doc fixes

torch_scatter/composite/logsumexp.py

@@ -21,7 +21,7 @@ def scatter_logsumexp(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
         dim_size = out.size(dim)
     else:
         if dim_size is None:
-            dim_size = int(index.max().item() + 1)
+            dim_size = int(index.max()) + 1
 
     size = src.size()
     size[dim] = dim_size

torch_scatter/scatter.py

@@ -10,20 +10,23 @@ try:
 except OSError:
     warnings.warn('Failed to load `scatter` binaries.')
 
-    def placeholder(src: torch.Tensor, index: torch.Tensor, dim: int,
-                    out: Optional[torch.Tensor],
-                    dim_size: Optional[int]) -> torch.Tensor:
+    def scatter_placeholder(src: torch.Tensor, index: torch.Tensor, dim: int,
+                            out: Optional[torch.Tensor],
+                            dim_size: Optional[int]) -> torch.Tensor:
         raise ImportError
+        return src
 
-    def arg_placeholder(src: torch.Tensor, index: torch.Tensor, dim: int,
-                        out: Optional[torch.Tensor], dim_size: Optional[int]
-                        ) -> Tuple[torch.Tensor, torch.Tensor]:
+    def scatter_with_arg_placeholder(src: torch.Tensor, index: torch.Tensor,
+                                     dim: int, out: Optional[torch.Tensor],
+                                     dim_size: Optional[int]
+                                     ) -> Tuple[torch.Tensor, torch.Tensor]:
         raise ImportError
+        return src, index
 
-    torch.ops.torch_scatter.scatter_sum = placeholder
-    torch.ops.torch_scatter.scatter_mean = placeholder
-    torch.ops.torch_scatter.scatter_min = arg_placeholder
-    torch.ops.torch_scatter.scatter_max = arg_placeholder
+    torch.ops.torch_scatter.scatter_sum = scatter_placeholder
+    torch.ops.torch_scatter.scatter_mean = scatter_placeholder
+    torch.ops.torch_scatter.scatter_min = scatter_with_arg_placeholder
+    torch.ops.torch_scatter.scatter_max = scatter_with_arg_placeholder
 
 
 @torch.jit.script

torch_scatter/segment_coo.py

@@ -14,16 +14,19 @@ except OSError:
                                 out: Optional[torch.Tensor],
                                 dim_size: Optional[int]) -> torch.Tensor:
         raise ImportError
+        return src
 
     def segment_coo_with_arg_placeholder(
             src: torch.Tensor, index: torch.Tensor,
             out: Optional[torch.Tensor],
             dim_size: Optional[int]) -> Tuple[torch.Tensor, torch.Tensor]:
         raise ImportError
+        return src, index
 
     def gather_coo_placeholder(src: torch.Tensor, index: torch.Tensor,
                                out: Optional[torch.Tensor]) -> torch.Tensor:
         raise ImportError
+        return src
 
     torch.ops.torch_scatter.segment_sum_coo = segment_coo_placeholder
     torch.ops.torch_scatter.segment_mean_coo = segment_coo_placeholder

torch_scatter/segment_csr.py

@@ -13,15 +13,18 @@ except OSError:
     def segment_csr_placeholder(src: torch.Tensor, indptr: torch.Tensor,
                                 out: Optional[torch.Tensor]) -> torch.Tensor:
         raise ImportError
+        return src
 
     def segment_csr_with_arg_placeholder(
             src: torch.Tensor, indptr: torch.Tensor,
             out: Optional[torch.Tensor]) -> Tuple[torch.Tensor, torch.Tensor]:
         raise ImportError
+        return src, indptr
 
     def gather_csr_placeholder(src: torch.Tensor, indptr: torch.Tensor,
                                out: Optional[torch.Tensor]) -> torch.Tensor:
         raise ImportError
+        return src
 
     torch.ops.torch_scatter.segment_sum_csr = segment_csr_placeholder
     torch.ops.torch_scatter.segment_mean_csr = segment_csr_placeholder