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Comment addressments and other good things
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stand-by committed Aug 2, 2024
1 parent 4f05248 commit de115a9
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Showing 2 changed files with 73 additions and 27 deletions.
4 changes: 3 additions & 1 deletion Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
build:
cmake -B build
cmake --build build --parallel
cmake --install build
# TODO in general python build should internally trigger cmake, but for now
# let's keep cmake lines here as we don't have any python build process yet
python -m pip cache purge
Expand All @@ -17,7 +18,8 @@ tests:

.PHONY: benchmark
benchmark:
pytest benchmarks -v
pytest -v benchmarks --benchmark-group-by=func --benchmark-sort=fullname \
--benchmark-columns='mean,median,min,max,stddev,iqr,outliers,ops,rounds,iterations'

.PHONY: clean
clean:
Expand Down
96 changes: 70 additions & 26 deletions benchmarks/test_pauli_string_benchmark.py
Original file line number Diff line number Diff line change
Expand Up @@ -9,12 +9,32 @@
import fast_pauli.pypauli.operations as pp

# TODO add a separate benchmark for get_sparse_repr vs compose_sparse_pauli
# TODO control numpy threading in a fixture for fair comparison


@pytest.fixture
def all_strings_for_qubits() -> list[str]:
"""Provide sample strings for testing."""
return lambda q: list(map("".join, it.product("IXYZ", repeat=q))) # type: ignore

def generate_paulis(qubits: int, limit: int = 1_000) -> list[str]:
strings: list[str] = []
for s in it.product("IXYZ", repeat=qubits):
if limit and len(strings) > limit:
break
strings.append("".join(s))
return strings

return generate_paulis # type: ignore


@pytest.fixture(scope="function")
def generate_random_complex(rng_seed: int = 321) -> np.ndarray:
"""Generate random complex numpy array with desired shape."""
rng = np.random.default_rng(rng_seed)
return lambda *shape: rng.random(shape) + 1j * rng.random(shape)


QUBITS_TO_BENCHMARK = [1, 2, 4, 10]


# following two helper functions are going to be removed once we align interfaces:
Expand All @@ -31,22 +51,29 @@ def benchmark_dense_conversion_py(paulis: list) -> None:


@pytest.mark.parametrize(
"lang,qubits,pauli_class,bench_func",
"pauli_class,qubits,lang,bench_func",
it.chain(
[("cpp", q, fp.PauliString, benchmark_dense_conversion_cpp) for q in [1, 2, 4]],
[("py", q, pp.PauliString, benchmark_dense_conversion_py) for q in [1, 2, 4]],
[
(fp.PauliString, q, "cpp", benchmark_dense_conversion_cpp)
for q in QUBITS_TO_BENCHMARK
],
[
(pp.PauliString, q, "py", benchmark_dense_conversion_py)
for q in QUBITS_TO_BENCHMARK
],
),
)
def test_dense_conversion_n_qubits( # type: ignore[no-untyped-def]
benchmark, all_strings_for_qubits, lang, qubits, pauli_class, bench_func
benchmark, all_strings_for_qubits, pauli_class, qubits, lang, bench_func
) -> None:
"""Benchmark dense conversion.
Parametrized test case to run the benchmark across
all Pauli strings of given length for given PauliString class.
"""
n_strings_limit = 10 if qubits > 4 else None
prepared_paulis = list(
map(lambda s: pauli_class(s), all_strings_for_qubits(qubits))
map(lambda s: pauli_class(s), all_strings_for_qubits(qubits, n_strings_limit))
)
benchmark(bench_func, paulis=prepared_paulis)

Expand All @@ -64,27 +91,35 @@ def benchmark_apply_py(paulis: list, states: list) -> None:


@pytest.mark.parametrize(
"lang,qubits,pauli_class,bench_func",
"pauli_class,qubits,lang,bench_func",
it.chain(
[("cpp", q, fp.PauliString, benchmark_apply_cpp) for q in [1, 2, 4]],
[("py", q, pp.PauliString, benchmark_apply_py) for q in [1, 2, 4]],
[(fp.PauliString, q, "cpp", benchmark_apply_cpp) for q in QUBITS_TO_BENCHMARK],
[(pp.PauliString, q, "py", benchmark_apply_py) for q in QUBITS_TO_BENCHMARK],
),
)
def test_apply_n_qubits( # type: ignore[no-untyped-def]
benchmark, all_strings_for_qubits, lang, qubits, pauli_class, bench_func
benchmark,
all_strings_for_qubits,
generate_random_complex,
pauli_class,
qubits,
lang,
bench_func,
) -> None:
"""Benchmark PauliString multiplication with provided state vector.
Parametrized test case to run the benchmark across
all Pauli strings of given length for given PauliString class.
"""
rng = np.random.default_rng(321)
dim = 1 << qubits
n_dims = 1 << qubits
n_strings_limit = 10 if qubits > 4 else None

prepared_paulis = list(
map(lambda s: pauli_class(s), all_strings_for_qubits(qubits))
map(lambda s: pauli_class(s), all_strings_for_qubits(qubits, n_strings_limit))
)
prepared_states = [rng.random(dim) for _ in range(len(prepared_paulis))]
prepared_states = [
generate_random_complex(n_dims) for _ in range(len(prepared_paulis))
]

benchmark(bench_func, paulis=prepared_paulis, states=prepared_states)

Expand All @@ -102,38 +137,47 @@ def benchmark_apply_batch_py(paulis: list, states: list) -> None:


@pytest.mark.parametrize(
"lang,qubits,states,pauli_class,bench_func",
"pauli_class,qubits,states,lang,bench_func",
it.chain(
[
("cpp", q, n, fp.PauliString, benchmark_apply_batch_cpp)
for q in [1, 2, 4]
(fp.PauliString, q, n, "cpp", benchmark_apply_batch_cpp)
for q in QUBITS_TO_BENCHMARK
for n in [16, 128]
],
[
("py", q, n, pp.PauliString, benchmark_apply_batch_py)
for q in [1, 2, 4]
(pp.PauliString, q, n, "py", benchmark_apply_batch_py)
for q in QUBITS_TO_BENCHMARK
for n in [16, 128]
],
),
)
def test_apply_batch_n_qubits( # type: ignore[no-untyped-def]
benchmark, all_strings_for_qubits, lang, qubits, states, pauli_class, bench_func
def test_apply_batch_n_qubits_n_states( # type: ignore[no-untyped-def]
benchmark,
all_strings_for_qubits,
generate_random_complex,
pauli_class,
qubits,
states,
lang,
bench_func,
) -> None:
"""Benchmark PauliString multiplication with provided set of state vectors.
Parametrized test case to run the benchmark across
all Pauli strings of given length for given PauliString class.
"""
rng = np.random.default_rng(321)
dim = 1 << qubits
n_dims = 1 << qubits
n_strings_limit = 10 if qubits > 4 else None

prepared_paulis = list(
map(lambda s: pauli_class(s), all_strings_for_qubits(qubits))
map(lambda s: pauli_class(s), all_strings_for_qubits(qubits, n_strings_limit))
)
prepared_states = [rng.random((dim, states)) for _ in range(len(prepared_paulis))]
prepared_states = [
generate_random_complex(n_dims, states) for _ in range(len(prepared_paulis))
]

benchmark(bench_func, paulis=prepared_paulis, states=prepared_states)


if __name__ == "__main__":
pytest.main()
pytest.main([__file__])

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