Here I have a 1D array: And the sum of all elements in the array should be 75491328*8*8 = 4831444992. However, when I use np.sum, I get a different output. That's what happens on my Jupyter Notebook using the latest version of Numpy. But when I use Jupyter Notebook of Coursera using old version 1.18.4 of Numpy, everything is fine.

Python: numpy.sum returns wrong ouput (numpy version 1.21.3)

Here I have a 1D array:

>>> import numpy as np
>>> a = np.array([75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328,
                  75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328,
                  75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328,
                  75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328,
                  75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328,
                  75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328,
                  75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328,
                  75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328, 75491328])

And the sum of all elements in the array should be 75491328*8*8 = 4831444992. However, when I use np.sum, I get a different output.

>>> np.sum(a)
536477696

That’s what happens on my Jupyter Notebook using the latest version of Numpy. But when I use Jupyter Notebook of Coursera using old version 1.18.4 of Numpy, everything is fine.

How can I fix this bug? Is it a bug or is it because of me?

Answer

The problem is caused by integer overflow, you should change the datatype of np.array to int64.

import numpy as np
np.array([Your values here], dtype=np.int64)

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Answer