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fix compilation warnings on 32bit systems
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@maxbachmann
maxbachmann committed Oct 24, 2024
1 parent 179c89f commit c5cfc1c
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Showing 6 changed files with 55 additions and 49 deletions.
58 changes: 32 additions & 26 deletions extras/rapidfuzz_amalgamated.hpp
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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: 2024-10-24 14:07:33.184436
// Generated: 2024-10-24 14:15:39.050296
// ----------------------------------------------------------
// This file is an amalgamation of multiple different files.
// You probably shouldn't edit it directly.
Expand Down Expand Up @@ -3572,7 +3572,7 @@ struct MultiSimilarityBase : public MultiNormalizedMetricBase<T, ResType> {

template <typename Sentence2>
void distance(ResType* scores, size_t score_count, const Sentence2& s2,
ResType score_cutoff = WorstDistance) const
ResType score_cutoff = static_cast<ResType>(WorstDistance)) const
{
_distance(scores, score_count, Range(s2), score_cutoff);
}
Expand Down Expand Up @@ -3671,26 +3671,26 @@ size_t damerau_levenshtein_distance_zhao(const Range<InputIt1>& s1, const Range<

auto iter_s2 = s2.begin();
for (IntType j = 1; j <= len2; j++) {
ptrdiff_t diag = R1[j - 1] + static_cast<IntType>(*iter_s1 != *iter_s2);
ptrdiff_t left = R[j - 1] + 1;
ptrdiff_t up = R1[j] + 1;
ptrdiff_t temp = std::min({diag, left, up});
int64_t diag = R1[j - 1] + static_cast<IntType>(*iter_s1 != *iter_s2);
int64_t left = R[j - 1] + 1;
int64_t up = R1[j] + 1;
int64_t temp = std::min({diag, left, up});

if (*iter_s1 == *iter_s2) {
last_col_id = j; // last occurence of s1_i
FR[j] = R1[j - 2]; // save H_k-1,j-2
T = last_i2l1; // save H_i-2,l-1
}
else {
ptrdiff_t k = last_row_id.get(static_cast<uint64_t>(*iter_s2)).val;
ptrdiff_t l = last_col_id;
int64_t k = last_row_id.get(static_cast<uint64_t>(*iter_s2)).val;
int64_t l = last_col_id;

if ((j - l) == 1) {
ptrdiff_t transpose = FR[j] + (i - k);
int64_t transpose = FR[j] + (i - k);
temp = std::min(temp, transpose);
}
else if ((i - k) == 1) {
ptrdiff_t transpose = T + (j - l);
int64_t transpose = T + (j - l);
temp = std::min(temp, transpose);
}
}
Expand Down Expand Up @@ -4482,7 +4482,7 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const
unroll<int, interleaveCount>([&](auto j) {
auto counts = popcount(~S[j]);
unroll<int, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? counts[i] : 0;
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
});
Expand All @@ -4502,7 +4502,7 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const

auto counts = popcount(~S);
unroll<int, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? counts[i] : 0;
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
}
Expand Down Expand Up @@ -5614,7 +5614,8 @@ static inline size_t count_transpositions_block(const BlockPatternMatchVector& P

uint64_t PatternFlagMask = blsi(P_flag);

Transpositions += !(PM.get(PatternWord, T_first[countr_zero(T_flag)]) & PatternFlagMask);
Transpositions += !(PM.get(PatternWord, T_first[static_cast<ptrdiff_t>(countr_zero(T_flag))]) &
PatternFlagMask);

T_flag = blsr(T_flag);
P_flag ^= PatternFlagMask;
Expand Down Expand Up @@ -5823,7 +5824,7 @@ static inline auto jaro_similarity_prepare_bound_short_s2(const VecType* s1_leng

// todo try to find a simd implementation for sse2
for (size_t i = 0; i < vec_width; ++i) {
size_t Bound = jaro_bounds(s1_lengths[i], s2.size());
size_t Bound = jaro_bounds(static_cast<size_t>(s1_lengths[i]), s2.size());

if (Bound > bounds.maxBound) bounds.maxBound = Bound;

