A. Unique TensorFlower 42476f730e MNIST TF 2.0 integration test
PiperOrigin-RevId: 220545522
2018-11-07 16:03:33 -08:00

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# TF 2.0 Showcase
The code here shows idiomatic ways to write TensorFlow 2.0 code. It doubles as
an integration test.
## General guidelines for showcase code:
- Code should minimize dependencies and be self-contained in one file. A user
should be able to copy-paste the example code into their project and have it
just work.
- Code should emphasize simplicity over performance, as long as it performs
within a factor of 2-3x of the optimized implementation.
- Code should work on CPU and single GPU.
- Code should run in Python 3.
- Code should conform to the [Google Python Style Guide](https://github.com/google/styleguide/blob/gh-pages/pyguide.md)
- Code should follow these guidelines:
- Prefer Keras.
- Split code into separate input pipeline and model code segments.
- Don't use tf.cond or tf.while_loop; instead, make use of AutoGraph's
functionality to compile Python `for`, `while`, and `if` statements.
- Prefer a simple training loop over Estimator
- Save and restore a SavedModel.
- Write basic TensorBoard metrics - loss, accuracy,