with tf.GradientTape() as tape: w = tf.Variable(tf.constant(3.0)) loss = tf.pow(w,2) grad = tape.gradient(loss,w) print(grad) #tf.Tensor(6.0, shape=(), dtype=float32) tf.one_hot(待转换数据,depth=几分类) tf.nn.softmax( ) assign_sub tf.argmax