Type RadialConstraint
Namespace tensorflow.keras.constraints
Parent Constraint
Interfaces IRadialConstraint
Constrains `Conv2D` kernel weights to be the same for each radius. For example, the desired output for the following 4-by-4 kernel:: ```
kernel = [[v_00, v_01, v_02, v_03],
[v_10, v_11, v_12, v_13],
[v_20, v_21, v_22, v_23],
[v_30, v_31, v_32, v_33]]
``` is this:: ```
kernel = [[v_11, v_11, v_11, v_11],
[v_11, v_33, v_33, v_11],
[v_11, v_33, v_33, v_11],
[v_11, v_11, v_11, v_11]]
``` This constraint can be applied to any `Conv2D` layer version, including
`Conv2DTranspose` and `SeparableConv2D`, and with either `"channels_last"` or
`"channels_first"` data format. The method assumes the weight tensor is of
shape `(rows, cols, input_depth, output_depth)`.