Fix intermediate dtypes for float16 inputs in cupyx.scipy.ndimage stats functions
#3402
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emcastillo
reviewed
Jun 8, 2020
cupyx/scipy/ndimage/measurements.py
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| if cupy.isscalar(index): | ||
| count, sum_c_sq = single_group(input[labels == index]) | ||
| return sum_c_sq / cupy.asanyarray(count).astype(float) |
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The three cases looks too similar
Couldn't be grouped in something like
def calc_var_with_intermediate_float(input):
vals_c = input - input.mean()
return cupy.square(vals_c).sum() / cupy.asanyarray(count).astype(float)
emcastillo
reviewed
Jun 8, 2020
cupyx/scipy/ndimage/measurements.py
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| if cupy.isscalar(index): | ||
| count, sum = single_group(input[labels == index]) | ||
| return sum / cupy.asanyarray(count).astype(float) |
emcastillo
reviewed
Jun 8, 2020
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I fixed them as well as |
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Sorry, please fix travis! |
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Mmm �[91mWarning, treated as error:�[39;49;00m .. autofunction:: |
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Perhaps because of |
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has it been updated recently? |
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Yesterday. https://pypi.org/project/Sphinx/#history |
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takagi
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Jenkins, test this please |
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Successfully created a job for commit 442aa77: |
emcastillo
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Jenkins CI test (for commit 442aa77, target branch master) succeeded! |
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Follows #3259 (comment).
NumPy's
ndarray.sum()andndarray.mean()use different intermediate dtypes for summation and return a little different results for float16 inputs.Because of this,
cupyx.scipy.ndimagestats functions introduced in #3259 return slightly different results for float16 inputs compared with their SciPy counterparts. This PR fixes the functions to follow SciPy's way to compute such values.