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Open Source Computer Vision Library
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1040 lines
29 KiB
1040 lines
29 KiB
#include "test_precomp.hpp" |
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#include "test_intrin_utils.hpp" |
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#include <climits> |
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using namespace cv; |
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namespace cvtest { namespace hal { |
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template<typename T> static inline void EXPECT_COMPARE_EQ_(const T a, const T b); |
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template<> inline void EXPECT_COMPARE_EQ_<float>(const float a, const float b) |
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{ |
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EXPECT_FLOAT_EQ( a, b ); |
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} |
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template<> inline void EXPECT_COMPARE_EQ_<double>(const double a, const double b) |
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{ |
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EXPECT_DOUBLE_EQ( a, b ); |
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} |
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template<typename R> struct TheTest |
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{ |
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typedef typename R::lane_type LaneType; |
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template <typename T1, typename T2> |
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static inline void EXPECT_COMPARE_EQ(const T1 a, const T2 b) |
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{ |
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EXPECT_COMPARE_EQ_<LaneType>((LaneType)a, (LaneType)b); |
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} |
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TheTest & test_loadstore() |
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{ |
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AlignedData<R> data; |
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AlignedData<R> out; |
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// check if addresses are aligned and unaligned respectively |
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EXPECT_EQ((size_t)0, (size_t)&data.a.d % 16); |
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EXPECT_NE((size_t)0, (size_t)&data.u.d % 16); |
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EXPECT_EQ((size_t)0, (size_t)&out.a.d % 16); |
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EXPECT_NE((size_t)0, (size_t)&out.u.d % 16); |
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// check some initialization methods |
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R r1 = data.a; |
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R r2 = v_load(data.u.d); |
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R r3 = v_load_aligned(data.a.d); |
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R r4(r2); |
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EXPECT_EQ(data.a[0], r1.get0()); |
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EXPECT_EQ(data.u[0], r2.get0()); |
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EXPECT_EQ(data.a[0], r3.get0()); |
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EXPECT_EQ(data.u[0], r4.get0()); |
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// check some store methods |
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out.u.clear(); |
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out.a.clear(); |
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v_store(out.u.d, r1); |
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v_store_aligned(out.a.d, r2); |
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EXPECT_EQ(data.a, out.a); |
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EXPECT_EQ(data.u, out.u); |
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// check more store methods |
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Data<R> d, res(0); |
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R r5 = d; |
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v_store_high(res.mid(), r5); |
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v_store_low(res.d, r5); |
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EXPECT_EQ(d, res); |
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// check halves load correctness |
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res.clear(); |
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R r6 = v_load_halves(d.d, d.mid()); |
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v_store(res.d, r6); |
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EXPECT_EQ(d, res); |
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// zero, all |
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Data<R> resZ = V_RegTrait128<LaneType>::zero(); |
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Data<R> resV = V_RegTrait128<LaneType>::all(8); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ((LaneType)0, resZ[i]); |
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EXPECT_EQ((LaneType)8, resV[i]); |
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} |
