From 2ee0a0fa0d4fb2ddbee5127ad926639a350630d8 Mon Sep 17 00:00:00 2001
From: Yifan Zhao <yifanz16@illinois.edu>
Date: Fri, 26 Mar 2021 14:30:16 -0500
Subject: [PATCH] Added keras/doc/Support.md and fixed a few links
---
hpvm/docs/components/index.rst | 3 +-
hpvm/docs/components/keras-frontend.rst | 4 +-
hpvm/docs/components/keras-support.rst | 1 +
hpvm/docs/references/compilation-process.rst | 2 +
hpvm/projects/keras/docs/Support.md | 54 --------------------
hpvm/projects/keras/docs/Support.rst | 54 ++++++++++++++++++++
6 files changed, 61 insertions(+), 57 deletions(-)
create mode 120000 hpvm/docs/components/keras-support.rst
delete mode 100644 hpvm/projects/keras/docs/Support.md
create mode 100644 hpvm/projects/keras/docs/Support.rst
diff --git a/hpvm/docs/components/index.rst b/hpvm/docs/components/index.rst
index e71b13a8bb..8f9ab42a8d 100644
--- a/hpvm/docs/components/index.rst
+++ b/hpvm/docs/components/index.rst
@@ -7,7 +7,7 @@ HPVM consists of a few relatively independent key components.
* HPVM code generator: a few ``opt`` passes that lowers HPVM IR to LLVM IR,
which is then compiled into object code and binary.
-`Compilation process of HPVM <../references/hpvm-specification.html>`_
+:doc:`Compilation process of HPVM </references/hpvm-specification>`
shows how these 2 components work together.
In addition, there are:
@@ -26,6 +26,7 @@ which explains their role, usage, and other details.
:maxdepth: 1
keras-frontend
+ keras-support
keras-benchmarks
torch2hpvm
predtuner
diff --git a/hpvm/docs/components/keras-frontend.rst b/hpvm/docs/components/keras-frontend.rst
index 51dc06ae62..d67adff4f2 100644
--- a/hpvm/docs/components/keras-frontend.rst
+++ b/hpvm/docs/components/keras-frontend.rst
@@ -39,5 +39,5 @@ At the root of this project (``/projects/keras/``) install the Keras frontend pi
Suppported Operations
---------------------
-List of supported operations and limitations are documented `here <../projects/keras/docs/Support.md>`_.
-TODO: move that Support.md in here as well, otherwise the link will fail when we publish to a website.
+List of supported operations and limitations are documented
+:doc:`here <keras-support>`.
diff --git a/hpvm/docs/components/keras-support.rst b/hpvm/docs/components/keras-support.rst
new file mode 120000
index 0000000000..0b77e04dc1
--- /dev/null
+++ b/hpvm/docs/components/keras-support.rst
@@ -0,0 +1 @@
+../../projects/keras/docs/Support.rst
\ No newline at end of file
diff --git a/hpvm/docs/references/compilation-process.rst b/hpvm/docs/references/compilation-process.rst
index ab3f392f4f..1115de935f 100644
--- a/hpvm/docs/references/compilation-process.rst
+++ b/hpvm/docs/references/compilation-process.rst
@@ -1,3 +1,5 @@
+.. _hpvm-comp-process:
+
HPVM Compilation Process
========================
diff --git a/hpvm/projects/keras/docs/Support.md b/hpvm/projects/keras/docs/Support.md
deleted file mode 100644
index b568d3d640..0000000000
--- a/hpvm/projects/keras/docs/Support.md
+++ /dev/null
@@ -1,54 +0,0 @@
-## Supported Keras Operators
-
-The Keras frontend supports `Sequential()` Keras models.
-The list of supported operations is as follows:
-
-* `Conv2D`
-* `DepthwiseConv2D`
-* `Dense`
-* `BatchNormalization`
-* `MaxPooling2D`
-* `AveragePooling2D`
-* `Flatten`
-* `Add`
-* `ZeroPadding2D`
-* `Activation`
- * `relu`
- * `tanh`
- * `softmax`
-
-
-
-## Limitations
-
-* Currently, we support Convolutional Neural Networks (CNNs) that include the supported operators (above) - RNNs/LSTMs not supported
-* We currently only support models in NCHW format (NHWC is not supported)
-* Softmax operator should be the last operation in the CNN pipeline
-* Softmax operation must be a separate operator (not specified as activation to another type of Keras operator). Example of what works:
-
-```python
-Activation ("softmax")
-```
-
-Example of what is NOT supported:
-
-```python
-Dense(num_classes, activation="softmax")
-```
-
-* For convolutions with stride > 1 `same` convolution is NOT supported. Explicitly add `ZeroPadding2D` layer before `Conv2D` or `DepthwiseConv2D` operators. Example of what does NOT work:
-
-```python
-Conv2D(num_filters, kernel_size = (3,3), strides = (2,2), padding = `same`)
-```
-
-Example of what works instead:
-
-```python
-# NOTE: Amount of padding varies with kernel sizes and strides
-ZeroPadding2D(padding=(1,1), data_format = `channels_first`) # only support NCHW
-Conv2D(num_filters, kernel_size = (3,3), strides = (2,2), padding = `valid`)
-```
-
-
-
diff --git a/hpvm/projects/keras/docs/Support.rst b/hpvm/projects/keras/docs/Support.rst
new file mode 100644
index 0000000000..8d9d11c4cb
--- /dev/null
+++ b/hpvm/projects/keras/docs/Support.rst
@@ -0,0 +1,54 @@
+Supported Keras Operators
+=========================
+
+The Keras frontend supports ``Sequential()`` Keras models.
+The list of supported operations is as follows:
+
+
+* ``Conv2D``
+* ``DepthwiseConv2D``
+* ``Dense``
+* ``BatchNormalization``
+* ``MaxPooling2D``
+* ``AveragePooling2D``
+* ``Flatten``
+* ``Add``
+* ``ZeroPadding2D``
+* ``Activation``
+
+ * ``relu``
+ * ``tanh``
+ * ``softmax``
+
+Limitations
+-----------
+
+* Currently, we support Convolutional Neural Networks (CNNs) that include the supported operators (above) - RNNs/LSTMs not supported
+* We currently only support models in NCHW format (NHWC is not supported)
+* Softmax operator should be the last operation in the CNN pipeline
+* Softmax operation must be a separate operator (not specified as activation to another type of Keras operator). Example of what works:
+
+.. code-block:: python
+
+ Activation ("softmax")
+
+Example of what is NOT supported:
+
+.. code-block:: python
+
+ Dense(num_classes, activation="softmax")
+
+
+* For convolutions with stride > 1 ``same`` convolution is NOT supported. Explicitly add ``ZeroPadding2D`` layer before ``Conv2D`` or ``DepthwiseConv2D`` operators. Example of what does NOT work:
+
+.. code-block:: python
+
+ Conv2D(num_filters, kernel_size = (3,3), strides = (2,2), padding = `same`)
+
+Example of what works instead:
+
+.. code-block:: python
+
+ # NOTE: Amount of padding varies with kernel sizes and strides
+ ZeroPadding2D(padding=(1,1), data_format = `channels_first`) # only support NCHW
+ Conv2D(num_filters, kernel_size = (3,3), strides = (2,2), padding = `valid`)
--
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