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fix types
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@maxbachmann
maxbachmann committed Dec 25, 2024
1 parent 6dc8807 commit a673a94
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Showing 6 changed files with 53 additions and 56 deletions.
67 changes: 32 additions & 35 deletions extras/rapidfuzz_amalgamated.hpp
View file
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
// Licensed under the MIT License <http://opensource.org/licenses/MIT>.
// SPDX-License-Identifier: MIT
// RapidFuzz v1.0.2
// Generated: 2024-12-25 01:42:39.581315
// Generated: 2024-12-25 02:01:10.995282
// ----------------------------------------------------------
// This file is an amalgamation of multiple different files.
// You probably shouldn't edit it directly.
Expand Down Expand Up @@ -592,7 +592,9 @@ Range(T& x) -> Range<decltype(to_begin(x))>;
template <typename InputIt1, typename InputIt2>
inline bool operator==(const Range<InputIt1>& a, const Range<InputIt2>& b)
{
return std::equal(a.begin(), a.end(), b.begin(), b.end());
if (a.size() != b.size()) return false;

return std::equal(a.begin(), a.end(), b.begin());
}

template <typename InputIt1, typename InputIt2>
Expand Down Expand Up @@ -978,13 +980,10 @@ class Editops : private std::vector<EditOp> {

inline bool operator==(const Editops& lhs, const Editops& rhs)
{
if (lhs.get_src_len() != rhs.get_src_len() || lhs.get_dest_len() != rhs.get_dest_len()) {
return false;
}
if (lhs.get_src_len() != rhs.get_src_len() || lhs.get_dest_len() != rhs.get_dest_len()) return false;

if (lhs.size() != rhs.size()) return false;

if (lhs.size() != rhs.size()) {
return false;
}
return std::equal(lhs.begin(), lhs.end(), rhs.begin());
}

Expand Down Expand Up @@ -1583,7 +1582,7 @@ struct UnrollImpl<T, N, Pos, true> {
{}
};

template <typename T, int N, class F>
template <typename T, T N, class F>
constexpr void unroll(F&& f)
{
UnrollImpl<T, N>::call(f);
Expand Down Expand Up @@ -4557,22 +4556,22 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const
size_t cur_vec = 0;
for (; cur_vec + interleaveCount * vecs <= block.size(); cur_vec += interleaveCount * vecs) {
std::array<native_simd<VecType>, interleaveCount> S;
unroll<int, interleaveCount>([&](auto j) { S[j] = static_cast<VecType>(-1); });
unroll<size_t, interleaveCount>([&](auto j) { S[j] = static_cast<VecType>(-1); });

for (const auto& ch : s2) {
unroll<int, interleaveCount>([&](auto j) {
unroll<size_t, interleaveCount>([&](auto j) {
alignas(32) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + j * vecs + i, ch); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + j * vecs + i, ch); });

native_simd<VecType> Matches(stored.data());
native_simd<VecType> u = S[j] & Matches;
S[j] = (S[j] + u) | (S[j] - u);
});
}

unroll<int, interleaveCount>([&](auto j) {
unroll<size_t, interleaveCount>([&](auto j) {
auto counts = popcount(~S[j]);
unroll<int, counts.size()>([&](auto i) {
unroll<size_t, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
Expand All @@ -4584,15 +4583,15 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const

for (const auto& ch : s2) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });

native_simd<VecType> Matches(stored.data());
native_simd<VecType> u = S & Matches;
S = (S + u) | (S - u);
}

auto counts = popcount(~S);
unroll<int, counts.size()>([&](auto i) {
unroll<size_t, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
Expand Down Expand Up @@ -4783,8 +4782,7 @@ size_t lcs_seq_similarity(const BlockPatternMatchVector& block, Range<InputIt1>
size_t max_misses = len1 + len2 - 2 * score_cutoff;

/* no edits are allowed */
if (max_misses == 0 || (max_misses == 1 && len1 == len2))
return std::equal(s1.begin(), s1.end(), s2.begin(), s2.end()) ? len1 : 0;
if (max_misses == 0 || (max_misses == 1 && len1 == len2)) return s1 == s2 ? len1 : 0;

if (max_misses < abs_diff(len1, len2)) return 0;

Expand Down Expand Up @@ -4816,8 +4814,7 @@ size_t lcs_seq_similarity(Range<InputIt1> s1, Range<InputIt2> s2, size_t score_c
size_t max_misses = len1 + len2 - 2 * score_cutoff;

/* no edits are allowed */
if (max_misses == 0 || (max_misses == 1 && len1 == len2))
return std::equal(s1.begin(), s1.end(), s2.begin(), s2.end()) ? len1 : 0;
if (max_misses == 0 || (max_misses == 1 && len1 == len2)) return s1 == s2 ? len1 : 0;

if (max_misses < abs_diff(len1, len2)) return 0;

