tf.keras.constraints.UnitNorm
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Constrains the weights incident to each hidden unit to have unit norm.
Inherits From: Constraint
tf.keras.constraints.UnitNorm(
axis=0
)
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).
|
Methods
get_config
View source
get_config()
__call__
View source
__call__(
w
)
Call self as a function.
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Last updated 2020-10-01 UTC.
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TensorFlow 2 version
View source on GitHub