def update_state()

in train/CustomModel.py [0:0]

• 7 lines of code
• 2 McCabe index (conditional complexity)

    def update_state(self, y_true, y_pred,sample_weight=None):
        ## converting to a 6 * None matrix
        corrects = tf.transpose(tf.cast(y_true,'float32'))
        preds = tf.transpose(tf.math.round(y_pred))
        ## converting to booleans
        booltrue = tf.equal(corrects,tf.constant(1.0))
        boolpred = tf.equal(preds,tf.constant(1.0))
        ## logical and to get true positives - including multi labels
        self.tp.assign_add(tf.reduce_sum(tf.cast(tf.math.logical_and(booltrue,boolpred),'float32')))
        ## sum to get all positives 
        self.trues.assign_add(tf.math.reduce_sum(corrects))