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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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)
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Please explain your changes below.
Only added
Finchonconfig.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.ymlworks 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.