From 7d6ca1b3a7882189839bd2cb80bc8a74fa70d617 Mon Sep 17 00:00:00 2001
From: Jian Weng <werefluke@gmail.com>
Date: Mon, 10 Sep 2018 21:46:57 -0700
Subject: [PATCH] [Tutorial] fix the link thing for the pass tutorial (#1700)

---
 tutorials/dev/low_level_custom_pass.py | 10 +++++++---
 tutorials/optimize/opt_gemm.py         |  2 ++
 2 files changed, 9 insertions(+), 3 deletions(-)

diff --git a/tutorials/dev/low_level_custom_pass.py b/tutorials/dev/low_level_custom_pass.py
index 617093d4a..68e569477 100644
--- a/tutorials/dev/low_level_custom_pass.py
+++ b/tutorials/dev/low_level_custom_pass.py
@@ -7,18 +7,22 @@ TVM is a framework that abstracts away the heterogenity of machine learning acce
 Sometimes users may want customize some analysis and IR transformations
 to adapt TVM to their own specialized hardware. This tutorial helps users write
 a customized pass in TVM.
+
  Prerequisites
--------------
+--------------
+
 Before reading this tutorial, we assume readers have already known these topics well:
+
 - Writing an algorithm in TVM and schedule it. Otherwise, see example tutorials like
-  `Optimize GeMM on CPU <https://docs.tvm.ai/tutorials/optimize/opt_gemm.html>_`.
+  :ref:`opt-gemm`.
 - The basic structure of HalideIR. Otherwise, see ``HalideIR/src/ir/IR.h`` to learn what
   attributes of IR nodes are defined.
 - Visitor design pattern. Otherwise, check the
-  `Python AST module <https://docs.python.org/3/library/ast.html>_` to see how an AST
+  `Python AST module <https://docs.python.org/3/library/ast.html>`_ to see how an AST
   visitor is implemented.
 - How a HalideIR/Schedule is lowered to either a LoweredFunc class or a LLVM module. Otherwise,
   take a look at ``python/tvm/build_module.py`` to get some basics.
+
 """
 
 from __future__ import absolute_import, print_function
diff --git a/tutorials/optimize/opt_gemm.py b/tutorials/optimize/opt_gemm.py
index 803b81e7d..6a0a25228 100644
--- a/tutorials/optimize/opt_gemm.py
+++ b/tutorials/optimize/opt_gemm.py
@@ -1,4 +1,6 @@
 """
+.. _opt-gemm:
+
 How to optimize GEMM on CPU
 ===========================
 **Author**: `Jian Weng <https://github.com/were>`_, \
-- 
GitLab