelSamplerConfig().setup(
                 patch_size=self.config.patch_size, num_rays_per_batch=num_rays_per_batch
             )

nerfstudio/data/pixel_samplers.py

@@ -319,7 +319,9 @@ class PatchPixelSampler(PixelSampler):
     ) -> Int[Tensor, "batch_size 3"]:
         if isinstance(mask, Tensor):
             # Note: if there is a mask, should switch to the base PixelSampler class
-            raise NotImplementedError()
+            raise NotImplementedError(
+                "Masked sampling not implemented for PairPixelSampler. Change Config to PixelSamplerConfig instead."
+            )
         else:
             sub_bs = batch_size // (self.config.patch_size**2)
             indices = torch.rand((sub_bs, 3), device=device) * torch.tensor(
@@ -379,10 +381,11 @@ class PairPixelSampler(PixelSampler):  # pylint: disable=too-few-public-methods
         mask: Optional[Tensor] = None,
         device: Union[torch.device, str] = "cpu",
     ) -> Int[Tensor, "batch_size 3"]:
-        if mask:
+        if isinstance(mask, Tensor):
             # Note: if there is a mask, should switch to the base PixelSampler class
-
-            raise NotImplementedError()
+            raise NotImplementedError(
+                "Masked sampling not implemented for PairPixelSampler. Change Config to PixelSamplerConfig instead."
+            )
         else:
             s = (self.rays_to_sample, 1)
             ns = torch.randint(0, num_images, s, dtype=torch.long, device=device)