LostTech.TensorFlow : API Documentation

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)`.


Public properties

object PythonObject get;