v1.1 - tf.keras, TF2, Eager compatibility, more

[OverLordGoldDragon]

New features:

• Full compatibility with TensorFlow 2.0.0 and Keras 2.3.0 (keras + tf.keras)
• Full compatibility with TensorFlow 1.14.0 and Keras 2.2.5 (keras + tf.keras)
• Run-based weight decay normalization scheme, normalizing over arbitrary # of iterations independent of LR scheduler (e.g. over all epochs) (total_iterations_wd)
• utils now contain all common optimizer ops, e.g. _apply_weight_decays()
• Reference implementation compatible with tf.python.keras, TF2 + Keras 2.3.0; see docstring
• Cleaner code

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BUGFIXES:

• lr_multipliers were not being applied for AdamW
• SGDW was missing K.symbolic wrapper
• and total_iterations != 0 was missing for NadamW and SGDW, yielding NaN optimizer weights for total_iterations = 0
• TF reset seed method was incompatible w/ TF 2.0.0; added support for both

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Misc changes:

• Updated README.md w/ info on total_iterations_wd
• Added README.md to keras_adamw on module version selection
• Added unit tests for respective optimizers
• Revamped test.sh; each test has a dedicated folder to ease coverage isolation
• Revamped .travis.yml:
  • Added versioning builds w/ TF_KERAS, TF_EAGER, TF_VERSION, and KERAS_VERSION flags
  • Removed boolean KERAS flag; repo is based on Keras
  • Reorder buggy setuptools & conda update -all commands
• Moved testing module requirements from requirements.txt to requirements-test.txt