Expand All @@ -5835,7 +5836,7 @@ static inline auto jaro_similarity_prepare_bound_short_s2(const VecType* s1_leng
bounds.boundMask = native_simd<VecType>(reinterpret_cast<uint64_t*>(boundMask_.data()));
# endif

size_t lastRelevantChar = maxLen + bounds.maxBound;
size_t lastRelevantChar = static_cast<size_t>(maxLen) + bounds.maxBound;
if (s2.size() > lastRelevantChar) s2.remove_suffix(s2.size() - lastRelevantChar);

return bounds;
Expand Down Expand Up @@ -5865,7 +5866,7 @@ static inline auto jaro_similarity_prepare_bound_long_s2(const VecType* s1_lengt
bounds.boundMaskSize = native_simd<VecType>(bit_mask_lsb<VecType>(2 * bounds.maxBound));
bounds.boundMask = native_simd<VecType>(bit_mask_lsb<VecType>(bounds.maxBound + 1));

size_t lastRelevantChar = maxLen + bounds.maxBound;
size_t lastRelevantChar = static_cast<size_t>(maxLen) + bounds.maxBound;
if (s2.size() > lastRelevantChar) s2.remove_suffix(s2.size() - lastRelevantChar);

return bounds;
Expand Down Expand Up @@ -5966,8 +5967,10 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
T_flag[i].store(T_flags + i * vec_width);

for (size_t i = 0; i < vec_width; ++i) {
VecType CommonChars = counts[i];
if (!jaro_common_char_filter(s1_lengths[result_index], s2.size(), CommonChars, score_cutoff)) {
size_t CommonChars = static_cast<size_t>(counts[i]);
if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
CommonChars, score_cutoff))
{
scores[result_index] = 0.0;
result_index++;
continue;
Expand Down Expand Up @@ -6001,8 +6004,8 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
}
}

double Sim =
jaro_calculate_similarity(s1_lengths[result_index], s2.size(), CommonChars, Transpositions);
double Sim = jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
CommonChars, Transpositions);

scores[result_index] = (Sim >= score_cutoff) ? Sim : 0;
result_index++;
Expand Down Expand Up @@ -6077,8 +6080,10 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
alignas(alignment) std::array<VecType, vec_width> T_flags;
T_flag.store(T_flags.data());
for (size_t i = 0; i < vec_width; ++i) {
VecType CommonChars = counts[i];
if (!jaro_common_char_filter(s1_lengths[result_index], s2.size(), CommonChars, score_cutoff)) {
size_t CommonChars = static_cast<size_t>(counts[i]);
if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
CommonChars, score_cutoff))
{
scores[result_index] = 0.0;
result_index++;
continue;
Expand All @@ -6101,8 +6106,8 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
P_flag_cur ^= PatternFlagMask;
}

double Sim =
jaro_calculate_similarity(s1_lengths[result_index], s2.size(), CommonChars, Transpositions);
double Sim = jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
CommonChars, Transpositions);

scores[result_index] = (Sim >= score_cutoff) ? Sim : 0;
result_index++;
Expand Down Expand Up @@ -7027,7 +7032,7 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
}
/* calculate score under consideration of wraparounds in parallel counter */
else {
if constexpr (std::numeric_limits<VecType>::max() < std::numeric_limits<size_t>::max()) {
if constexpr (!std::is_same_v<VecType, uint64_t>) {
size_t min_dist = abs_diff(s1_lengths[result_index], s2.size());
size_t wraparound_score = static_cast<size_t>(std::numeric_limits<VecType>::max()) + 1;

Expand Down Expand Up @@ -7391,7 +7396,8 @@ auto levenshtein_hyrroe2003_block(const BlockPatternMatchVector& PM, const Range
vecs[last_block].VN = 0;

size_t chars_in_block = (last_block + 1 == words) ? ((s1.size() - 1) % word_size + 1) : 64;
scores[last_block] = scores[last_block - 1] + chars_in_block - HP_carry + HN_carry;
scores[last_block] = scores[last_block - 1] + chars_in_block - static_cast<size_t>(HP_carry) +
static_cast<size_t>(HN_carry);
// todo probably wrong types
scores[last_block] = static_cast<size_t>(static_cast<ptrdiff_t>(scores[last_block]) +
advance_block(last_block));
Expand Down
2 changes: 1 addition & 1 deletion rapidfuzz/details/distance.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -501,7 +501,7 @@ struct MultiSimilarityBase : public MultiNormalizedMetricBase<T, ResType> {

