build docs

Author: rusty1s

setup.py

@@ -14,6 +14,8 @@
 if os.getenv('FORCE_NON_CUDA', '0') == '1':
     WITH_CUDA = False
 
+BUILD_DOCS = os.getenv('BUILD_DOCS', '0') == '1'
+
 
 def get_extensions():
     Extension = CppExtension
@@ -74,7 +76,7 @@ def get_extensions():
     install_requires=install_requires,
     setup_requires=setup_requires,
     tests_require=tests_require,
-    ext_modules=get_extensions(),
+    ext_modules=get_extensions() if not BUILD_DOCS else [],
     cmdclass={
         'build_ext': BuildExtension.with_options(no_python_abi_suffix=True)
     },

torch_scatter/scatter.py

@@ -1,10 +1,29 @@
+import warnings
 import os.path as osp
 from typing import Optional, Tuple
 
 import torch
 
-torch.ops.load_library(
-    osp.join(osp.dirname(osp.abspath(__file__)), '_scatter.so'))
+try:
+    torch.ops.load_library(
+        osp.join(osp.dirname(osp.abspath(__file__)), '_scatter.so'))
+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:
+        raise ImportError
+
+    def 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
+
+    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.jit.script

torch_scatter/segment_coo.py

@@ -1,10 +1,35 @@
+import warnings
 import os.path as osp
 from typing import Optional, Tuple
 
 import torch
 
-torch.ops.load_library(
-    osp.join(osp.dirname(osp.abspath(__file__)), '_segment_coo.so'))
+try:
+    torch.ops.load_library(
+        osp.join(osp.dirname(osp.abspath(__file__)), '_segment_coo.so'))
+except OSError:
+    warnings.warn('Failed to load `segment_coo` binaries.')
+
+    def segment_coo_placeholder(src: torch.Tensor, index: torch.Tensor,
+                                out: Optional[torch.Tensor],
+                                dim_size: Optional[int]) -> torch.Tensor:
+        raise ImportError
+
+    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
+
+    def gather_coo_placeholder(src: torch.Tensor, index: torch.Tensor,
+                               out: Optional[torch.Tensor]) -> torch.Tensor:
+        raise ImportError
+
+    torch.ops.torch_scatter.segment_sum_coo = segment_coo_placeholder
+    torch.ops.torch_scatter.segment_mean_coo = segment_coo_placeholder
+    torch.ops.torch_scatter.segment_min_coo = segment_coo_with_arg_placeholder
+    torch.ops.torch_scatter.segment_max_coo = segment_coo_with_arg_placeholder
+    torch.ops.torch_scatter.gather_coo = gather_coo_placeholder
 
 
 @torch.jit.script

torch_scatter/segment_csr.py

@@ -1,10 +1,33 @@
+import warnings
 import os.path as osp
 from typing import Optional, Tuple
 
 import torch
 
-torch.ops.load_library(
-    osp.join(osp.dirname(osp.abspath(__file__)), '_segment_csr.so'))
+try:
+    torch.ops.load_library(
+        osp.join(osp.dirname(osp.abspath(__file__)), '_segment_csr.so'))
+except OSError:
+    warnings.warn('Failed to load `segment_csr` binaries.')
+
+    def segment_csr_placeholder(src: torch.Tensor, indptr: torch.Tensor,
+                                out: Optional[torch.Tensor]) -> torch.Tensor:
+        raise ImportError
+
+    def segment_csr_with_arg_placeholder(
+            src: torch.Tensor, indptr: torch.Tensor,
+            out: Optional[torch.Tensor]) -> Tuple[torch.Tensor, torch.Tensor]:
+        raise ImportError
+
+    def gather_csr_placeholder(src: torch.Tensor, indptr: torch.Tensor,
+                               out: Optional[torch.Tensor]) -> torch.Tensor:
+        raise ImportError
+
+    torch.ops.torch_scatter.segment_sum_csr = segment_csr_placeholder
+    torch.ops.torch_scatter.segment_mean_csr = segment_csr_placeholder
+    torch.ops.torch_scatter.segment_min_csr = segment_csr_with_arg_placeholder
+    torch.ops.torch_scatter.segment_max_csr = segment_csr_with_arg_placeholder
+    torch.ops.torch_scatter.gather_csr = gather_csr_placeholder
 
 
 @torch.jit.script