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Addons - Activations

Maintainers

Submodule Maintainers Contact Info
gelu @AakashKumarNain @WindQAQ [email protected] [email protected]
hardshrink @WindQAQ [email protected]
lisht @WindQAQ [email protected]
mish @digantamisra98 @WindQAQ [email protected], [email protected]
softshrink @WindQAQ [email protected]
sparsemax @AndreasMadsen [email protected]
tanhshrink @fsx950223 [email protected]
rrelu @fsx950223 [email protected]

Contents

Submodule Activation Reference
gelu gelu https://arxiv.org/abs/1606.08415
hardshrink hardshrink
lisht lisht https://arxiv.org/abs/1901.05894
mish mish https://arxiv.org/abs/1908.08681
softshrink softshrink
sparsemax sparsemax https://arxiv.org/abs/1602.02068
tanhshrink tanhshrink
rrelu rrelu https://arxiv.org/abs/1505.00853

Contribution Guidelines

Standard API

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

  • Be a tf.function unless it is a straightforward call to a custom op or likely to be retraced.
  • 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

  • Simple unittests that demonstrate the layer is behaving as expected.
  • When applicable, run all unittests 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.
  • Add activation name to activations_test.py to test serialization.

Documentation Requirements

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