mirror of
https://github.com/zebrajr/pytorch.git
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6384c2d81b
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35115 This commit runs the newly added tools/clang_format.py on the JIT codebase and includes all of the formatting changes thus produced. Testing: Ran the script, CI. Test Plan: Imported from OSS Reviewed By: eellison Differential Revision: D20568523 Pulled By: SplitInfinity fbshipit-source-id: e09bdb982ccf090eecfb7c7b461b8d0681eef82b
55 lines
1.4 KiB
C++
55 lines
1.4 KiB
C++
#include <torch/csrc/jit/frontend/edit_distance.h>
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#include <algorithm>
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#include <cstring>
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#include <memory>
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namespace torch {
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namespace jit {
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// computes levenshtein edit distance between two words
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// returns maxEditDistance + 1 if the edit distance exceeds MaxEditDistance
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// reference: http://llvm.org/doxygen/edit__distance_8h_source.html
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size_t ComputeEditDistance(
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const char* word1,
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const char* word2,
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size_t maxEditDistance) {
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size_t m = strlen(word1);
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size_t n = strlen(word2);
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const unsigned small_buffer_size = 64;
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unsigned small_buffer[small_buffer_size];
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std::unique_ptr<unsigned[]> allocated;
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unsigned* row = small_buffer;
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if (n + 1 > small_buffer_size) {
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row = new unsigned[n + 1];
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allocated.reset(row);
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}
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for (unsigned i = 1; i <= n; ++i)
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row[i] = i;
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for (size_t y = 1; y <= m; ++y) {
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row[0] = y;
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unsigned best_this_row = row[0];
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unsigned previous = y - 1;
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for (size_t x = 1; x <= n; ++x) {
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int old_row = row[x];
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row[x] = std::min(
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previous + (word1[y - 1] == word2[x - 1] ? 0u : 1u),
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std::min(row[x - 1], row[x]) + 1);
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previous = old_row;
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best_this_row = std::min(best_this_row, row[x]);
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}
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if (maxEditDistance && best_this_row > maxEditDistance)
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return maxEditDistance + 1;
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}
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unsigned result = row[n];
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return result;
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}
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} // namespace jit
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} // namespace torch
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