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// reinterpret_as |
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v_uint8x16 vu8 = v_reinterpret_as_u8(r1); out.a.clear(); v_store((uchar*)out.a.d, vu8); EXPECT_EQ(data.a, out.a); |
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v_int8x16 vs8 = v_reinterpret_as_s8(r1); out.a.clear(); v_store((schar*)out.a.d, vs8); EXPECT_EQ(data.a, out.a); |
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v_uint16x8 vu16 = v_reinterpret_as_u16(r1); out.a.clear(); v_store((ushort*)out.a.d, vu16); EXPECT_EQ(data.a, out.a); |
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v_int16x8 vs16 = v_reinterpret_as_s16(r1); out.a.clear(); v_store((short*)out.a.d, vs16); EXPECT_EQ(data.a, out.a); |
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v_uint32x4 vu32 = v_reinterpret_as_u32(r1); out.a.clear(); v_store((unsigned*)out.a.d, vu32); EXPECT_EQ(data.a, out.a); |
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v_int32x4 vs32 = v_reinterpret_as_s32(r1); out.a.clear(); v_store((int*)out.a.d, vs32); EXPECT_EQ(data.a, out.a); |
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v_uint64x2 vu64 = v_reinterpret_as_u64(r1); out.a.clear(); v_store((uint64*)out.a.d, vu64); EXPECT_EQ(data.a, out.a); |
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v_int64x2 vs64 = v_reinterpret_as_s64(r1); out.a.clear(); v_store((int64*)out.a.d, vs64); EXPECT_EQ(data.a, out.a); |
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v_float32x4 vf32 = v_reinterpret_as_f32(r1); out.a.clear(); v_store((float*)out.a.d, vf32); EXPECT_EQ(data.a, out.a); |
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#if CV_SIMD128_64F |
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v_float64x2 vf64 = v_reinterpret_as_f64(r1); out.a.clear(); v_store((double*)out.a.d, vf64); EXPECT_EQ(data.a, out.a); |
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#endif |
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return *this; |
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} |
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TheTest & test_interleave() |
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{ |
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Data<R> data1, data2, data3, data4; |
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data2 += 20; |
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data3 += 40; |
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data4 += 60; |
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R a = data1, b = data2, c = data3; |
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R d = data1, e = data2, f = data3, g = data4; |
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LaneType buf3[R::nlanes * 3]; |
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LaneType buf4[R::nlanes * 4]; |
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v_store_interleave(buf3, a, b, c); |
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v_store_interleave(buf4, d, e, f, g); |
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Data<R> z(0); |
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a = b = c = d = e = f = g = z; |
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v_load_deinterleave(buf3, a, b, c); |
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v_load_deinterleave(buf4, d, e, f, g); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(data1, Data<R>(a)); |
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EXPECT_EQ(data2, Data<R>(b)); |
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EXPECT_EQ(data3, Data<R>(c)); |
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EXPECT_EQ(data1, Data<R>(d)); |
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EXPECT_EQ(data2, Data<R>(e)); |
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EXPECT_EQ(data3, Data<R>(f)); |
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EXPECT_EQ(data4, Data<R>(g)); |
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} |
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return *this; |
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} |
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// float32x4 only |
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TheTest & test_interleave_2channel() |
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{ |
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Data<R> data1, data2; |
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data2 += 20; |
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R a = data1, b = data2; |
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LaneType buf2[R::nlanes * 2]; |
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v_store_interleave(buf2, a, b); |
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Data<R> z(0); |
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a = b = z; |
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v_load_deinterleave(buf2, a, b); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(data1, Data<R>(a)); |
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EXPECT_EQ(data2, Data<R>(b)); |
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} |
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return *this; |
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} |
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// v_expand and v_load_expand |
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TheTest & test_expand() |
