custom weighted categorical loss for keras

gistfile1.txt

def custom_cat_crossentropy(y_true, y_pred):
    # negate 3x3 sub matrix of income matrix to get cost matrix
    # check https://github.com/tensorflow/tensorflow/blob/r1.10/tensorflow/python/keras/backend.py#L3461
    cost_m = tf.constant([[ 0.00222222,  0.01111111,  0.00222222],
       [ 0.00222222, -0.05888889,  0.00222222],
       [ 0.00222222,  1.51111111,  0.00222222]])
    y_true = tf.matmul(y_true, cost_m)
    return tf.keras.losses.categorical_crossentropy(y_true, y_pred)