From 07a0e2fd4eb4b4bfb117eeac555bf0d1ede6d9ed Mon Sep 17 00:00:00 2001 From: Kevin Klein <7267523+kklein@users.noreply.github.com> Date: Mon, 8 Jul 2024 12:16:03 +0200 Subject: [PATCH] Format `Var` as code. (#162) Co-authored-by: Christian Bourjau --- docs/manual/overview.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/manual/overview.rst b/docs/manual/overview.rst index 64b3af9e..df2e4238 100644 --- a/docs/manual/overview.rst +++ b/docs/manual/overview.rst @@ -10,7 +10,7 @@ Like its name suggests, is represents a variable (a placeholder, lazy value, ... A ``Var`` object does not have a concrete value, but it does have an explicit type. For instance, it may have type Tensor, which is parametrised by the element type (like ``numpy.float32``) and shape (a tuple like ``('N', 2)`` - meaning *N x 2*). -For example, given ``a: Var`` and ``b: Var``, ``c: Var = add(a, b)`` is the Var representing the sum of ``a`` and ``b``. +Considering two ``Var`` objects ``a`` and ``b`` one may represent their sum as ``c: Var = add(a, b)``. The type and shape information of ``c`` is automatically derived from the inputs following the ONNX type inference implementation. The ``add`` function is an *operator constructor*, which internally constructs an ``Add`` node and returns a variable representing its output.