From 69bbcbb1efbb364cb7c4152f365fc882418187d3 Mon Sep 17 00:00:00 2001
From: James Lamb <jaylamb20@gmail.com>
Date: Thu, 18 Feb 2021 23:46:43 -0600
Subject: [PATCH] add anchors for olds links

---
 docs/Advanced-Topics.rst         | 2 ++
 docs/Features.rst                | 2 ++
 docs/Parallel-Learning-Guide.rst | 6 ++++++
 3 files changed, 10 insertions(+)

diff --git a/docs/Advanced-Topics.rst b/docs/Advanced-Topics.rst
index 680977eef81f..9137dc3123fc 100644
--- a/docs/Advanced-Topics.rst
+++ b/docs/Advanced-Topics.rst
@@ -59,6 +59,8 @@ Parameters Tuning
 
 -  Refer to `Parameters Tuning <./Parameters-Tuning.rst>`__.
 
+.. _Parallel Learning:
+
 Distributed Learning
 --------------------
 
diff --git a/docs/Features.rst b/docs/Features.rst
index 08b7bb2f20df..6566eb628af2 100644
--- a/docs/Features.rst
+++ b/docs/Features.rst
@@ -72,6 +72,8 @@ It only needs to use some collective communication algorithms, like "All reduce"
 LightGBM implements state-of-art algorithms\ `[9] <#references>`__.
 These collective communication algorithms can provide much better performance than point-to-point communication.
 
+.. _Optimization in Parallel Learning:
+
 Optimization in Distributed Learning
 ------------------------------------
 
diff --git a/docs/Parallel-Learning-Guide.rst b/docs/Parallel-Learning-Guide.rst
index 6e3fcb60ef6c..acc42eee43e3 100644
--- a/docs/Parallel-Learning-Guide.rst
+++ b/docs/Parallel-Learning-Guide.rst
@@ -1,6 +1,8 @@
 Distributed Learning Guide
 ==========================
 
+.. _Parallel Learning Guid:
+
 This guide describes distributed learning in LightGBM. Distributed learning allows the use of multiple machines to produce a single model.
 
 Follow the `Quick Start <./Quick-Start.rst>`__ to know how to use LightGBM first.
@@ -65,6 +67,8 @@ Kubeflow users can also use the `Kubeflow XGBoost Operator`_ for machine learnin
 
 Kubeflow integrations for LightGBM are not maintained by LightGBM's maintainers.
 
+.. _Build Parallel Version:
+
 LightGBM CLI
 ^^^^^^^^^^^^
 
@@ -99,6 +103,8 @@ Then write these IP in one file (assume ``mlist.txt``) like following:
 
 **Note**: For Windows users, need to start "smpd" to start MPI service. More details can be found `here`_.
 
+.. _Run Parallel Learning:
+
 Run Distributed Learning
 ''''''''''''''''''''''''