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Major slowdown as einsum optimize path used even for two arguments #10357

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mhvk opened this issue Jan 10, 2018 · 0 comments · Fixed by #10359
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Major slowdown as einsum optimize path used even for two arguments #10357

mhvk opened this issue Jan 10, 2018 · 0 comments · Fixed by #10359
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06 - Regression component: numpy._core

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@mhvk
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mhvk commented Jan 10, 2018

While looking at #10343 and #10352, I wondered why optimization is attempted for only 2 inputs, when there is obviously nothing to optimize. The slowdown is dramatic, a factor of 25 (enough to label this a regression):

a = np.eye(3)
b = np.arange(3)
%timeit np.einsum('...ij,j...->i...', a, b)
# 10000 loops, best of 3: 87.7 µs per loop
%timeit np.einsum('...ij,j...->i...', a, b, optimize=False)
# 100000 loops, best of 3: 3.52 µs per loop
@mhvk mhvk mentioned this issue Jan 10, 2018
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@larsoner larsoner mentioned this issue Jan 10, 2018
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mhvk added a commit to mhvk/numpy that referenced this issue Jan 10, 2018
@mhvk
BUG: do not optimize einsum with only 2 arguments.
720cb56 
fixes numpygh-10357.

Avoid slow execution of 2-argument einsum calls, by ensuring
we use the c code directly.
@mhvk mhvk mentioned this issue Jan 10, 2018
Merged
@charris charris added this to the 1.14.1 release milestone Feb 3, 2018
hanjohn pushed a commit to hanjohn/numpy that referenced this issue Feb 15, 2018
@mhvk @hanjohn
BUG: do not optimize einsum with only 2 arguments.
f031b7c 
fixes numpygh-10357.

Avoid slow execution of 2-argument einsum calls, by ensuring
we use the c code directly.
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BUG: do not optimize einsum with only 2 arguments. mhvk/numpy
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@charris @mhvk