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{ |
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typedef typename V_RegTrait128<LaneType>::w_reg Rx2; |
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Data<R> dataA; |
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R a = dataA; |
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Data<Rx2> resB = v_load_expand(dataA.d); |
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Rx2 c, d; |
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v_expand(a, c, d); |
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Data<Rx2> resC = c, resD = d; |
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const int n = Rx2::nlanes; |
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for (int i = 0; i < n; ++i) |
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{ |
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EXPECT_EQ(dataA[i], resB[i]); |
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EXPECT_EQ(dataA[i], resC[i]); |
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EXPECT_EQ(dataA[i + n], resD[i]); |
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} |
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return *this; |
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} |
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TheTest & test_expand_q() |
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{ |
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typedef typename V_RegTrait128<LaneType>::q_reg Rx4; |
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Data<R> data; |
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Data<Rx4> out = v_load_expand_q(data.d); |
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const int n = Rx4::nlanes; |
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for (int i = 0; i < n; ++i) |
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EXPECT_EQ(data[i], out[i]); |
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return *this; |
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} |
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TheTest & test_addsub() |
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{ |
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Data<R> dataA, dataB; |
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dataB.reverse(); |
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R a = dataA, b = dataB; |
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Data<R> resC = a + b, resD = a - b; |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(saturate_cast<LaneType>(dataA[i] + dataB[i]), resC[i]); |
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EXPECT_EQ(saturate_cast<LaneType>(dataA[i] - dataB[i]), resD[i]); |
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} |
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return *this; |
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} |
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TheTest & test_addsub_wrap() |
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{ |
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Data<R> dataA, dataB; |
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dataB.reverse(); |
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R a = dataA, b = dataB; |
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Data<R> resC = v_add_wrap(a, b), |
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resD = v_sub_wrap(a, b); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ((LaneType)(dataA[i] + dataB[i]), resC[i]); |
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EXPECT_EQ((LaneType)(dataA[i] - dataB[i]), resD[i]); |
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} |
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return *this; |
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} |
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TheTest & test_mul() |
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{ |
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Data<R> dataA, dataB; |
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dataB.reverse(); |
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R a = dataA, b = dataB; |
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Data<R> resC = a * b; |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(dataA[i] * dataB[i], resC[i]); |
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} |
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return *this; |
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} |
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TheTest & test_div() |
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{ |
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Data<R> dataA, dataB; |
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dataB.reverse(); |
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R a = dataA, b = dataB; |
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Data<R> resC = a / b; |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(dataA[i] / dataB[i], resC[i]); |
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} |
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return *this; |
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} |
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TheTest & test_mul_expand() |
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{ |
