From 305da94f0d3604ab4ff6c27d38c40ea70be0c984 Mon Sep 17 00:00:00 2001
From: Yifan Zhao <yifanz16@illinois.edu>
Date: Fri, 26 Mar 2021 21:37:02 -0500
Subject: [PATCH] Fixed some links in documentation
---
hpvm/docs/getting-started.rst | 8 ++++----
hpvm/docs/install.rst | 2 +-
hpvm/projects/predtuner | 2 +-
hpvm/test/README.rst | 6 ------
4 files changed, 6 insertions(+), 12 deletions(-)
diff --git a/hpvm/docs/getting-started.rst b/hpvm/docs/getting-started.rst
index 0f1ee13cb8..cbf5d0b095 100644
--- a/hpvm/docs/getting-started.rst
+++ b/hpvm/docs/getting-started.rst
@@ -63,8 +63,8 @@ Create a DNN `module` and load the checkpoint:
Any `torch.nn.Module` can be similarly used,
as long as they only contain the tensor operators supported in HPVM.
-See "Supported Operators" in :doc:`PyTorch frontend <components/torch2hpvm>`
-and :doc:`Keras frontend <components/keras-frontend>`.
+See "Supported Operators" in :doc:`PyTorch frontend </components/torch2hpvm>`
+and :doc:`Keras frontend </components/keras-frontend>`.
Now we are ready to export the model. The main functioning class of `torch2hpvm` is `ModelExporter`:
@@ -183,7 +183,7 @@ After the tuning finishes, the tuner will
* save the HPVM config format (write-only) at ``./hpvm_confs.txt``.
It is also possible to save the configuration in other formats
-(see the :doc:`predtuner documentation <components/predtuner>`).
+(see the :doc:`predtuner documentation </components/predtuner>`).
Profiling the Configurations
----------------------------
@@ -228,4 +228,4 @@ An example of ``configs_profiled.png`` looks like this (proportion of your image
This concludes the whole workflow of HPVM.
For more detailed usages, check out the documentation of each component listed
-:doc:`here <components/index>`.
+:doc:`here </components/index>`.
diff --git a/hpvm/docs/install.rst b/hpvm/docs/install.rst
index 47b400d2be..4876cf960c 100644
--- a/hpvm/docs/install.rst
+++ b/hpvm/docs/install.rst
@@ -161,4 +161,4 @@ You can run tests similarly as how ``approxhpvm.py`` is compiled: for example,
make -j<number of threads> check-hpvm-pass
-runs ``check-hpvm-pass`` tests. See TODO for details on benchmarks and test cases.
+runs ``check-hpvm-pass`` tests. See :doc:`/tests` for details on benchmarks and test cases.
diff --git a/hpvm/projects/predtuner b/hpvm/projects/predtuner
index aa28a41ca1..a149e36517 160000
--- a/hpvm/projects/predtuner
+++ b/hpvm/projects/predtuner
@@ -1 +1 @@
-Subproject commit aa28a41ca12b15af31e1d15b687367e27cde3878
+Subproject commit a149e365170263666db764664ad8ed6b03f258d3
diff --git a/hpvm/test/README.rst b/hpvm/test/README.rst
index e770b05cb3..66af5c999f 100644
--- a/hpvm/test/README.rst
+++ b/hpvm/test/README.rst
@@ -120,9 +120,3 @@ Currently, there are 20 of them. These are:
``_cudnn`` suffix indicates the code is generated onto cuDNN functions.
Otherwise they are generated to ``tensor_runtime`` DNN functions which are hand-written in CUDA.
-
-TODO: figure out how to
-^^^^^^^^^^^^^^^^^^^^^^^
-
-
-#. Auto run Keras and PyTorch tests (generating, compiling and running all DNNs)
--
GitLab