tf.concat与numpy.concatenate

tf.concat

t1 = [[1, 2, 3], [4, 5, 6]]t2 = [[7, 8, 9], [10, 11, 12]]tf.concat(0, [t1, t2]) ==> [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]tf.concat(1, [t1, t2]) ==> [[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]]# tensor t3 with shape [2, 3]# tensor t4 with shape [2, 3]tf.shape(tf.concat(0, [t3, t4])) ==> [4, 3]tf.shape(tf.concat(1, [t3, t4])) ==> [2, 6]

numpy.concatenate

a = np.array([[1, 2], [3, 4]])b = np.array([[5, 6]])np.concatenate((a, b), axis=0)array([[1, 2],       [3, 4],       [5, 6]])np.concatenate((a, b.T), axis=1)array([[1, 2, 5],       [3, 4, 6]])