BUG: work round int overflow in size calculation #325
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matthew-brett
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| @@ -504,7 +507,8 @@ def array_from_file(shape, in_dtype, infile, offset=0, order='F', mmap=True): | |||
| pass | |||
| if len(shape) == 0: | |||
| return np.array([]) | |||
| n_bytes = int(np.prod(shape) * in_dtype.itemsize) | |||
| # Use reduce and mul to work round integer overflow on 32-bit platforms | |||
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| @@ -504,7 +507,8 @@ def array_from_file(shape, in_dtype, infile, offset=0, order='F', mmap=True): | |||
| pass | |||
| if len(shape) == 0: | |||
| return np.array([]) | |||
| n_bytes = int(np.prod(shape) * in_dtype.itemsize) | |||
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You could also specify the dtype in np.prod, rather than introduce operator.mul:
n_bytes = int(np.prod(shape, dtype=np.int64) * in_dtype.itemsize)
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The advantage of using operator.mul is that is uses Python integers internally, and so completely prevents overflow for any possible value of the shape. In fact the test tests overflow for values above the int64 range, although of course you cannot make an array that large.
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Fair enough. Might change the comment to reflect that it's not just avoiding int32 overflows, but that's really nit-picky.
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Omar pointed out the integer overflow in calculating the image size of an image of size > 4GB, on a 32-bit platform.
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OK to merge? |
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Not sure who are valid signers-off, but it looks reasonable to me. |
larsoner
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Jul 9, 2015
BUG: work round int overflow in size calculation
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Thanks @matthew-brett for the fix |
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grlee77
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Mar 15, 2016
BUG: work round int overflow in size calculation
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Omar pointed out the integer overflow in calculating the image size of an
image of size > 4GB, on a 32-bit platform.