Merge pull request #18 from vsl9/master

Minor docs updates
NVIDIA · Sep 18, 2019 · 651a206 · 651a206
2 parents 909e975 + 72e3f11
commit 651a206
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Showing 4 changed files with 7 additions and 11 deletions.
diff --git a/README.rst b/README.rst
@@ -38,7 +38,7 @@ See `this video <https://nvidia.github.io/NeMo/>`_ for a quick walk-through.
 **Requirements**
 
 1) Python 3.6 or 3.7
-2) Pytorch 1.2 with GPU support
+2) PyTorch 1.2 with GPU support
 3) NVIDIA APEX. Install from here: https://github.com/NVIDIA/apex
 
 
@@ -81,7 +81,7 @@ instead of
 
 .. code-block:: bash
 	
-	# Install the ASR collection from collections/nemo_asr 
+    # Install the ASR collection from collections/nemo_asr 
     apt-get install libsndfile1
     cd collections/nemo_asr
     pip install .

diff --git a/docs/sources/source/index.rst b/docs/sources/source/index.rst
@@ -22,7 +22,7 @@ A "Neural Module" is a block of code that computes a set of outputs from a set o
 
 Neural Modules’ inputs and outputs have Neural Type for semantic checking.
 
-An application built with NeMo application is a Directed Acyclic Graph(DAG) of connected modules enabling researchers to define and build new speech and nlp networks easily through API Compatible modules.
+An application built with NeMo application is a Directed Acyclic Graph (DAG) of connected modules enabling researchers to define and build new speech and nlp networks easily through API Compatible modules.
 
 
 **Introduction**
@@ -49,14 +49,10 @@ See this video for a walk-through.
 **Requirements**
 
 1) Python 3.6 or 3.7
-2) Pytorch 1.2 with GPU support
+2) PyTorch 1.2 with GPU support
 3) NVIDIA APEX: https://github.com/NVIDIA/apex
 
 
-**Documentation**
-TBD
-
-
 **Getting started**
 
 If desired, you can start with `NGC PyTorch container <https://ngc.nvidia.com/catalog/containers/nvidia:pytorch>`_ which already includes

diff --git a/examples/asr/ASR-Jasper-Tutorial.ipynb b/examples/asr/ASR-Jasper-Tutorial.ipynb
@@ -354,7 +354,7 @@
    "metadata": {},
    "source": [
     "## Mixed Precision Training\n",
-    "Mixed precision and distributed training in NeMo is based on <a href=\"https://github.com/NVIDIA/apex\">NVIDIA’s APEX library</a>. This is installed with NVIDIA's NGC Pytorch container with an example of updating in the example Dockerfile.\n",
+    "Mixed precision and distributed training in NeMo is based on <a href=\"https://github.com/NVIDIA/apex\">NVIDIA’s APEX library</a>. This is installed with NVIDIA's NGC PyTorch container with an example of updating in the example Dockerfile.\n",
     "\n",
     "> **Note** -  _Because mixed precision requires Tensor Cores it\n",
     "> only works on NVIDIA Volta and Turing based GPUs._\n",

diff --git a/examples/start_here/README.md b/examples/start_here/README.md
@@ -4,7 +4,7 @@ Just learns simple function `y=sin(x)`.
 Simply run from `examples/start_here` folder.
 
 # ChatBot Example
-This is an adaptation of [Pytorch Chatbot tutorial](https://pytorch.org/tutorials/beginner/chatbot_tutorial.html)
+This is an adaptation of [PyTorch Chatbot tutorial](https://pytorch.org/tutorials/beginner/chatbot_tutorial.html)
 Simply run from `examples/start_here` folder.
 
 During training it will print **SOURCE**, **PREDICTED RESPONSE** and **TARGET**.
@@ -43,4 +43,4 @@ outputs, hidden = decoder(targets=tgt,
                           max_target_len=max_tgt_length)
 ...                          
 ```
-Simply run from `examples/start_here` folder.
+Simply run from `examples/start_here` folder.