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test: working on benchmarks with Finch
as backend
#772
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CodSpeed Performance ReportMerging #772 will not alter performanceComparing Summary
Benchmarks breakdown
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Great work @DeaMariaLeon! A few suggestions.
It seems the |
m, n, p = sides | ||
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if m * n >= max_size or n * p >= max_size: | ||
if m * n >= max_size or n * p >= max_size or m * n <= min_size or n * p <= min_size: | ||
pytest.skip() | ||
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rng = np.random.default_rng(seed=seed) | ||
x = sparse.random((m, n), density=DENSITY, format=format, random_state=rng) | ||
y = sparse.random((n, p), density=DENSITY, format=format, random_state=rng) | ||
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All the tests on file test_benchmark_coo.py
were meant to fail with Finch
.
Finch
sparse.random
(used to build x
& y
, line 25 and 26) is different, because it doesn't have the format
argument that is used with Numba
.
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@mtsokol How hard would it be to add this to finch
?
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You can probably use sparse.asarray(..., format=<format>)
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Do we just need a format=nothing default and then a reformatting line inside finch.random?
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That'd suffice -- if the format isn't what the format
arg demands, reformat.
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do we have a way of specifying format currently?
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do we have a way of specifying format currently?
asarray
supports a format arg: https://github.com/willow-ahrens/finch-tensor/blob/25d5de0c6b0c75120a06c0b1c2ec1568216c71f8/src/finch/tensor.py#L647
if hasattr(sparse, "compiled"): | ||
operator.matmul = sparse.compiled(operator.matmul) |
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if hasattr(sparse, "compiled"): | |
operator.matmul = sparse.compiled(operator.matmul) | |
f = operator.matmul | |
if hasattr(sparse, "compiled"): | |
f = sparse.compiled(f) |
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if hasattr(sparse, "compiled"): | |
operator.matmul = sparse.compiled(operator.matmul) | |
def f(x, y): | |
return x @ y | |
if hasattr(sparse, "compiled"): | |
f = sparse.compiled(f) |
pytest.skip() | ||
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rng = np.random.default_rng(seed=seed) | ||
x = sparse.random((m, n), density=DENSITY, format=format, random_state=rng) | ||
y = sparse.random((n, p), density=DENSITY, format=format, random_state=rng) | ||
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if hasattr(sparse, "compiled"): | ||
operator.matmul = sparse.compiled(operator.matmul) | ||
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x @ y # Numba compilation |
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x @ y # Numba compilation | |
f(x, y) # Compilation |
m, n, p = sides | ||
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if m * n >= max_size or n * p >= max_size: | ||
if m * n >= max_size or n * p >= max_size or m * n <= min_size or n * p <= min_size: |
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if m * n >= max_size or n * p >= max_size or m * n <= min_size or n * p <= min_size: | |
if m * n >= max_size or n * p >= max_size or m * n * DENSITY <= min_size or n * p * DENSITY <= min_size: |
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What type of PR is this? (check all applicable)
Related issues
Checklist
Please explain your changes below.
Only added
Finch
onconfig.py
- (locally I see the names of the backend. But I'm not sure if this renders fine on CodSpeed).Also, per Hameer instructions I need to see which tests fail with
Finch
.I would like to see if the change on
codspeed.yml
works like expected.Finally, I have only added the line
if hasattr(sparse, "compiled"): f = sparse.compiled(f)
to the first two benchmarks to make sure I correctly understood.