From 26b74fda76fdcd076c79cc4051c69a344562cfa7 Mon Sep 17 00:00:00 2001 From: Griffin Bassman Date: Fri, 17 Nov 2023 10:08:07 -0500 Subject: [PATCH] refactor: use standard library for inverse sqrt (#4665) * use standard library for inverse sqrt * fix sklearn tests * fix diff --- python/vowpalwabbit/sklearn.py | 12 +- test/pred-sets/ref/poisson.train.predict | 198 +- test/train-sets/ref/automl_readable.txt | 2756 +-- test/train-sets/ref/automl_readable_cubic.txt | 19878 ++++++++-------- test/train-sets/ref/automl_readable_qc.txt | 2850 +-- test/train-sets/ref/cb_adf_dm.stderr | 2 +- test/train-sets/ref/cbadf_automl_readable.txt | 2756 +-- test/train-sets/ref/sparse.stderr | 2 +- vowpalwabbit/core/src/reductions/gd.cc | 45 +- 9 files changed, 14228 insertions(+), 14271 deletions(-) diff --git a/python/vowpalwabbit/sklearn.py b/python/vowpalwabbit/sklearn.py index f142a9a6e38..f35d723ec96 100644 --- a/python/vowpalwabbit/sklearn.py +++ b/python/vowpalwabbit/sklearn.py @@ -738,12 +738,12 @@ class would be predicted. >>> model = VWMultiClassifier(oaa=3, loss_function='logistic') >>> _ = model.fit(X, y) >>> model.predict_proba(X) - array([[0.38924146, 0.30537927, 0.30537927], - [0.40661219, 0.29669389, 0.29669389], - [0.52335149, 0.23832427, 0.23832427], - [0.52696788, 0.23651604, 0.23651604], - [0.65430814, 0.17284594, 0.17284594], - [0.61224216, 0.19387889, 0.19387889]]) + array([[0.38926664, 0.30536669, 0.30536669], + [0.40663728, 0.2966814 , 0.2966814 ], + [0.52337217, 0.23831393, 0.23831393], + [0.52698863, 0.23650573, 0.23650573], + [0.6543135 , 0.17284323, 0.17284323], + [0.61224902, 0.19387549, 0.19387549]]) """ return VW.predict(self, X=X) diff --git a/test/pred-sets/ref/poisson.train.predict b/test/pred-sets/ref/poisson.train.predict index bc1683b20e4..ec594539f3e 100644 --- a/test/pred-sets/ref/poisson.train.predict +++ b/test/pred-sets/ref/poisson.train.predict @@ -1,100 +1,100 @@ 1 -3.799717 -1.758895 -2.823944 -3.418083 -3.174116 -4.399955 -6.617443 -9.925587 -6.859698 -9.062473 -10.236777 -4.409184 -16.511784 -13.219240 -5.015990 -8.376214 -4.853359 -4.775251 -10.194923 -3.586257 -7.299780 -3.085816 -19.471279 -6.456569 -5.083687 -5.718489 -4.165322 -4.801548 -12.160492 -11.505902 -7.201016 -8.249208 -3.413971 -11.563130 -10.683638 -8.653486 -6.696140 -7.353734 -4.634882 -20.726450 -4.390856 -6.037433 -17.106670 -5.407927 -5.619127 -8.686151 -12.502230 -3.594334 -3.730500 -15.105044 -13.844496 -16.222132 -5.544982 -3.611238 -14.929321 -23.313150 -5.492814 -4.416268 -6.741525 -8.565622 -10.134159 -21.189169 -6.113652 -12.738751 -5.251778 -8.007408 -6.202647 -22.053446 -18.842344 -10.703218 -9.388963 -6.564823 -4.188909 -6.913012 -3.585745 -11.230138 -10.335607 -9.245808 -13.397093 -10.333648 -4.940864 -16.954252 -3.094200 -13.083524 -17.795330 -14.321293 -11.400364 -21.311798 -8.588335 -8.495510 -6.460412 -12.288263 -6.253819 -8.273765 -4.329605 -3.374068 -4.934896 -4.281456 -6.190218 +3.800619 +1.758935 +2.824216 +3.418108 +3.174257 +4.400357 +6.617925 +9.926342 +6.860019 +9.062867 +10.237043 +4.409323 +16.512039 +13.219710 +5.016036 +8.376304 +4.853390 +4.775280 +10.194972 +3.586254 +7.299616 +3.085841 +19.471577 +6.456658 +5.083767 +5.718542 +4.165406 +4.801608 +12.160570 +11.506034 +7.201034 +8.249253 +3.414075 +11.563263 +10.683724 +8.653652 +6.696215 +7.353841 +4.634963 +20.726303 +4.390929 +6.037502 +17.106434 +5.407959 +5.619164 +8.686163 +12.502134 +3.594335 +3.730505 +15.104943 +13.844918 +16.222507 +5.545042 +3.611302 +14.929578 +23.313255 +5.492844 +4.416314 +6.741583 +8.565572 +10.134337 +21.189093 +6.113706 +12.738770 +5.251884 +8.007589 +6.202812 +22.053951 +18.843071 +10.703443 +9.389182 +6.564854 +4.188958 +6.913089 +3.585796 +11.230267 +10.335644 +9.245924 +13.396866 +10.333596 +4.940830 +16.954107 +3.094223 +13.083464 +17.795250 +14.321327 +11.400293 +21.311584 +8.588274 +8.495458 +6.460392 +12.288342 +6.253785 +8.273701 +4.329561 +3.374042 +4.934813 +4.281405 +6.190152 diff --git a/test/train-sets/ref/automl_readable.txt b/test/train-sets/ref/automl_readable.txt index d5bfd667b7a..9741685df7d 100644 --- a/test/train-sets/ref/automl_readable.txt +++ b/test/train-sets/ref/automl_readable.txt @@ -1,5 +1,5 @@ Version 9.9.0 -Id +Id Min label:-1 Max label:0 bits:18 @@ -556,1380 +556,1380 @@ sd::oec.weighted_labeled_examples 3 current_pass 1 l1_state 0 l2_state 1 -824:-0.00344349 0.273984 1 -825:-0.00350212 0.273083 1 -826:-0.00356218 0.272238 1 -2064:-0.0766733 0.00136382 0.0389047 -2065:-0.078847 0.00135622 0.0389047 -2066:-0.0811653 0.00134847 0.0389047 -2220:-0.00298373 0.90106 1 -2221:-0.00306774 0.896037 1 -2222:-0.00315794 0.890915 1 -2344:0.17543 4.43607e-06 0.003 -2345:0.17433 4.39086e-06 0.003 -2346:0.172419 4.34476e-06 0.003 -2768:-0.00406582 0.196591 0.847071 -2769:-0.00413391 0.195945 0.847071 -2770:-0.00420527 0.195339 0.847071 -2868:-8.75044 4.24447e-08 0.000393595 -2869:-8.89817 4.23052e-08 0.000393595 -2870:-9.0511 4.21743e-08 0.000393595 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0.000320934 +262125:-0.12605 8.40806e-08 0.000320934 +262126:-0.126185 8.40806e-08 0.000320934 diff --git a/test/train-sets/ref/automl_readable_qc.txt b/test/train-sets/ref/automl_readable_qc.txt index 6a86a395308..7e0531228c9 100644 --- a/test/train-sets/ref/automl_readable_qc.txt +++ b/test/train-sets/ref/automl_readable_qc.txt @@ -1,5 +1,5 @@ Version 9.9.0 -Id +Id Min label:-1 Max label:0 bits:18 @@ -1801,1428 +1801,1428 @@ sd::oec.weighted_labeled_examples 3 current_pass 1 l1_state 0 l2_state 1 -824:-0.00344349 0.273984 1 -825:-0.00338733 0.274929 1 -826:-0.00333381 0.275914 1 -2064:-0.0766733 0.00136382 0.0389047 -2065:-0.0746501 0.00137127 0.0389047 -2066:-0.0727064 0.00137856 0.0389047 -2220:-0.00298373 0.90106 1 -2221:-0.00290389 0.90598 1 -2222:-0.00282899 0.910799 1 -2344:0.17543 4.43607e-06 0.003 -2345:0.176529 4.48035e-06 0.003 -2346:0.176805 4.52372e-06 0.003 -2768:-0.00406582 0.196591 0.847071 -2769:-0.00399887 0.19727 0.847071 -2770:-0.00393627 0.197976 0.847071 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0.00930113 +261348:-80.5418 1.23618e-09 3.70393e-05 +261349:-78.393 1.24293e-09 3.70393e-05 +261350:-76.3624 1.24954e-09 3.70393e-05 +261792:-0.677503 1.74703e-05 0.00440325 +261793:-0.659427 1.75657e-05 0.00440325 +261794:-0.642347 1.76591e-05 0.00440325 +261992:-0.121831 0.000218943 0.0282685 +261993:-0.119851 0.0002197 0.0282685 +261994:-0.117944 0.000220485 0.0282685 diff --git a/test/train-sets/ref/cb_adf_dm.stderr b/test/train-sets/ref/cb_adf_dm.stderr index fb0df691fe4..0904acde7e8 100644 --- a/test/train-sets/ref/cb_adf_dm.stderr +++ b/test/train-sets/ref/cb_adf_dm.stderr @@ -13,7 +13,7 @@ Output pred = ACTION_SCORES average since example example current current current loss last counter weight label predict features 2.000000 2.000000 1 1.0 0:1:0.5 0:0 18 -1.000000 0.000000 2 2.0 1:0:0.5 1:-0.08 8 +1.000000 0.000000 2 2.0 1:0:0.5 1:-0.09 8 finished run number of examples = 3 diff --git a/test/train-sets/ref/cbadf_automl_readable.txt b/test/train-sets/ref/cbadf_automl_readable.txt index 0f36529c285..123dd020e24 100644 --- a/test/train-sets/ref/cbadf_automl_readable.txt +++ b/test/train-sets/ref/cbadf_automl_readable.txt @@ -1,5 +1,5 @@ Version 9.9.0 -Id +Id Min label:-1 