[Doc] Small graphs readme.txt, edit pass (#1030)

* [Doc] Small graphs readme.txt, edit pass

Edit for grammar and style. Should this be an .rst on .txt?

* Update README.txt

tutorials/models/2_small_graph/README.txt

 .. _tutorials2-index:
 
-Dealing with many small graphs
+Batching many small graphs
 ==============================
 
 * **Tree-LSTM** `[paper] <https://arxiv.org/abs/1503.00075>`__ `[tutorial]
-  <2_small_graph/3_tree-lstm.html>`__ `[code]
+  <2_small_graph/3_tree-lstm.html>`__ `[PyTorch code]
   <https://github.com/dmlc/dgl/blob/master/examples/pytorch/tree_lstm>`__:
-  sentences of natural languages have inherent structures, which are thrown
+  Sentences have inherent structures that are thrown
   away by treating them simply as sequences. Tree-LSTM is a powerful model
-  that learns the representation by leveraging prior syntactic structures
-  (e.g. parse-tree). The challenge to train it well is that simply by padding
-  a sentence to the maximum length no longer works, since trees of different
+  that learns the representation by using prior syntactic structures such as a parse-tree.
+  The challenge in training is that simply by padding
+  a sentence to the maximum length no longer works. Trees of different
   sentences have different sizes and topologies. DGL solves this problem by
-  throwing the trees into a bigger "container" graph, and use message-passing
-  to explore maximum parallelism. The key API we use is batching.
+  adding the trees to a bigger container graph, and then using message-passing
+  to explore maximum parallelism. Batching is a key API for this.