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typedef typename V_RegTrait128<LaneType>::w_reg Rx2; |
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Data<R> dataA, dataB(2); |
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R a = dataA, b = dataB; |
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Rx2 c, d; |
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v_mul_expand(a, b, c, d); |
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Data<Rx2> resC = c, resD = d; |
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const int n = R::nlanes / 2; |
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for (int i = 0; i < n; ++i) |
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{ |
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EXPECT_EQ((typename Rx2::lane_type)dataA[i] * dataB[i], resC[i]); |
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EXPECT_EQ((typename Rx2::lane_type)dataA[i + n] * dataB[i + n], resD[i]); |
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} |
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return *this; |
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} |
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TheTest & test_abs() |
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{ |
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typedef typename V_RegTrait128<LaneType>::u_reg Ru; |
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typedef typename Ru::lane_type u_type; |
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Data<R> dataA, dataB(10); |
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R a = dataA, b = dataB; |
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a = a - b; |
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Data<Ru> resC = v_abs(a); |
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for (int i = 0; i < Ru::nlanes; ++i) |
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{ |
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EXPECT_EQ((u_type)std::abs(dataA[i] - dataB[i]), resC[i]); |
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} |
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return *this; |
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} |
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template <int s> |
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TheTest & test_shift() |
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{ |
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Data<R> dataA; |
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R a = dataA; |
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Data<R> resB = a << s, resC = v_shl<s>(a), resD = a >> s, resE = v_shr<s>(a); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(dataA[i] << s, resB[i]); |
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EXPECT_EQ(dataA[i] << s, resC[i]); |
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EXPECT_EQ(dataA[i] >> s, resD[i]); |
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EXPECT_EQ(dataA[i] >> s, resE[i]); |
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} |
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return *this; |
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} |
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TheTest & test_cmp() |
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{ |
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Data<R> dataA, dataB; |
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dataB.reverse(); |
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dataB += 1; |
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R a = dataA, b = dataB; |
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Data<R> resC = (a == b); |
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Data<R> resD = (a != b); |
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Data<R> resE = (a > b); |
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Data<R> resF = (a >= b); |
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Data<R> resG = (a < b); |
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Data<R> resH = (a <= b); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(dataA[i] == dataB[i], resC[i] != 0); |
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EXPECT_EQ(dataA[i] != dataB[i], resD[i] != 0); |
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EXPECT_EQ(dataA[i] > dataB[i], resE[i] != 0); |
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EXPECT_EQ(dataA[i] >= dataB[i], resF[i] != 0); |
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EXPECT_EQ(dataA[i] < dataB[i], resG[i] != 0); |
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EXPECT_EQ(dataA[i] <= dataB[i], resH[i] != 0); |
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} |
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return *this; |
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} |
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TheTest & test_dot_prod() |
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{ |
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typedef typename V_RegTrait128<LaneType>::w_reg Rx2; |
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Data<R> dataA, dataB(2); |
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R a = dataA, b = dataB; |
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Data<Rx2> res = v_dotprod(a, b); |
