README.md

Addons - Optimizers

Maintainers

Submodule	Maintainers	Contact Info
conditional_gradient	Pengyu Kan, Vishnu Lokhande	[email protected], [email protected]
cyclical_learning_rate	Raphael Meudec	[email protected]
lamb	Jing Li, Junjie Ke	[email protected], [email protected]
lazy_adam	Saishruthi Swaminathan	[email protected]
lookahead	Zhao Hanguang	[email protected]
moving_average	Dheeraj R. Reddy	[email protected]
rectified_adam	Zhao Hanguang	[email protected]
stochastic_weight_averaging	Shreyash Patodia	[email protected]
weight_decay_optimizers	Phil Jund	[email protected]

Components

Submodule	Optimizer	Reference
conditional_gradient	ConditionalGradient	https://arxiv.org/pdf/1803.06453.pdf
cyclical_learning_rate	Cyclical Learning Rate	https://arxiv.org/abs/1506.01186
lamb	LAMB	https://arxiv.org/abs/1904.00962
lazy_adam	LazyAdam	https://arxiv.org/abs/1412.6980
lookahead	Lookahead	https://arxiv.org/abs/1907.08610v1
moving_average	MovingAverage
rectified_adam	RectifiedAdam	https://arxiv.org/pdf/1908.03265v1.pdf
stochastic_weight_averaging	SWA	https://arxiv.org/abs/1803.05407.pdf
weight_decay_optimizers	SGDW, AdamW, extend_with_decoupled_weight_decay	https://arxiv.org/pdf/1711.05101.pdf

Contribution Guidelines

Standard API

In order to conform with the current API standard, all optimizers must:

• Inherit from either keras.optimizer_v2.OptimizerV2 or its subclasses.
• Register as a keras global object so it can be serialized properly: @tf.keras.utils.register_keras_serializable(package='Addons')
• Add the addon to the py_library in this sub-package's BUILD file.

Testing Requirements

• When applicable, run all tests with TensorFlow's @run_in_graph_and_eager_modes (for test method) or run_all_in_graph_and_eager_modes (for TestCase subclass) decorator.
• Add a py_test to this sub-package's BUILD file.

Documentation Requirements

• Update the table of contents in this sub-packages's README.