[WIP] l2 constraned parts in keras

l2_constrained_loss.py

import tensorflow as tf

K = tf.keras.backend

def l2_constrained_loss(norm):
    def _l2_constrained_loss(y_true, y_pred):
        y_pred = tf.nn.softmax(y_pred * norm)
        return tf.keras.losses.categorical_crossentropy(y_true, y_pred)
    return _l2_constrained_loss

def l2_constrained_accuracy(norm):
    def _l2_constrained_accuracy(y_true, y_pred):
        y_pred = tf.nn.softmax(y_pred * norm)
        return tf.keras.metrics.categorical_accuracy(y_true, y_pred)
    return _l2_constrained_accuracy

def l2_constrained_topk_accuracy(norm, k):
    def _l2_constrained_topk_accuracy(y_true, y_pred):
        y_pred = tf.nn.softmax(y_pred * norm)
        return tf.keras.metrics.top_k_categorical_accuracy(y_true, y_pred, k=k)
    return _l2_constrained_topk_accuracy