Expand Down Expand Up @@ -5593,7 +5590,7 @@ static inline void flag_similar_characters_step(const BlockPatternMatchVector& P
if (T_j >= 0 && T_j < 256) {
for (; word + 3 < last_word - 1; word += 4) {
uint64_t PM_j[4];
unroll<int, 4>([&](auto i) {
unroll<size_t, 4>([&](auto i) {
PM_j[i] = PM.get(word + i, static_cast<uint8_t>(T_j)) & (~flagged.P_flag[word + i]);
});

Expand Down Expand Up @@ -6048,7 +6045,7 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
size_t j = 0;
for (; j < std::min(bounds.maxBound, s2_cur.size()); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand All @@ -6062,7 +6059,7 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa

for (; j < s2_cur.size(); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand Down Expand Up @@ -6165,7 +6162,7 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
size_t j = 0;
for (; j < std::min(bounds.maxBound, s2_cur.size()); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand All @@ -6178,7 +6175,7 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM

for (; j < s2_cur.size(); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand Down Expand Up @@ -7138,12 +7135,12 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
native_simd<VecType> VN(VecType(0));

alignas(alignment) std::array<VecType, vec_width> currDist_;
unroll<int, vec_width>(
unroll<size_t, vec_width>(
[&](auto i) { currDist_[i] = static_cast<VecType>(s1_lengths[result_index + i]); });
native_simd<VecType> currDist(reinterpret_cast<uint64_t*>(currDist_.data()));
/* mask used when computing D[m,j] in the paper 10^(m-1) */
alignas(alignment) std::array<VecType, vec_width> mask_;
unroll<int, vec_width>([&](auto i) {
unroll<size_t, vec_width>([&](auto i) {
if (s1_lengths[result_index + i] == 0)
mask_[i] = 0;
else
Expand All @@ -7154,7 +7151,7 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
for (const auto& ch : s2) {
/* Step 1: Computing D0 */
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });

native_simd<VecType> X(stored.data());
auto D0 = (((X & VP) + VP) ^ VP) | X | VN;
Expand All @@ -7178,7 +7175,7 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
alignas(alignment) std::array<VecType, vec_width> distances;
currDist.store(distances.data());

unroll<int, vec_width>([&](auto i) {
unroll<size_t, vec_width>([&](auto i) {
size_t score = 0;
/* strings of length 0 are not handled correctly */
if (s1_lengths[result_index] == 0) {
Expand Down Expand Up @@ -7649,7 +7646,7 @@ size_t uniform_levenshtein_distance(const BlockPatternMatchVector& block, Range<
if (score_hint < 31) score_hint = 31;

// when no differences are allowed a direct comparision is sufficient
if (score_cutoff == 0) return !std::equal(s1.begin(), s1.end(), s2.begin(), s2.end());
if (score_cutoff == 0) return s1 != s2;

if (score_cutoff < abs_diff(s1.size(), s2.size())) return score_cutoff + 1;

Expand Down Expand Up @@ -7707,7 +7704,7 @@ size_t uniform_levenshtein_distance(Range<InputIt1> s1, Range<InputIt2> s2, size
if (score_hint < 31) score_hint = 31;

// when no differences are allowed a direct comparision is sufficient
if (score_cutoff == 0) return !std::equal(s1.begin(), s1.end(), s2.begin(), s2.end());
if (score_cutoff == 0) return s1 != s2;

// at least length difference insertions/deletions required
if (score_cutoff < (s1.size() - s2.size())) return score_cutoff + 1;
Expand Down Expand Up @@ -8635,12 +8632,12 @@ void osa_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatternMatchV
native_simd<VecType> PM_j_old(VecType(0));

alignas(alignment) std::array<VecType, vec_width> currDist_;
unroll<int, vec_width>(
unroll<size_t, vec_width>(
[&](auto i) { currDist_[i] = static_cast<VecType>(s1_lengths[result_index + i]); });
native_simd<VecType> currDist(reinterpret_cast<uint64_t*>(currDist_.data()));
/* mask used when computing D[m,j] in the paper 10^(m-1) */
alignas(alignment) std::array<VecType, vec_width> mask_;
unroll<int, vec_width>([&](auto i) {
unroll<size_t, vec_width>([&](auto i) {
if (s1_lengths[result_index + i] == 0)
mask_[i] = 0;
else
Expand All @@ -8651,7 +8648,7 @@ void osa_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatternMatchV
for (const auto& ch : s2) {
/* Step 1: Computing D0 */
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });

native_simd<VecType> PM_j(stored.data());
auto TR = (andnot(PM_j, D0) << 1) & PM_j_old;
Expand All @@ -8678,7 +8675,7 @@ void osa_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatternMatchV
alignas(alignment) std::array<VecType, vec_width> distances;
currDist.store(distances.data());