template <typename Sentence2>
void distance(ResType* scores, size_t score_count, const Sentence2& s2,
ResType score_cutoff = WorstDistance) const
ResType score_cutoff = static_cast<ResType>(WorstDistance)) const
{
_distance(scores, score_count, Range(s2), score_cutoff);
}
Expand Down
16 changes: 8 additions & 8 deletions rapidfuzz/distance/DamerauLevenshtein_impl.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -64,26 +64,26 @@ size_t damerau_levenshtein_distance_zhao(const Range<InputIt1>& s1, const Range<

auto iter_s2 = s2.begin();
for (IntType j = 1; j <= len2; j++) {
ptrdiff_t diag = R1[j - 1] + static_cast<IntType>(*iter_s1 != *iter_s2);
ptrdiff_t left = R[j - 1] + 1;
ptrdiff_t up = R1[j] + 1;
ptrdiff_t temp = std::min({diag, left, up});
int64_t diag = R1[j - 1] + static_cast<IntType>(*iter_s1 != *iter_s2);
int64_t left = R[j - 1] + 1;
int64_t up = R1[j] + 1;
int64_t temp = std::min({diag, left, up});

if (*iter_s1 == *iter_s2) {
last_col_id = j; // last occurence of s1_i
FR[j] = R1[j - 2]; // save H_k-1,j-2
T = last_i2l1; // save H_i-2,l-1
}
else {
ptrdiff_t k = last_row_id.get(static_cast<uint64_t>(*iter_s2)).val;
ptrdiff_t l = last_col_id;
int64_t k = last_row_id.get(static_cast<uint64_t>(*iter_s2)).val;
int64_t l = last_col_id;

if ((j - l) == 1) {
ptrdiff_t transpose = FR[j] + (i - k);
int64_t transpose = FR[j] + (i - k);
temp = std::min(temp, transpose);
}
else if ((i - k) == 1) {
ptrdiff_t transpose = T + (j - l);
int64_t transpose = T + (j - l);
temp = std::min(temp, transpose);
}
}
Expand Down
20 changes: 10 additions & 10 deletions rapidfuzz/distance/Jaro_impl.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -296,7 +296,7 @@ static inline size_t count_transpositions_block(const BlockPatternMatchVector& P

uint64_t PatternFlagMask = blsi(P_flag);

Transpositions += !(PM.get(PatternWord, T_first[countr_zero(T_flag)]) & PatternFlagMask);
Transpositions += !(PM.get(PatternWord, T_first[static_cast<ptrdiff_t>(countr_zero(T_flag))]) & PatternFlagMask);

T_flag = blsr(T_flag);
P_flag ^= PatternFlagMask;
Expand Down Expand Up @@ -505,7 +505,7 @@ static inline auto jaro_similarity_prepare_bound_short_s2(const VecType* s1_leng

// todo try to find a simd implementation for sse2
for (size_t i = 0; i < vec_width; ++i) {
size_t Bound = jaro_bounds(s1_lengths[i], s2.size());
size_t Bound = jaro_bounds(static_cast<size_t>(s1_lengths[i]), s2.size());

if (Bound > bounds.maxBound) bounds.maxBound = Bound;

Expand All @@ -517,7 +517,7 @@ static inline auto jaro_similarity_prepare_bound_short_s2(const VecType* s1_leng
bounds.boundMask = native_simd<VecType>(reinterpret_cast<uint64_t*>(boundMask_.data()));
# endif

size_t lastRelevantChar = maxLen + bounds.maxBound;
size_t lastRelevantChar = static_cast<size_t>(maxLen) + bounds.maxBound;
if (s2.size() > lastRelevantChar) s2.remove_suffix(s2.size() - lastRelevantChar);

return bounds;
Expand Down Expand Up @@ -547,7 +547,7 @@ static inline auto jaro_similarity_prepare_bound_long_s2(const VecType* s1_lengt
bounds.boundMaskSize = native_simd<VecType>(bit_mask_lsb<VecType>(2 * bounds.maxBound));
bounds.boundMask = native_simd<VecType>(bit_mask_lsb<VecType>(bounds.maxBound + 1));

