MaxNorm weight constraint.

Constrains the weights incident to each hidden unit to have a norm less than or equal to a desired value.

Usage

constraint_maxnorm(max_value = 2L, axis = 1L)

Arguments

max_value

the maximum norm value for the incoming weights.

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).

Value

A Constraint instance, a callable that can be passed to layer constructors or used directly by calling it with tensors.

See also

• https://keras.io/api/layers/constraints#maxnorm-class

Other constraints:
Constraint()
constraint_minmaxnorm()
constraint_nonneg()
constraint_unitnorm()