Updated toc and tutorial notes.

Author: brianjo

_static/img/hybrid.png

@@ -1,6 +1,9 @@
-Loading a PyTorch model in C++
+Loading a PyTorch Model in C++
 ==============================
 
+This tutorial requires PyTorch 1.0 (preview) or later. For installation information 
+visit http://pytorch.org/get-started.
+
 As its name suggests, the primary interface to PyTorch is the Python
 programming language. While Python is a suitable and preferred language for
 many scenarios requiring dynamism and ease of iteration, there are equally many

advanced_source/cpp_export.rst

@@ -7,6 +7,9 @@
 
 
 ######################################################################
+# This example requires PyTorch 1.0 (preview) or later. 
+# For installation information visit http://pytorch.org/get-started.
+# 
 # In this tutorial, we explore a fun and interesting use-case of recurrent
 # sequence-to-sequence models. We will train a simple chatbot using movie
 # scripts from the `Cornell Movie-Dialogs

beginner_source/chatbot_tutorial.py

@@ -7,17 +7,17 @@
 
 
 ######################################################################
+# This example requires PyTorch 1.0 (preview) or later. For installation 
+# information visit http://pytorch.org/get-started.
+#
 # This tutorial will walk through the process of transitioning a
 # sequence-to-sequence model to Torch Script using PyTorch’s Hybrid
 # Frontend. The model that we will convert is the chatbot model from the
-# `Chatbot tutorial <>`__. While the `introductory hybrid frontend
-# tutorials <>`__ are useful for gaining an understanding of the
-# work-flow, purpose, and basic syntax of the feature, this document
-# covers a more challenging model and a more practical use-case. You can
-# either treat this tutorial as a “Part 2” to the `Chatbot tutorial <>`__
+# `Chatbot tutorial <https://pytorch.org/tutorials/beginner/chatbot_tutorial.html>`__. 
+# You can either treat this tutorial as a “Part 2” to the Chatbot tutorial
 # and deploy your own pretrained model, or you can start with this
 # document and use a pretrained model that we host. In the latter case,
-# you can reference the original `Chatbot tutorial <>`__ for details
+# you can reference the original Chatbot tutorial for details
 # regarding data preprocessing, model theory and definition, and model
 # training.
 #

beginner_source/deploy_seq2seq_hybrid_frontend_tutorial.py

@@ -4,6 +4,9 @@
 ===============================================
 **Author:** `Nathan Inkawhich <https://github.com/inkawhich>`_
 
+This tutorial requires PyTorch 1.0 (preview) or later. For installation 
+information visit http://pytorch.org/get-started.
+
 This document is meant to highlight the syntax of the Hybrid Frontend
 through a non-code intensive example. The Hybrid Frontend is one of the
 new shiny features of Pytorch 1.0 and provides an avenue for developers

beginner_source/hybrid_frontend/learning_hybrid_frontend_through_example_tutorial.py

@@ -43,9 +43,9 @@ Getting Started
    :description: :doc:`beginner/transfer_learning_tutorial`
 
 .. customgalleryitem::
-   :figure: /_static/img/hybrid_frontend/220px-KnnClassification.png
+   :figure: /_static/img/hybrid.png
    :tooltip: Experiment with some of the key features of the PyTorch hybrid frontend
-   :description: :doc:`beginner/hybrid_frontend_tutorial`
+   :description: :doc:`beginner/deploy_seq2seq_hybrid_frontend_tutorial`
 
 .. customgalleryitem::
    :figure: /_static/img/thumbnails/floppy.png
@@ -214,7 +214,7 @@ Production Usage
    beginner/data_loading_tutorial
    beginner/pytorch_with_examples
    beginner/transfer_learning_tutorial
-   beginner/hybrid_frontend_tutorial
+   beginner/deploy_seq2seq_hybrid_frontend_tutorial   
    beginner/saving_loading_models
 
 .. toctree::