Numpy和Tensorflow:ValueError：包含多个元素的数组的真值不明确。使用a.any（）或a.all（）

Question

我试图用tensorflow中的feed_dict将值传递给我的神经网络，同时传递值，我得到了标题中提到的值误差

这是我的密码：

train_scipy.minimize(sess, feed_dict={
        sol_int:f, 
        int_var:int_draw,
        bou_var_1:bou_draw1,
        bou_var_2:bou_draw2,
        bou_var_3:bou_draw3,
        bou_var_4:bou_draw4,
        bou_var_5:bou_draw5,
        bou_var_1_alt:bou_draw1_alt,
        bou_var_2_alt:bou_draw2_alt,
        bou_var_3_alt:bou_draw3_alt,
        bou_var_4_alt:bou_draw4_alt,
        bou_var_5_alt:bou_draw5_alt
    })

我的错误：

Traceback (most recent call last):
  File "mscopy.py", line 378, in <module>
    main(sys.argv[1:])
  File "mscopy.py", line 369, in main
    bou_var_5_alt:bou_draw5_alt
  File "/home/jbrahmbhatt/.local/lib/python3.6/site-packages/tensorflow/contrib/opt/python/training/external_optimizer.py", line 207, in minimize
    optimizer_kwargs=self.optimizer_kwargs)
  File "/home/jbrahmbhatt/.local/lib/python3.6/site-packages/tensorflow/contrib/opt/python/training/external_optimizer.py", line 402, in _minimize
    result = scipy.optimize.minimize(*minimize_args, **minimize_kwargs)
  File "/home/jbrahmbhatt/.local/lib/python3.6/site-packages/scipy/optimize/_minimize.py", line 595, in minimize
    return _minimize_bfgs(fun, x0, args, jac, callback, **options)
  File "/home/jbrahmbhatt/.local/lib/python3.6/site-packages/scipy/optimize/optimize.py", line 990, in _minimize_bfgs
    old_fval, old_old_fval, amin=1e-100, amax=1e100)
  File "/home/jbrahmbhatt/.local/lib/python3.6/site-packages/scipy/optimize/optimize.py", line 810, in _line_search_wolfe12
    **kwargs)
  File "/home/jbrahmbhatt/.local/lib/python3.6/site-packages/scipy/optimize/linesearch.py", line 101, in line_search_wolfe1
    c1=c1, c2=c2, amax=amax, amin=amin, xtol=xtol)
  File "/home/jbrahmbhatt/.local/lib/python3.6/site-packages/scipy/optimize/linesearch.py", line 155, in scalar_search_wolfe1
    alpha1 = min(1.0, 1.01*2*(phi0 - old_phi0)/derphi0)
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

由于代码太大了，我不能放更多的东西，但如果需要，我可以提供其他细节，我不确定这里出了什么问题。我从.csv文件中获取值并将其传递给优化器