metrics.py 文件源码

def _preprocess(self, logits, targets):
        # Get most probable class of the output
        logits = tf.arg_max(logits, dimension=1)

        # If one-hot provided, transform into class
        if targets.get_shape().ndims > 2:
            targets = tf.arg_max(targets, dimension=1)

        # Erase singletion dimension if exists
        if targets.get_shape().ndims > 1:
            targets = tf.squeeze(targets, axis=1)

        return logits, targets