Added keras/doc/Support.md and fixed a few links

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

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>`.

hpvm/docs/components/keras-support.rst

+../../projects/keras/docs/Support.rst
\ No newline at end of file

hpvm/docs/references/compilation-process.rst

+.. _hpvm-comp-process:
+
 HPVM Compilation Process
 ========================
 

hpvm/projects/keras/docs/Support.md → hpvm/projects/keras/docs/Support.rst

-## Supported Keras Operators 
+Supported Keras Operators
+=========================
 
-The Keras frontend supports `Sequential()` Keras models.
+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`
 
+* ``Conv2D``
+* ``DepthwiseConv2D``
+* ``Dense``
+* ``BatchNormalization``
+* ``MaxPooling2D``
+* ``AveragePooling2D``
+* ``Flatten``
+* ``Add``
+* ``ZeroPadding2D``
+* ``Activation`` 
 
+  * ``relu``
+  * ``tanh``
+  * ``softmax``
 
-## Limitations 
+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")
-```
+.. code-block:: python
+
+   Activation ("softmax")
 
 Example of what is NOT supported:
 
-```python
-Dense(num_classes, activation="softmax")
-```
+.. code-block:: python
 
-* 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:
+   Dense(num_classes, activation="softmax")
 
-```python
-Conv2D(num_filters, kernel_size = (3,3), strides = (2,2), padding = `same`)
-```
 
-Example of what works instead:
+* 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
-# 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`)
-```
+.. 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`)