keras-spiking

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KerasSpiking

KerasSpiking provides tools for training and running spiking neural networks directly within the Keras framework. The main feature is keras_spiking.SpikingActivation, which can be used to transform any activation function into a spiking equivalent. For example, we can translate a non-spiking model, such as

.. code-block:: python

inp = tf.keras.Input((5,))
dense = tf.keras.layers.Dense(10)(inp)
act = tf.keras.layers.Activation("relu")(dense)
model = tf.keras.Model(inp, act)

into the spiking equivalent:

.. code-block:: python

# add time dimension to inputs
inp = tf.keras.Input((None, 5))
dense = tf.keras.layers.Dense(10)(inp)
# replace Activation with SpikingActivation
act = keras_spiking.SpikingActivation("relu")(dense)
model = tf.keras.Model(inp, act)

Models with SpikingActivation layers can be optimized and evaluated in the same way as any other Keras model. They will automatically take advantage of KerasSpiking's "spiking aware training": using the spiking activations on the forward pass and the non-spiking (differentiable) activation function on the backwards pass.

KerasSpiking also includes various tools to assist in the training of spiking models, such as additional regularizers <https://www.nengo.ai/keras-spiking/reference.html#module-keras_spiking.regularizers>_ and filtering layers <https://www.nengo.ai/keras-spiking/reference.html#module-keras_spiking.layers>_.

If you are interested in building and optimizing spiking neuron models, you may also be interested in NengoDL <https://www.nengo.ai/nengo-dl>. See this page <https://www.nengo.ai/keras-spiking/nengo-dl-comparison.html> for a comparison of the different use cases supported by these two packages.

Documentation

Check out the documentation <https://www.nengo.ai/keras-spiking/>_ for

• Installation instructions <https://www.nengo.ai/keras-spiking/installation.html>_
• More detailed example introducing the features of KerasSpiking <https://www.nengo.ai/keras-spiking/examples/spiking-fashion-mnist.html>_
• API reference <https://www.nengo.ai/keras-spiking/reference.html>_