From 0e79074cf19c0b09ac7f0dd832d1f16d8ca78c25 Mon Sep 17 00:00:00 2001 From: Shanqing Cai Date: Wed, 17 Jan 2018 11:51:07 -0800 Subject: TFE: Improve spinn/README.md PiperOrigin-RevId: 182247687 --- third_party/examples/eager/spinn/README.md | 22 +++++++++++++++++----- 1 file changed, 17 insertions(+), 5 deletions(-) (limited to 'third_party/examples') diff --git a/third_party/examples/eager/spinn/README.md b/third_party/examples/eager/spinn/README.md index 6aa95ccce9..6bd3d53e56 100644 --- a/third_party/examples/eager/spinn/README.md +++ b/third_party/examples/eager/spinn/README.md @@ -19,14 +19,26 @@ Other eager execution examples can be found under [tensorflow/contrib/eager/pyth ## Content -Python source file(s): -- `spinn.py`: Model definition and training routines written with TensorFlow - eager execution idioms. +- [`data.py`](../../../../tensorflow/contrib/eager/python/examples/spinn/data.py): Pipeline for loading and preprocessing the + [SNLI](https://nlp.stanford.edu/projects/snli/) data and + [GloVe](https://nlp.stanford.edu/projects/glove/) word embedding, written + using the [`tf.data`](https://www.tensorflow.org/programmers_guide/datasets) + API. +- [`spinn.py`](./spinn.py): Model definition and training routines. + This example illustrates how one might perform the following actions with + eager execution enabled: + * defining a model consisting of a dynamic computation graph, + * assigning operations to the CPU or GPU dependending on device availability, + * training the model using the data from the `tf.data`-based pipeline, + * obtaining metrics such as mean accuracy during training, + * saving and loading checkpoints, + * writing summaries for monitoring and visualization in TensorBoard. ## 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. +- Make sure you have installed TensorFlow release 1.5 or higher. Alternatively, + you can use the latest `tf-nightly` or `tf-nightly-gpu` pip + package to access the eager execution feature. - Download and extract the raw SNLI data and GloVe embedding vectors. For example: -- cgit v1.2.3