TF Eager: Add SPINN model example for dynamic/recursive NN.

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+# SPINN with TensorFlow eager execution
+
+SPINN, or Stack-Augmented Parser-Interpreter Neural Network, is a recursive
+neural network that utilizes syntactic parse information for natural language
+understanding.
+
+SPINN was originally described by:
+Bowman, S.R., Gauthier, J., Rastogi A., Gupta, R., Manning, C.D., & Potts, C.
+  (2016). A Fast Unified Model for Parsing and Sentence Understanding.
+  https://arxiv.org/abs/1603.06021
+
+Our implementation is based on @jekbradbury's PyTorch implementation at:
+https://github.com/jekbradbury/examples/blob/spinn/snli/spinn.py,
+
+which was released under the BSD 3-Clause License at:
+https://github.com/jekbradbury/examples/blob/spinn/LICENSE
+
+##  Content
+
+Python source file(s):
+- `spinn.py`: Model definition and training routines written with TensorFlow
+  eager execution idioms.
+
+## To run
+
+- Make sure you have installed the latest `tf-nightly` or `tf-nightly-gpu` pip
+  package of TensorFlow in order to access the eager execution feature.
+
+- Download and extract the raw SNLI data and GloVe embedding vectors.
+  For example:
+
+  ```bash
+  curl -fSsL https://nlp.stanford.edu/projects/snli/snli_1.0.zip --create-dirs -o /tmp/spinn-data/snli/snli_1.0.zip
+  unzip -d /tmp/spinn-data/snli /tmp/spinn-data/snli/snli_1.0.zip
+  curl -fSsL http://nlp.stanford.edu/data/glove.42B.300d.zip --create-dirs -o /tmp/spinn-data/glove/glove.42B.300d.zip
+  unzip -d /tmp/spinn-data/glove /tmp/spinn-data/glove/glove.42B.300d.zip
+  ```
+
+- Train model. E.g.,
+
+  ```bash
+  python spinn.py --data_root /tmp/spinn-data --logdir /tmp/spinn-logs
+  ```
+
+  During training, model checkpoints and TensorBoard summaries will be written
+  periodically to the directory specified with the `--logdir` flag.
+  The training script will reload a saved checkpoint from the directory if it
+  can find one there.
+
+  To view the summaries with TensorBoard:
+
+  ```bash
+  tensorboard --logdir /tmp/spinn-logs
+  ```