typo

Author: rusty1s

README.md

@@ -28,6 +28,7 @@ The package consists of the following operations:
 * [**Scatter Mul**](https://rusty1s.github.io/pytorch_scatter/build/html/functions/mul.html)
 * [**Scatter Div**](https://rusty1s.github.io/pytorch_scatter/build/html/functions/div.html)
 * [**Scatter Mean**](https://rusty1s.github.io/pytorch_scatter/build/html/functions/mean.html)
+* [**Scatter Std**](https://rusty1s.github.io/pytorch_scatter/build/html/functions/std.html)
 * [**Scatter Min**](https://rusty1s.github.io/pytorch_scatter/build/html/functions/min.html)
 * [**Scatter Max**](https://rusty1s.github.io/pytorch_scatter/build/html/functions/max.html)
 

docs/source/_figures/build.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-files=(add sub mul div mean max min)
+files=(add sub mul div mean max min std)
 
 for name in "${files[@]}"; do
   pdflatex "$name"

docs/source/_figures/std.svg

@@ -0,0 +1,8 @@
+\def\indices{{0, 0, 1, 0, 2, 2, 3, 3}}
+\def\inputs{{5, 1, 7, 2, 3, 2, 1, 3}}
+\def\outputs{{2.1, 0, 0.7, 1.4}}
+\def\colors{{"cyan", "orange", "olive", "magenta"}}
+\def\numberInputs{7}
+\def\numberOutputs{3}
+\def\operation{std}
+\input{template}

docs/source/_figures/std.tex

@@ -0,0 +1,6 @@
+Scatter Std
+===========
+
+.. automodule:: torch_scatter
+
+.. autofunction:: scatter_std

docs/source/functions/std.rst

@@ -15,7 +15,7 @@
                       ['cuda/scatter.cpp', 'cuda/scatter_kernel.cu'])
     ]
 
-__version__ = '1.0.5'
+__version__ = '1.1.0'
 url = 'https://github.com/rusty1s/pytorch_scatter'
 
 install_requires = []
@@ -36,5 +36,4 @@
     tests_require=tests_require,
     ext_modules=ext_modules,
     cmdclass=cmdclass,
-    packages=find_packages(),
-)
+    packages=find_packages(), )

setup.py

@@ -0,0 +1,19 @@
+from itertools import product
+
+import pytest
+import torch
+from torch_scatter import scatter_std
+
+from .utils import grad_dtypes as dtypes, devices, tensor
+
+biass = [True, False]
+
+
+@pytest.mark.parametrize('dtype,device,bias', product(dtypes, devices, biass))
+def test_std(dtype, device, bias):
+    src = tensor([[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]], dtype, device)
+    index = tensor([[0, 0, 0, 0, 0], [1, 1, 1, 1, 1]], torch.long, device)
+
+    out = scatter_std(src, index, dim=-1, unbiased=bias)
+    expected = src.std(dim=-1, unbiased=bias)
+    assert out.tolist() == [[expected[0].item(), 0], [0, expected[0].item()]]

test/test_std.py

@@ -7,7 +7,7 @@
 from .max import scatter_max
 from .min import scatter_min
 
-__version__ = '1.0.5'
+__version__ = '1.1.0'
 
 __all__ = [
     'scatter_add',

torch_scatter/__init__.py

@@ -13,7 +13,7 @@ def scatter_add(src, index, dim=-1, out=None, dim_size=None, fill_value=0):
     |
 
     Sums all values from the :attr:`src` tensor into :attr:`out` at the indices
-    specified in the :attr:`index` tensor along an given axis :attr:`dim`. For
+    specified in the :attr:`index` tensor along a given axis :attr:`dim`. For
     each value in :attr:`src`, its output index is specified by its index in
     :attr:`input` for dimensions outside of :attr:`dim` and by the
     corresponding value in :attr:`index` for dimension :attr:`dim`. If

torch_scatter/add.py

@@ -39,7 +39,7 @@ def scatter_div(src, index, dim=-1, out=None, dim_size=None, fill_value=1):
     |
 
     Divides all values from the :attr:`src` tensor into :attr:`out` at the
-    indices specified in the :attr:`index` tensor along an given axis
+    indices specified in the :attr:`index` tensor along a given axis
     :attr:`dim`.If multiple indices reference the same location, their
     **contributions divide** (`cf.` :meth:`~torch_scatter.scatter_add`).