import tensorflow as tf import numpy as np d_scores = {} d_scores[0] = [[1,2],[3,4],[5,6]] d_scores[1] = [[1,2],[3,4],[5,6]] d_scores[2] = [[1,2],[3,4],[5,6]] l_scores = [] l_scores.append(d_scores) l_scores.append(d_scores) #l_scores.append(d_scores) ls = [s[0] for s in l_scores] ls_ = tf.concat(ls, axis=1) t=tf.concat([[[1, 2, 3],[4, 5, 6]],[[7, 8, 9], [10, 11, 12]]],axis=0) with tf.Session() as sess: print(d_scores) print(l_scores) print(l_scores[0]) print(ls) print(ls_.eval()) print(t.eval())
结果
{0: [[1, 2], [3, 4], [5, 6]], 1: [[1, 2], [3, 4], [5, 6]], 2: [[1, 2], [3, 4], [5, 6]]}
[{0: [[1, 2], [3, 4], [5, 6]], 1: [[1, 2], [3, 4], [5, 6]], 2: [[1, 2], [3, 4], [5, 6]]}, {0: [[1, 2], [3, 4], [5, 6]], 1: [[1, 2], [3, 4], [5, 6]], 2: [[1, 2], [3, 4], [5, 6]]}]
{0: [[1, 2], [3, 4], [5, 6]], 1: [[1, 2], [3, 4], [5, 6]], 2: [[1, 2], [3, 4], [5, 6]]}
[[[1, 2], [3, 4], [5, 6]], [[1, 2], [3, 4], [5, 6]]]
[[1 2 1 2]
[3 4 3 4]
[5 6 5 6]]
[[ 1 2 3]
[ 4 5 6]
[ 7 8 9]
[10 11 12]]