unroll<int, vec_width>([&](auto i) {
unroll<size_t, vec_width>([&](auto i) {
size_t score = 0;
/* strings of length 0 are not handled correctly */
if (s1_lengths[result_index] == 0) {
Expand Down
2 changes: 1 addition & 1 deletion rapidfuzz/details/intrinsics.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -218,7 +218,7 @@ struct UnrollImpl<T, N, Pos, true> {
{}
};

template <typename T, int N, class F>
template <typename T, T N, class F>
constexpr void unroll(F&& f)
{
UnrollImpl<T, N>::call(f);
Expand Down
10 changes: 5 additions & 5 deletions rapidfuzz/distance/Jaro_impl.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -161,7 +161,7 @@ static inline void flag_similar_characters_step(const BlockPatternMatchVector& P
if (T_j >= 0 && T_j < 256) {
for (; word + 3 < last_word - 1; word += 4) {
uint64_t PM_j[4];
unroll<int, 4>([&](auto i) {
unroll<size_t, 4>([&](auto i) {
PM_j[i] = PM.get(word + i, static_cast<uint8_t>(T_j)) & (~flagged.P_flag[word + i]);
});

Expand Down Expand Up @@ -616,7 +616,7 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
size_t j = 0;
for (; j < std::min(bounds.maxBound, s2_cur.size()); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand All @@ -630,7 +630,7 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa

for (; j < s2_cur.size(); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand Down Expand Up @@ -733,7 +733,7 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
size_t j = 0;
for (; j < std::min(bounds.maxBound, s2_cur.size()); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand All @@ -746,7 +746,7 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM

for (; j < s2_cur.size(); ++j) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, s2_cur[j]); });
native_simd<VecType> X(stored.data());
native_simd<VecType> PM_j = andnot(X & bounds.boundMask, P_flag);

Expand Down
14 changes: 7 additions & 7 deletions rapidfuzz/distance/LCSseq_impl.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -158,22 +158,22 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const
size_t cur_vec = 0;
for (; cur_vec + interleaveCount * vecs <= block.size(); cur_vec += interleaveCount * vecs) {
std::array<native_simd<VecType>, interleaveCount> S;
unroll<int, interleaveCount>([&](auto j) { S[j] = static_cast<VecType>(-1); });
unroll<size_t, interleaveCount>([&](auto j) { S[j] = static_cast<VecType>(-1); });

for (const auto& ch : s2) {
unroll<int, interleaveCount>([&](auto j) {
unroll<size_t, interleaveCount>([&](auto j) {
alignas(32) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + j * vecs + i, ch); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + j * vecs + i, ch); });

native_simd<VecType> Matches(stored.data());
native_simd<VecType> u = S[j] & Matches;
S[j] = (S[j] + u) | (S[j] - u);
});
}

unroll<int, interleaveCount>([&](auto j) {
unroll<size_t, interleaveCount>([&](auto j) {
auto counts = popcount(~S[j]);
unroll<int, counts.size()>([&](auto i) {
unroll<size_t, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
Expand All @@ -185,15 +185,15 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const

for (const auto& ch : s2) {
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });

native_simd<VecType> Matches(stored.data());
native_simd<VecType> u = S & Matches;
S = (S + u) | (S - u);
}

auto counts = popcount(~S);
unroll<int, counts.size()>([&](auto i) {
unroll<size_t, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
Expand Down
8 changes: 4 additions & 4 deletions rapidfuzz/distance/Levenshtein_impl.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -347,12 +347,12 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
native_simd<VecType> VN(VecType(0));

alignas(alignment) std::array<VecType, vec_width> currDist_;
unroll<int, vec_width>(
unroll<size_t, vec_width>(
[&](auto i) { currDist_[i] = static_cast<VecType>(s1_lengths[result_index + i]); });
native_simd<VecType> currDist(reinterpret_cast<uint64_t*>(currDist_.data()));
/* mask used when computing D[m,j] in the paper 10^(m-1) */
alignas(alignment) std::array<VecType, vec_width> mask_;
unroll<int, vec_width>([&](auto i) {
unroll<size_t, vec_width>([&](auto i) {
if (s1_lengths[result_index + i] == 0)
mask_[i] = 0;
else
Expand All @@ -363,7 +363,7 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
for (const auto& ch : s2) {
/* Step 1: Computing D0 */
alignas(alignment) std::array<uint64_t, vecs> stored;
unroll<int, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });
unroll<size_t, vecs>([&](auto i) { stored[i] = block.get(cur_vec + i, ch); });

native_simd<VecType> X(stored.data());
auto D0 = (((X & VP) + VP) ^ VP) | X | VN;
Expand All @@ -387,7 +387,7 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
alignas(alignment) std::array<VecType, vec_width> distances;
currDist.store(distances.data());

unroll<int, vec_width>([&](auto i) {
unroll<size_t, vec_width>([&](auto i) {
size_t score = 0;
/* strings of length 0 are not handled correctly */
if (s1_lengths[result_index] == 0) {
Expand Down
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