Max label:0 bits:18 @@ -556,1380 +556,1380 @@ sd::oec.weighted_labeled_examples 2 current_pass 1 l1_state 0 l2_state 1 -824:-0.00344349 0.273984 1 -825:-0.00350212 0.273083 1 -826:-0.00356218 0.272238 1 -2064:-0.0766733 0.00136382 0.0389047 -2065:-0.078847 0.00135622 0.0389047 -2066:-0.0811653 0.00134847 0.0389047 -2220:-0.00298373 0.90106 1 -2221:-0.00306774 0.896037 1 -2222:-0.00315794 0.890915 1 -2344:0.17543 4.43607e-06 0.003 -2345:0.17433 4.39086e-06 0.003 -2346:0.172419 4.34476e-06 0.003 -2768:-0.00406582 0.196591 0.847071 -2769:-0.00413391 0.195945 0.847071 -2770:-0.00420527 0.195339 0.847071 -2868:-8.75044 4.24447e-08 0.000393595 -2869:-8.89817 4.23052e-08 0.000393595 -2870:-9.0511 4.21743e-08 0.000393595 -2928:-7.07343 1.60275e-07 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0.00930113 +261348:-80.5418 1.23618e-09 3.70393e-05 +261349:-82.8193 1.22929e-09 3.70393e-05 +261350:-85.238 1.22226e-09 3.70393e-05 +261792:-0.677503 1.74703e-05 0.00440325 +261793:-0.696661 1.7373e-05 0.00440325 +261794:-0.717007 1.72736e-05 0.00440325 +261992:-0.121831 0.000218943 0.0282685 +261993:-0.123889 0.000218224 0.0282685 +261994:-0.126031 0.000217547 0.0282685 diff --git a/test/train-sets/ref/sparse.stderr b/test/train-sets/ref/sparse.stderr index fb0df691fe4..0904acde7e8 100644 --- a/test/train-sets/ref/sparse.stderr +++ b/test/train-sets/ref/sparse.stderr @@ -13,7 +13,7 @@ Output pred = ACTION_SCORES average since example example current current current loss last counter weight label predict features 2.000000 2.000000 1 1.0 0:1:0.5 0:0 18 -1.000000 0.000000 2 2.0 1:0:0.5 1:-0.08 8 +1.000000 0.000000 2 2.0 1:0:0.5 1:-0.09 8 finished run number of examples = 3 diff --git a/vowpalwabbit/core/src/reductions/gd.cc b/vowpalwabbit/core/src/reductions/gd.cc index 8ac8ac6a7f4..d98b994306a 100644 --- a/vowpalwabbit/core/src/reductions/gd.cc +++ b/vowpalwabbit/core/src/reductions/gd.cc @@ -136,49 +136,6 @@ void sync_weights(VW::workspace& all) all.sd->contraction = 1.; } -VW_WARNING_STATE_PUSH -VW_WARNING_DISABLE_UNUSED_FUNCTION -inline float quake_inv_sqrt(float x) -{ - // Carmack/Quake/SGI fast method: - float xhalf = 0.5f * x; - static_assert(sizeof(int) == sizeof(float), "Floats and ints are converted between, they must be the same size."); - int i = reinterpret_cast(x); // store floating-point bits in integer - i = 0x5f3759d5 - (i >> 1); // initial guess for Newton's method - x = reinterpret_cast(i); // convert new bits into float - x = x * (1.5f - xhalf * x * x); // One round of Newton's method - return x; -} -VW_WARNING_STATE_POP - -static inline float inv_sqrt(float x) -{ -#if !defined(VW_NO_INLINE_SIMD) -# if defined(__ARM_NEON__) - // Propagate into vector - float32x2_t v1 = vdup_n_f32(x); - // Estimate - float32x2_t e1 = vrsqrte_f32(v1); - // N-R iteration 1 - float32x2_t e2 = vmul_f32(e1, vrsqrts_f32(v1, vmul_f32(e1, e1))); - // N-R iteration 2 - float32x2_t e3 = vmul_f32(e2, vrsqrts_f32(v1, vmul_f32(e2, e2))); - // Extract result - return vget_lane_f32(e3, 0); -# elif defined(__SSE2__) - __m128 eta = _mm_load_ss(&x); - eta = _mm_rsqrt_ss(eta); - _mm_store_ss(&x, eta); -# else - x = quake_inv_sqrt(x); -# endif -#else - x = quake_inv_sqrt(x); -#endif - - return x; -} - VW_WARNING_STATE_PUSH VW_WARNING_DISABLE_COND_CONST_EXPR template @@ -623,7 +580,7 @@ inline float compute_rate_decay(power_data& s, float& fw) float rate_decay = 1.f; if (adaptive) { - if (sqrt_rate) { rate_decay = inv_sqrt(w[adaptive]); } + if (sqrt_rate) { rate_decay = 1.0f / std::sqrt(w[adaptive]); } else { rate_decay = powf(w[adaptive], s.minus_power_t); } } if VW_STD17_CONSTEXPR (normalized != 0)