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tf.keras.constraints.UnitNorm

Constrains the weights incident to each hidden unit to have unit norm.

Inherits From: Constraint

Also available via the shortcut function tf.keras.constraints.unit_norm.

Arguments
axis integer, axis along which to calculate weight norms. For instance, in a Dense layer the weight matrix has shape (input_dim, output_dim), set axis to 0 to constrain each weight vector of length (input_dim,). In a Conv2D layer with data_format="channels_last", the weight tensor has shape (rows, cols, input_depth, output_depth), set axis to [0, 1, 2] to constrain the weights of each filter tensor of size (rows, cols, input_depth).

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Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/constraints/UnitNorm