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const int n = R::nlanes / 2; |
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for (int i = 0; i < n; ++i) |
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{ |
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EXPECT_EQ(dataA[i*2] * dataB[i*2] + dataA[i*2 + 1] * dataB[i*2 + 1], res[i]); |
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} |
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return *this; |
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} |
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TheTest & test_logic() |
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{ |
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Data<R> dataA, dataB(2); |
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R a = dataA, b = dataB; |
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Data<R> resC = a & b, resD = a | b, resE = a ^ b, resF = ~a; |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(dataA[i] & dataB[i], resC[i]); |
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EXPECT_EQ(dataA[i] | dataB[i], resD[i]); |
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EXPECT_EQ(dataA[i] ^ dataB[i], resE[i]); |
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EXPECT_EQ((LaneType)~dataA[i], resF[i]); |
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} |
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return *this; |
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} |
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TheTest & test_sqrt_abs() |
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{ |
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Data<R> dataA, dataD; |
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dataD *= -1.0; |
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R a = dataA, d = dataD; |
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Data<R> resB = v_sqrt(a), resC = v_invsqrt(a), resE = v_abs(d); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_COMPARE_EQ((float)std::sqrt(dataA[i]), (float)resB[i]); |
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EXPECT_COMPARE_EQ(1/(float)std::sqrt(dataA[i]), (float)resC[i]); |
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EXPECT_COMPARE_EQ((float)abs(dataA[i]), (float)resE[i]); |
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} |
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return *this; |
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} |
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TheTest & test_min_max() |
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{ |
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Data<R> dataA, dataB; |
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dataB.reverse(); |
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R a = dataA, b = dataB; |
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Data<R> resC = v_min(a, b), resD = v_max(a, b); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(std::min(dataA[i], dataB[i]), resC[i]); |
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EXPECT_EQ(std::max(dataA[i], dataB[i]), resD[i]); |
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} |
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return *this; |
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} |
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TheTest & test_popcount() |
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{ |
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static unsigned popcountTable[] = {0, 1, 2, 4, 5, 7, 9, 12, 13, 15, 17, 20, 22, 25, 28, 32, 33}; |
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Data<R> dataA; |
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R a = dataA; |
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unsigned resB = (unsigned)v_reduce_sum(v_popcount(a)); |
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EXPECT_EQ(popcountTable[R::nlanes], resB); |
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return *this; |
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} |
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TheTest & test_absdiff() |
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{ |
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typedef typename V_RegTrait128<LaneType>::u_reg Ru; |
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typedef typename Ru::lane_type u_type; |
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Data<R> dataA(std::numeric_limits<LaneType>::max()), |
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dataB(std::numeric_limits<LaneType>::min()); |
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dataA[0] = (LaneType)-1; |
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dataB[0] = 1; |
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dataA[1] = 2; |
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dataB[1] = (LaneType)-2; |
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R a = dataA, b = dataB; |
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Data<Ru> resC = v_absdiff(a, b); |
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const u_type mask = std::numeric_limits<LaneType>::is_signed ? (u_type)(1 << (sizeof(u_type)*8 - 1)) : 0; |
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for (int i = 0; i < Ru::nlanes; ++i) |
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{ |
