题目内容
下面程序段的执行结果为( )。import tensorflow as tfa = tf.range(6)a1 = tf.reshape(a, [2, 3])b = tf.constant([[7, 8, 9], [10, 11, 12]])b1 = tf.gather(b, axis=1, indices=[1, 2, 0])c = a1*b1print(c.numpy())
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对下列程序段的执行结果，描述错误的是( )。import tensorflow as tfx = tf.constant([1., 4., 9., 16.])pow(x, 0.5)
下列程序段的执行结果为( )。import tensorflow as tfa = tf.range(24)b = tf.reshape(a,[4,6])c = tf.gather_nd(b,[[0,0],[1,1],[2,2]])print(c.numpy())
执行下列程序段后，得到的结果是( )。import tensorflow as tfimport numpy as npa = tf.constant(np.arange(48).reshape(3,2,4,2))b =tf.random.shuffle(a)c = tf.constant(np.arange(8).reshape(2,4))d = a@cprint(d.shape)
下列程序段的执行结果为( )。import tensorflow as tfimport numpy as npa = tf.constant([[1., 2., 3.],[4., 5., 6.]])b = tf.random.shuffle(a)c = tf.constant(np.arange(6), shape=(3,2) ,dtype=tf.float32)d = tf.reduce_mean(b@c, axis=0)e = tf.argmin(d,axis=0)print("d_value:",d.numpy())print("e_value:",e.numpy())
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