Python OverflowError:数学范围错误在不同的运行中以不同的方式引发 [英] Python OverflowError: math range error being raised differently in different runs

问题描述

我的程序似乎几乎崩溃了.

My program seems to be crashing almost arbitrarily.

我的代码包括这两行:

z[i, j] = -math.exp(oneminusbeta[j, i])
weights[i,j] = math.exp(beta[j,i] + oneminusbeta[j,i])

我之前已经对具有2维的数据运行了我的整个代码，这是7341 x 648.运行该代码我没有任何问题.

I've run my whole code before on data that had 2 dimensions, it was 7341 x 648. I had no issues at all running that code.

但是现在我正在使用的数据大约是它的十倍.它是71678 x 648，并且出现此错误:

But now the data I'm using is about ten times as big. It's 71678 x 648, and I'm getting this error:

OverflowError: math range error

我在任何特定点上都没有.我在每行代码之前记录注释，以便我可以了解导致崩溃的原因，并且看来崩溃在上述第二行(weights[i,j] = math.exp(beta[j,i] + oneminusbeta[j,i]))上的发生频率更高.

And I'm not getting this on any specific point. I'm logging comments before every line of code so that I can see what's causing the crash, and it appears the crash is happening more often on the second line mentioned above (weights[i,j] = math.exp(beta[j,i] + oneminusbeta[j,i])).

问题是，它在不同时间崩溃. 最初，它在weights[30816, 42]崩溃了.然后在weights[55399, 43].然后在z[33715,45].但是，这三种情况下的数据都是相同的.

The thing is, it crashes at different times. At first, it crashed at weights[30816, 42]. Then at weights[55399, 43]. Then at z[33715,45]. But the data is the same in all 3 cases.

可能是什么问题?这是python与内存相关的问题吗?顺便说一下，我也在使用Numba.

What could the problem be? Is this a memory related issue with python? I'm using Numba too, by the way.

我忘了提一下，我已经设置了阈值，以使exp()函数中使用的阈值不超过709或-708，因此从技术上讲不应出现溢出.

I forgot to mention, I've put thresholds so that what goes into the exp() function doesn't exceed what 709 or -708, so technically there shouldn't be an overflow.

推荐答案

计算结果无法在计算机上显示.这可能意味着math.exp(...)大于大约10 ³⁰⁸ ，或者传递给math.exp()的参数大于大约710.

The result of your calculation cannot be represented on your computer. This probably means that math.exp(...) is greater than about 10³⁰⁸, or the argument passed to math.exp() is greater than about 710.

尝试在每次计算之前打印beta[j,i]和oneminusbeta[j,i]的值.

Try printing the values of beta[j,i] and oneminusbeta[j,i] before each calculation.

实际上，您不必在每行代码之前都打印注释.相反，尝试使用try块包装计算，如下所示:

In fact, you don't have to print comments before every line of code. Instead, try wrapping the calculations with a try block, like so:

try:
  weights[i,j] = math.exp(beta[j,i] + oneminusbeta[j,i])
except OverflowError:
  print "Calculation failed! j=%d i=%d beta=%f oneminusbeta=%f"%(j,i,beta[j,i],oneminusbeta[j,i])
  raise

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