blob: 8aacf20e3c5a4abee586d9cbbbc5052d32b8d099 [file]
//===----------------------------------------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
///
/// \file
/// This file contains unit tests for single-precision SIMD sin.
///
//===----------------------------------------------------------------------===//
#include "hdr/math_macros.h"
#include "src/__support/CPP/simd.h"
#include "src/__support/FPUtil/FPBits.h"
#include "src/math/sinf.h"
#include "src/mathvec/sinf.h"
#include "test/UnitTest/SIMDMatcher.h"
#include "test/UnitTest/Test.h"
#include "test/src/math/sdcomp26094.h"
#include "test/src/mathvec/UnitTestWrappers.h"
#include "hdr/stdint_proxy.h"
using LlvmLibcVecSinfTest = LIBC_NAMESPACE::testing::FPTest<float>;
using SinfOp =
LIBC_NAMESPACE::testing::mathvec::UnaryOp<float, LIBC_NAMESPACE::sinf,
LIBC_NAMESPACE::sinf>;
using LIBC_NAMESPACE::cpp::splat;
using LIBC_NAMESPACE::testing::SDCOMP26094_VALUES;
using LIBC_NAMESPACE::testing::mathvec::wrap_ref;
using LIBC_NAMESPACE::testing::mathvec::wrap_vector;
TEST_F(LlvmLibcVecSinfTest, SpecialNumbers) {
EXPECT_SIMD_EQ(splat(aNaN), wrap_vector<SinfOp>(aNaN));
EXPECT_SIMD_EQ(splat(aNaN), wrap_vector<SinfOp>(inf));
EXPECT_SIMD_EQ(splat(aNaN), wrap_vector<SinfOp>(neg_inf));
EXPECT_SIMD_EQ(splat(0.0f), wrap_vector<SinfOp>(0.0f));
}
// SDCOMP-26094: check sinf in the cases for which the range reducer
// returns values furthest beyond its nominal upper bound of pi/4.
TEST_F(LlvmLibcVecSinfTest, SDCOMP_26094) {
for (uint32_t v : SDCOMP26094_VALUES) {
float x = FPBits((v)).get_val();
EXPECT_SIMD_EQ(wrap_ref<SinfOp>(x, -x), wrap_vector<SinfOp>(x, -x));
}
}
TEST_F(LlvmLibcVecSinfTest, SpecificBitPatterns) {
constexpr int N = 36;
constexpr uint32_t INPUTS[N] = {
0x3f06'0a92U, // x = pi/6
0x3f3a'dc51U, // x = 0x1.75b8a2p-1f
0x3f49'0fdbU, // x = pi/4
0x3f86'0a92U, // x = pi/3
0x3fa7'832aU, // x = 0x1.4f0654p+0f
0x3fc9'0fdbU, // x = pi/2
0x4017'1973U, // x = 0x1.2e32e6p+1f
0x4049'0fdbU, // x = pi
0x4096'cbe4U, // x = 0x1.2d97c8p+2f
0x40c9'0fdbU, // x = 2*pi
0x433b'7490U, // x = 0x1.76e92p+7f
0x437c'e5f1U, // x = 0x1.f9cbe2p+7f
0x4619'9998U, // x = 0x1.33333p+13f
0x474d'246fU, // x = 0x1.9a48dep+15f
0x4afd'ece4U, // x = 0x1.fbd9c8p+22f
0x4c23'32e9U, // x = 0x1.4665d2p+25f
0x50a3'e87fU, // x = 0x1.47d0fep+34f
0x5239'47f6U, // x = 0x1.728fecp+37f
0x53b1'46a6U, // x = 0x1.628d4cp+40f
0x55ca'fb2aU, // x = 0x1.95f654p+44f
0x588e'f060U, // x = 0x1.1de0cp+50f
0x5c07'bcd0U, // x = 0x1.0f79ap+57f
0x5ebc'fddeU, // x = 0x1.79fbbcp+62f
0x5fa6'eba7U, // x = 0x1.4dd74ep+64f
0x61a4'0b40U, // x = 0x1.48168p+68f
0x6386'134eU, // x = 0x1.0c269cp+72f
0x6589'8498U, // x = 0x1.13093p+76f
0x6600'0001U, // x = 0x1.000002p+77f
0x664e'46e4U, // x = 0x1.9c8dc8p+77f
0x66b0'14aaU, // x = 0x1.602954p+78f
0x67a9'242bU, // x = 0x1.524856p+80f
0x6a19'76f1U, // x = 0x1.32ede2p+85f
0x6c55'da58U, // x = 0x1.abb4bp+89f
0x6f79'be45U, // x = 0x1.f37c8ap+95f
0x7276'69d4U, // x = 0x1.ecd3a8p+101f
0x7758'4625U, // x = 0x1.b08c4ap+111f
};
for (int i = 0; i < N; ++i) {
float x = FPBits(INPUTS[i]).get_val();
EXPECT_SIMD_EQ(wrap_ref<SinfOp>(x, -x), wrap_vector<SinfOp>(x, -x));
}
}
TEST_F(LlvmLibcVecSinfTest, InFloatRange) { TEST_MATHVEC_FLOAT_RANGE(SinfOp); }