如下所示： def softmax(logits, axis=None, name=None, dim=None): """Computes softmax activations. This function performs the equivalent of softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis) Args: logits: A non-empty `Tensor`. Must be one