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u_type uA = dataA[i] ^ mask; |
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u_type uB = dataB[i] ^ mask; |
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EXPECT_EQ(uA > uB ? uA - uB : uB - uA, resC[i]); |
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} |
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return *this; |
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} |
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TheTest & test_float_absdiff() |
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{ |
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Data<R> dataA(std::numeric_limits<LaneType>::max()), |
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dataB(std::numeric_limits<LaneType>::min()); |
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dataA[0] = -1; |
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dataB[0] = 1; |
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dataA[1] = 2; |
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dataB[1] = -2; |
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R a = dataA, b = dataB; |
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Data<R> resC = v_absdiff(a, b); |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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EXPECT_EQ(dataA[i] > dataB[i] ? dataA[i] - dataB[i] : dataB[i] - dataA[i], resC[i]); |
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} |
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return *this; |
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} |
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TheTest & test_reduce() |
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{ |
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Data<R> dataA; |
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R a = dataA; |
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EXPECT_EQ((LaneType)1, v_reduce_min(a)); |
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EXPECT_EQ((LaneType)R::nlanes, v_reduce_max(a)); |
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EXPECT_EQ((LaneType)((1 + R::nlanes)*R::nlanes/2), v_reduce_sum(a)); |
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return *this; |
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} |
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TheTest & test_mask() |
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{ |
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Data<R> dataA, dataB, dataC, dataD(1), dataE(2); |
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dataA[1] *= (LaneType)-1; |
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dataC *= (LaneType)-1; |
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R a = dataA, b = dataB, c = dataC, d = dataD, e = dataE; |
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int m = v_signmask(a); |
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EXPECT_EQ(2, m); |
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EXPECT_EQ(false, v_check_all(a)); |
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EXPECT_EQ(false, v_check_all(b)); |
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EXPECT_EQ(true, v_check_all(c)); |
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EXPECT_EQ(true, v_check_any(a)); |
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EXPECT_EQ(false, v_check_any(b)); |
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EXPECT_EQ(true, v_check_any(c)); |
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typedef V_TypeTraits<LaneType> Traits; |
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typedef typename Traits::int_type int_type; |
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R f = v_select(b, d, e); |
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Data<R> resF = f; |
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for (int i = 0; i < R::nlanes; ++i) |
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{ |
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int_type m2 = Traits::reinterpret_int(dataB[i]); |
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EXPECT_EQ((Traits::reinterpret_int(dataD[i]) & m2) |
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| (Traits::reinterpret_int(dataE[i]) & ~m2), |
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Traits::reinterpret_int(resF[i])); |
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} |
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return *this; |
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} |
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template <int s> |
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TheTest & test_pack() |
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{ |
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typedef typename V_RegTrait128<LaneType>::w_reg Rx2; |
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typedef typename Rx2::lane_type w_type; |
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Data<Rx2> dataA, dataB; |
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dataA += std::numeric_limits<LaneType>::is_signed ? -10 : 10; |
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dataB *= 10; |
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Rx2 a = dataA, b = dataB; |
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Data<R> resC = v_pack(a, b); |
