From a1a65f67e405aea100db3d767a5243f667a3455c Mon Sep 17 00:00:00 2001 From: Haoxun Zhan Date: Wed, 2 Jan 2019 21:33:54 +0800 Subject: [PATCH] Fix incorrect RST in cppdocs tensor_basics.rst.txt https://pytorch.org/cppdocs/notes/tensor_basics.html#scalars-and-zero-dimensional-tensors --- _sources/notes/tensor_basics.rst.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/_sources/notes/tensor_basics.rst.txt b/_sources/notes/tensor_basics.rst.txt index 73f6a06418a..5872852f3ec 100644 --- a/_sources/notes/tensor_basics.rst.txt +++ b/_sources/notes/tensor_basics.rst.txt @@ -77,7 +77,7 @@ otherwise behave as normal tensors. Scalars and zero-dimensional tensors ------------------------------------ -In addition to the ``Tensor`` objects, ATen also includes ``Scalar``s that +In addition to the ``Tensor`` objects, ATen also includes ``Scalar``\s that represent a single number. Like a Tensor, Scalars are dynamically typed and can hold any one of ATen's number types. Scalars can be implicitly constructed from C++ number types. Scalars are needed because some functions like ``addmm`` take @@ -100,7 +100,7 @@ will *always* return a Scalar value, like ``sum``. torch::Tensor c = ... torch::Tensor r = torch::addmm(1.0, a, .5, b, c); -In addition to ``Scalar``s, ATen also allows ``Tensor`` objects to be +In addition to ``Scalar``\s, ATen also allows ``Tensor`` objects to be zero-dimensional. These Tensors hold a single value and they can be references to a single element in a larger ``Tensor``. They can be used anywhere a ``Tensor`` is expected. They are normally created by operators like `select`