我有一个形状为(8,8,2)的数组,想在该数组上训练一个NN。我想像这样在训练数据中添加另一个整数:[array,int],但最终得到的形状像(2,),我无法对其进行训练。有没有办法创建一个TensorFlow可以接受或训练带有此新数组的NN的数组?
我试图将整数变成向量并将其添加到形状为(9,8,2)的数组中,但这会导致大量冗余信息。
my_array = [[(rook, b), (horse, b), (bishop, b), (queen, b), (king, b), (bishop, b), (horse, b), (rook, b)],
[(pawn, b) for i in range(8)],
[(0, 0) for i in range(8)],
[(0, 0) for i in range(8)],
[(0, 0) for i in range(8)],
[(0, 0) for i in range(8)],
[(pawn, w) for i in range(8)],
[(rook, w), (horse, w), (bishop, w), (queen, w), (king, w), (bishop, w), (horse, w), (rook, w)]]
my_int = 1
I_tried = my_array+[[(my_int, my_int) for i in range(8)]]
print(numpy.array(my_array).shape) # --> (8, 8, 2)
print(numpy.array(I_tried).shape) # --> (2,)
答案 0 :(得分:0)
您可能想要使用元组而不是列表。取决于此串联的目的。但是您可以尝试以下方法:
my_int = 1
second_array = [(my_int, my_int) for i in range(8)]
I_tried = (my_array, second_array)