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Data<R> resD = v_rshr_pack<s>(a, b); |
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|
|
Data<R> resE(0); |
|
v_pack_store(resE.d, b); |
|
|
|
Data<R> resF(0); |
|
v_rshr_pack_store<s>(resF.d, b); |
|
|
|
const int n = Rx2::nlanes; |
|
const w_type add = (w_type)1 << (s - 1); |
|
for (int i = 0; i < n; ++i) |
|
{ |
|
EXPECT_EQ(saturate_cast<LaneType>(dataA[i]), resC[i]); |
|
EXPECT_EQ(saturate_cast<LaneType>(dataB[i]), resC[i + n]); |
|
EXPECT_EQ(saturate_cast<LaneType>((dataA[i] + add) >> s), resD[i]); |
|
EXPECT_EQ(saturate_cast<LaneType>((dataB[i] + add) >> s), resD[i + n]); |
|
EXPECT_EQ(saturate_cast<LaneType>(dataB[i]), resE[i]); |
|
EXPECT_EQ((LaneType)0, resE[i + n]); |
|
EXPECT_EQ(saturate_cast<LaneType>((dataB[i] + add) >> s), resF[i]); |
|
EXPECT_EQ((LaneType)0, resF[i + n]); |
|
} |
|
return *this; |
|
} |
|
|
|
template <int s> |
|
TheTest & test_pack_u() |
|
{ |
|
typedef typename V_TypeTraits<LaneType>::w_type LaneType_w; |
|
typedef typename V_RegTrait128<LaneType_w>::int_reg Ri2; |
|
typedef typename Ri2::lane_type w_type; |
|
|
|
Data<Ri2> dataA, dataB; |
|
dataA += -10; |
|
dataB *= 10; |
|
Ri2 a = dataA, b = dataB; |
|
|
|
Data<R> resC = v_pack_u(a, b); |
|
Data<R> resD = v_rshr_pack_u<s>(a, b); |
|
|
|
Data<R> resE(0); |
|
v_pack_u_store(resE.d, b); |
|
|
|
Data<R> resF(0); |
|
v_rshr_pack_u_store<s>(resF.d, b); |
|
|
|
const int n = Ri2::nlanes; |
|
const w_type add = (w_type)1 << (s - 1); |
|
for (int i = 0; i < n; ++i) |
|
{ |
|
EXPECT_EQ(saturate_cast<LaneType>(dataA[i]), resC[i]); |
|
EXPECT_EQ(saturate_cast<LaneType>(dataB[i]), resC[i + n]); |
|
EXPECT_EQ(saturate_cast<LaneType>((dataA[i] + add) >> s), resD[i]); |
|
EXPECT_EQ(saturate_cast<LaneType>((dataB[i] + add) >> s), resD[i + n]); |
|
EXPECT_EQ(saturate_cast<LaneType>(dataB[i]), resE[i]); |
|
EXPECT_EQ((LaneType)0, resE[i + n]); |
|
EXPECT_EQ(saturate_cast<LaneType>((dataB[i] + add) >> s), resF[i]); |
|
EXPECT_EQ((LaneType)0, resF[i + n]); |
|
} |
|
return *this; |
|
} |
|
|
|
TheTest & test_unpack() |
|
{ |
|
Data<R> dataA, dataB; |
|
dataB *= 10; |
|
R a = dataA, b = dataB; |
|
|
|
R c, d, e, f, lo, hi; |
|
v_zip(a, b, c, d); |
|
v_recombine(a, b, e, f); |
|
lo = v_combine_low(a, b); |
|
hi = v_combine_high(a, b); |
|
|
|
Data<R> resC = c, resD = d, resE = e, resF = f, resLo = lo, resHi = hi; |
|
|
|
const int n = R::nlanes/2; |
|
for (int i = 0; i < n; ++i) |
|
{ |
|
EXPECT_EQ(dataA[i], resC[i*2]); |
|
EXPECT_EQ(dataB[i], resC[i*2+1]); |
|
EXPECT_EQ(dataA[i+n], resD[i*2]); |
|
EXPECT_EQ(dataB[i+n], resD[i*2+1]); |
|
|
|
EXPECT_EQ(dataA[i], resE[i]); |
|
EXPECT_EQ(dataB[i], resE[i+n]); |
|
EXPECT_EQ(dataA[i+n], resF[i]); |
|
EXPECT_EQ(dataB[i+n], resF[i+n]); |
|
|
|
EXPECT_EQ(dataA[i], resLo[i]); |
|
EXPECT_EQ(dataB[i], resLo[i+n]); |
|
EXPECT_EQ(dataA[i+n], resHi[i]); |
|
EXPECT_EQ(dataB[i+n], resHi[i+n]); |
|
} |
|
|
|
return *this; |
|
} |
|
|
|
template<int s> |
|
TheTest & test_extract() |
|
{ |
|
Data<R> dataA, dataB; |
|
dataB *= 10; |
|
R a = dataA, b = dataB; |
|
|
|
Data<R> resC = v_extract<s>(a, b); |
|
|
|
for (int i = 0; i < R::nlanes; ++i) |
|
{ |
|
if (i + s >= R::nlanes) |
|
EXPECT_EQ(dataB[i - R::nlanes + s], resC[i]); |
|
else |
|
EXPECT_EQ(dataA[i + s], resC[i]); |
|
} |
|
|
|
return *this; |
|
} |
|
|
|
TheTest & test_float_math() |
|
{ |
|
typedef typename V_RegTrait128<LaneType>::int_reg Ri; |
|
Data<R> data1, data2, data3; |
|
data1 *= 1.1; |
|
data2 += 10; |
|
R a1 = data1, a2 = data2, a3 = data3; |
|
|
|
Data<Ri> resB = v_round(a1), |
|
resC = v_trunc(a1), |
|
resD = v_floor(a1), |
|
resE = v_ceil(a1); |
|
|
|
Data<R> resF = v_magnitude(a1, a2), |
|
resG = v_sqr_magnitude(a1, a2), |
|
resH = v_muladd(a1, a2, a3); |
|
|
|
for (int i = 0; i < R::nlanes; ++i) |
|
{ |
|
EXPECT_EQ(cvRound(data1[i]), resB[i]); |
|
EXPECT_EQ((typename Ri::lane_type)data1[i], resC[i]); |
|
EXPECT_EQ(cvFloor(data1[i]), resD[i]); |
|
EXPECT_EQ(cvCeil(data1[i]), resE[i]); |
|
|
|
EXPECT_COMPARE_EQ(std::sqrt(data1[i]*data1[i] + data2[i]*data2[i]), resF[i]); |
|
EXPECT_COMPARE_EQ(data1[i]*data1[i] + data2[i]*data2[i], resG[i]); |
|
EXPECT_COMPARE_EQ(data1[i]*data2[i] + data3[i], resH[i]); |
|
} |
|
|
|
return *this; |
|
} |
|
|
|
TheTest & test_float_cvt32() |
|
{ |
|
typedef v_float32x4 Rt; |
|
Data<R> dataA; |
|
dataA *= 1.1; |
|
R a = dataA; |
|
Rt b = v_cvt_f32(a); |
|
Data<Rt> resB = b; |
|
int n = std::min<int>(Rt::nlanes, R::nlanes); |
|
for (int i = 0; i < n; ++i) |
|
{ |
|
EXPECT_EQ((typename Rt::lane_type)dataA[i], resB[i]); |
|
} |
|
return *this; |
|
} |
|
|
|
TheTest & test_float_cvt64() |
|
{ |
|
#if CV_SIMD128_64F |
|
typedef v_float64x2 Rt; |
|
Data<R> dataA; |
|
dataA *= 1.1; |
|
R a = dataA; |
|
Rt b = v_cvt_f64(a); |
|
Rt c = v_cvt_f64_high(a); |
|
Data<Rt> resB = b; |
|
Data<Rt> resC = c; |
|
int n = std::min<int>(Rt::nlanes, R::nlanes); |
|
for (int i = 0; i < n; ++i) |
|
{ |
|
EXPECT_EQ((typename Rt::lane_type)dataA[i], resB[i]); |
|
} |
|
for (int i = 0; i < n; ++i) |
|
{ |
|
EXPECT_EQ((typename Rt::lane_type)dataA[i+n], resC[i]); |
|
} |
|
#endif |
|
return *this; |
|
} |
|
|
|
TheTest & test_matmul() |
|
{ |
|
Data<R> dataV, dataA, dataB, dataC, dataD; |
|
dataB.reverse(); |
|
dataC += 2; |
|
dataD *= 0.3; |
|
R v = dataV, a = dataA, b = dataB, c = dataC, d = dataD; |
|
|
|
Data<R> res = v_matmul(v, a, b, c, d); |
|
for (int i = 0; i < R::nlanes; ++i) |
|
{ |
|
LaneType val = dataV[0] * dataA[i] |
|
+ dataV[1] * dataB[i] |
