vasilito
cb424d7448
verify-patch-sanity.py validates every active recipe .patch has internally- consistent hunk line counts — catching the 'malformed patch at line N' failure at commit/CI/preflight time instead of hours into a cook. This cycle hit that class three times (qtwaylandscanner, sddm, xwayland), each only discovered when cookbook tried to apply the patch. Running it across the repo found 29 latent malformed patches (validated against GNU patch: e.g. relibc/P3-sysv-ipc reproduces 'malformed patch at line 22'). They were harmless only because they sit in vendored recipes (baked, not re- applied) — but would fail on any version-bump re-derivation. --fix recounts the hunk headers (body untouched) and repaired all 29. Wired into build-preflight.sh (Phase 1.0D) and redbear-ci.yml, with a unit test (test-patch-sanity.sh). Skips archived/legacy trees and unvalidatable formats (empty placeholders, bare-@@ git hunks).
116 lines
3.8 KiB
C++
116 lines
3.8 KiB
C++
// -*- C++ -*-
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//===----------------------------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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export namespace std {
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// [rand.req.urng], uniform random bit generator requirements
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using std::uniform_random_bit_generator;
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// [rand.eng.lcong], class template linear_congruential_engine
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using std::linear_congruential_engine;
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// [rand.eng.mers], class template mersenne_twister_engine
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using std::mersenne_twister_engine;
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// [rand.eng.sub], class template subtract_with_carry_engine
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using std::subtract_with_carry_engine;
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// [rand.adapt.disc], class template discard_block_engine
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using std::discard_block_engine;
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// [rand.adapt.ibits], class template independent_bits_engine
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using std::independent_bits_engine;
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// [rand.adapt.shuf], class template shuffle_order_engine
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using std::shuffle_order_engine;
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// [rand.predef], engines and engine adaptors with predefined parameters
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using std::knuth_b;
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using std::minstd_rand;
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using std::minstd_rand0;
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using std::mt19937;
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using std::mt19937_64;
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using std::ranlux24;
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using std::ranlux24_base;
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using std::ranlux48;
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using std::ranlux48_base;
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using std::default_random_engine;
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#if _LIBCPP_HAS_RANDOM_DEVICE
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// [rand.device], class random_device
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using std::random_device;
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#endif
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// [rand.util.seedseq], class seed_seq
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using std::seed_seq;
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// [rand.util.canonical], function template generate_canonical
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using std::generate_canonical;
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// [rand.dist.uni.int], class template uniform_int_distribution
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using std::uniform_int_distribution;
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// [rand.dist.uni.real], class template uniform_real_distribution
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using std::uniform_real_distribution;
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// [rand.dist.bern.bernoulli], class bernoulli_distribution
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using std::bernoulli_distribution;
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// [rand.dist.bern.bin], class template binomial_distribution
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using std::binomial_distribution;
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// [rand.dist.bern.geo], class template geometric_distribution
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using std::geometric_distribution;
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// [rand.dist.bern.negbin], class template negative_binomial_distribution
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using std::negative_binomial_distribution;
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// [rand.dist.pois.poisson], class template poisson_distribution
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using std::poisson_distribution;
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// [rand.dist.pois.exp], class template exponential_distribution
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using std::exponential_distribution;
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// [rand.dist.pois.gamma], class template gamma_distribution
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using std::gamma_distribution;
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// [rand.dist.pois.weibull], class template weibull_distribution
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using std::weibull_distribution;
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// [rand.dist.pois.extreme], class template extreme_value_distribution
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using std::extreme_value_distribution;
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// [rand.dist.norm.normal], class template normal_distribution
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using std::normal_distribution;
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// [rand.dist.norm.lognormal], class template lognormal_distribution
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using std::lognormal_distribution;
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// [rand.dist.norm.chisq], class template chi_squared_distribution
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using std::chi_squared_distribution;
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// [rand.dist.norm.cauchy], class template cauchy_distribution
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using std::cauchy_distribution;
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// [rand.dist.norm.f], class template fisher_f_distribution
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using std::fisher_f_distribution;
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// [rand.dist.norm.t], class template student_t_distribution
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using std::student_t_distribution;
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// [rand.dist.samp.discrete], class template discrete_distribution
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using std::discrete_distribution;
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// [rand.dist.samp.pconst], class template piecewise_constant_distribution
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using std::piecewise_constant_distribution;
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// [rand.dist.samp.plinear], class template piecewise_linear_distribution
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using std::piecewise_linear_distribution;
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} // namespace std
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