custom_metrics.py

class Custom_Precision(tf.keras.metrics.Precision):

    def update_state(self, y_true, y_pred, sample_weight=None):
        y_pred_fix = tf.math.less(y_pred, 0.5) 
        y_pred_fix = tf.cast(y_pred_fix, y_pred.dtype)
       
        return super().update_state(y_true, y_pred_fix, sample_weight)
  
class Custom_Recall(tf.keras.metrics.Recall):

    def update_state(self, y_true, y_pred, sample_weight=None):
        y_pred_fix = tf.math.less(y_pred, 0.5) 
        y_pred_fix = tf.cast(y_pred_fix, y_pred.dtype)
       
        return super().update_state(y_true, y_pred_fix, sample_weight)
  
class Custom_Accuracy(tf.keras.metrics.Accuracy):

    def update_state(self, y_true, y_pred, sample_weight=None):
        y_pred_fix = tf.math.less(y_pred, 0.5) 
        y_pred_fix = tf.cast(y_pred_fix, y_pred.dtype)
       
        return super().update_state(y_true, y_pred_fix, sample_weight)