size_t lastRelevantChar = maxLen + bounds.maxBound;
size_t lastRelevantChar = static_cast<size_t>(maxLen) + bounds.maxBound;
if (s2.size() > lastRelevantChar) s2.remove_suffix(s2.size() - lastRelevantChar);

return bounds;
Expand Down Expand Up @@ -648,8 +648,8 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
T_flag[i].store(T_flags + i * vec_width);

for (size_t i = 0; i < vec_width; ++i) {
VecType CommonChars = counts[i];
if (!jaro_common_char_filter(s1_lengths[result_index], s2.size(), CommonChars, score_cutoff)) {
size_t CommonChars = static_cast<size_t>(counts[i]);
if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, score_cutoff)) {
scores[result_index] = 0.0;
result_index++;
continue;
Expand Down Expand Up @@ -684,7 +684,7 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
}

double Sim =
jaro_calculate_similarity(s1_lengths[result_index], s2.size(), CommonChars, Transpositions);
jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, Transpositions);

scores[result_index] = (Sim >= score_cutoff) ? Sim : 0;
result_index++;
Expand Down Expand Up @@ -759,8 +759,8 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
alignas(alignment) std::array<VecType, vec_width> T_flags;
T_flag.store(T_flags.data());
for (size_t i = 0; i < vec_width; ++i) {
VecType CommonChars = counts[i];
if (!jaro_common_char_filter(s1_lengths[result_index], s2.size(), CommonChars, score_cutoff)) {
size_t CommonChars = static_cast<size_t>(counts[i]);
if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, score_cutoff)) {
scores[result_index] = 0.0;
result_index++;
continue;
Expand All @@ -784,7 +784,7 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
}

double Sim =
jaro_calculate_similarity(s1_lengths[result_index], s2.size(), CommonChars, Transpositions);
jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, Transpositions);

scores[result_index] = (Sim >= score_cutoff) ? Sim : 0;
result_index++;
Expand Down
4 changes: 2 additions & 2 deletions rapidfuzz/distance/LCSseq_impl.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -159,7 +159,7 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const
unroll<int, interleaveCount>([&](auto j) {
auto counts = popcount(~S[j]);
unroll<int, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? counts[i] : 0;
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
});
Expand All @@ -179,7 +179,7 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const

auto counts = popcount(~S);
unroll<int, counts.size()>([&](auto i) {
*score_iter = (counts[i] >= score_cutoff) ? counts[i] : 0;
*score_iter = (counts[i] >= score_cutoff) ? static_cast<size_t>(counts[i]) : 0;
score_iter++;
});
}
Expand Down
4 changes: 2 additions & 2 deletions rapidfuzz/distance/Levenshtein_impl.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -363,7 +363,7 @@ void levenshtein_hyrroe2003_simd(Range<size_t*> scores, const detail::BlockPatte
}
/* calculate score under consideration of wraparounds in parallel counter */
else {
if constexpr (std::numeric_limits<VecType>::max() < std::numeric_limits<size_t>::max()) {
if constexpr (!std::is_same_v<VecType, uint64_t>) {
size_t min_dist = abs_diff(s1_lengths[result_index], s2.size());
size_t wraparound_score = static_cast<size_t>(std::numeric_limits<VecType>::max()) + 1;

Expand Down Expand Up @@ -727,7 +727,7 @@ auto levenshtein_hyrroe2003_block(const BlockPatternMatchVector& PM, const Range
vecs[last_block].VN = 0;

size_t chars_in_block = (last_block + 1 == words) ? ((s1.size() - 1) % word_size + 1) : 64;
scores[last_block] = scores[last_block - 1] + chars_in_block - HP_carry + HN_carry;
scores[last_block] = scores[last_block - 1] + chars_in_block - static_cast<size_t>(HP_carry) + static_cast<size_t>(HN_carry);
// todo probably wrong types
scores[last_block] = static_cast<size_t>(static_cast<ptrdiff_t>(scores[last_block]) +
advance_block(last_block));
Expand Down

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