|
+ dataV[2] * dataC[i] |
|
+ dataV[3] * dataD[i]; |
|
EXPECT_DOUBLE_EQ(val, res[i]); |
|
} |
|
return *this; |
|
} |
|
|
|
TheTest & test_transpose() |
|
{ |
|
Data<R> dataA, dataB, dataC, dataD; |
|
dataB *= 5; |
|
dataC *= 10; |
|
dataD *= 15; |
|
R a = dataA, b = dataB, c = dataC, d = dataD; |
|
R e, f, g, h; |
|
v_transpose4x4(a, b, c, d, |
|
e, f, g, h); |
|
|
|
Data<R> res[4] = {e, f, g, h}; |
|
for (int i = 0; i < R::nlanes; ++i) |
|
{ |
|
EXPECT_EQ(dataA[i], res[i][0]); |
|
EXPECT_EQ(dataB[i], res[i][1]); |
|
EXPECT_EQ(dataC[i], res[i][2]); |
|
EXPECT_EQ(dataD[i], res[i][3]); |
|
} |
|
return *this; |
|
} |
|
|
|
TheTest & test_reduce_sum4() |
|
{ |
|
R a(0.1f, 0.02f, 0.003f, 0.0004f); |
|
R b(1, 20, 300, 4000); |
|
R c(10, 2, 0.3f, 0.04f); |
|
R d(1, 2, 3, 4); |
|
|
|
R sum = v_reduce_sum4(a, b, c, d); |
|
|
|
Data<R> res = sum; |
|
EXPECT_EQ(0.1234f, res[0]); |
|
EXPECT_EQ(4321.0f, res[1]); |
|
EXPECT_EQ(12.34f, res[2]); |
|
EXPECT_EQ(10.0f, res[3]); |
|
return *this; |
|
} |
|
|
|
TheTest & test_loadstore_fp16() |
|
{ |
|
#if CV_FP16 && CV_SIMD128 |
|
AlignedData<R> data; |
|
AlignedData<R> out; |
|
|
|
if(checkHardwareSupport(CV_CPU_FP16)) |
|
{ |
|
// check if addresses are aligned and unaligned respectively |
|
EXPECT_EQ((size_t)0, (size_t)&data.a.d % 16); |
|
EXPECT_NE((size_t)0, (size_t)&data.u.d % 16); |
|
EXPECT_EQ((size_t)0, (size_t)&out.a.d % 16); |
|
EXPECT_NE((size_t)0, (size_t)&out.u.d % 16); |
|
|
|
// check some initialization methods |
|
R r1 = data.u; |
|
R r2 = v_load_f16(data.a.d); |
|
R r3(r2); |
|
EXPECT_EQ(data.u[0], r1.get0()); |
|
EXPECT_EQ(data.a[0], r2.get0()); |
|
EXPECT_EQ(data.a[0], r3.get0()); |
|
|
|
// check some store methods |
|
out.a.clear(); |
|
v_store_f16(out.a.d, r1); |
|
EXPECT_EQ(data.a, out.a); |
|
} |
|
|
|
return *this; |
|
#endif |
|
} |
|
|
|
TheTest & test_float_cvt_fp16() |
|
{ |
|
#if CV_FP16 && CV_SIMD128 |
|
AlignedData<v_float32x4> data; |
|
|
|
if(checkHardwareSupport(CV_CPU_FP16)) |
|
{ |
|
// check conversion |
|
v_float32x4 r1 = v_load(data.a.d); |
|
v_float16x4 r2 = v_cvt_f16(r1); |
|
v_float32x4 r3 = v_cvt_f32(r2); |
|
EXPECT_EQ(0x3c00, r2.get0()); |
|
EXPECT_EQ(r3.get0(), r1.get0()); |
|
} |
|
|
|
return *this; |
|
#endif |
|
} |
|
|
|
}; |
|
|
|
|
|
//============= 8-bit integer ===================================================================== |
|
|
|
TEST(hal_intrin, uint8x16) { |
|
TheTest<v_uint8x16>() |
|
.test_loadstore() |
|
.test_interleave() |
|
.test_expand() |
|
.test_expand_q() |
|
.test_addsub() |
|
.test_addsub_wrap() |
|
.test_cmp() |
|
.test_logic() |
|
.test_min_max() |
|
.test_absdiff() |
|
.test_mask() |
|
.test_popcount() |
|
.test_pack<1>().test_pack<2>().test_pack<3>().test_pack<8>() |
|
.test_pack_u<1>().test_pack_u<2>().test_pack_u<3>().test_pack_u<8>() |
|
.test_unpack() |
|
.test_extract<0>().test_extract<1>().test_extract<8>().test_extract<15>() |
|
; |
|
} |
|
|
|
TEST(hal_intrin, int8x16) { |
|
TheTest<v_int8x16>() |
|
.test_loadstore() |
|
.test_interleave() |
|
.test_expand() |
|
.test_expand_q() |
|
.test_addsub() |
|
.test_addsub_wrap() |
|
.test_cmp() |
|
.test_logic() |
|
.test_min_max() |
|
.test_absdiff() |
|
.test_abs() |
|
.test_mask() |
|
.test_popcount() |
|
.test_pack<1>().test_pack<2>().test_pack<3>().test_pack<8>() |
|
.test_unpack() |
|
.test_extract<0>().test_extract<1>().test_extract<8>().test_extract<15>() |
|
; |
|
} |
|
|
|
//============= 16-bit integer ===================================================================== |
|
|
|
TEST(hal_intrin, uint16x8) { |
|
TheTest<v_uint16x8>() |
|
.test_loadstore() |
|
.test_interleave() |
|
.test_expand() |
|
.test_addsub() |
|
.test_addsub_wrap() |
|
.test_mul() |
|
.test_mul_expand() |
|
.test_cmp() |
|
.test_shift<1>() |
|
.test_shift<8>() |
|
.test_logic() |
|
.test_min_max() |
|
.test_absdiff() |
|
.test_reduce() |
|
.test_mask() |
|
.test_popcount() |
|
.test_pack<1>().test_pack<2>().test_pack<7>().test_pack<16>() |
|
.test_pack_u<1>().test_pack_u<2>().test_pack_u<7>().test_pack_u<16>() |
|
.test_unpack() |
|
.test_extract<0>().test_extract<1>().test_extract<4>().test_extract<7>() |
|
; |
|
} |
|
|
|
TEST(hal_intrin, int16x8) { |
|
TheTest<v_int16x8>() |
|
.test_loadstore() |
|
.test_interleave() |
|
.test_expand() |
|
.test_addsub() |
|
.test_addsub_wrap() |
|
.test_mul() |
|
.test_mul_expand() |
|
.test_cmp() |
|
.test_shift<1>() |
|
.test_shift<8>() |
|
.test_dot_prod() |
|
.test_logic() |
|
.test_min_max() |
|
.test_absdiff() |
|
.test_abs() |
|
.test_reduce() |
|
.test_mask() |
|
.test_popcount() |
|
.test_pack<1>().test_pack<2>().test_pack<7>().test_pack<16>() |
|
.test_unpack() |
|
.test_extract<0>().test_extract<1>().test_extract<4>().test_extract<7>() |
|
; |
|
} |
|
|
|
//============= 32-bit integer ===================================================================== |
|
|
|
TEST(hal_intrin, uint32x4) { |
|
TheTest<v_uint32x4>() |
|
.test_loadstore() |
|
.test_interleave() |
|
.test_expand() |
|
.test_addsub() |
|
.test_mul() |
|
.test_mul_expand() |
|
.test_cmp() |
|
.test_shift<1>() |
|
.test_shift<8>() |
|
.test_logic() |
|
.test_min_max() |
|
.test_absdiff() |
|
.test_reduce() |
|
.test_mask() |
|
.test_popcount() |
|
.test_pack<1>().test_pack<2>().test_pack<15>().test_pack<32>() |
|
.test_unpack() |
|
.test_extract<0>().test_extract<1>().test_extract<2>().test_extract<3>() |
|
.test_transpose() |
|
; |
|
} |
|
|
|
TEST(hal_intrin, int32x4) { |
|
TheTest<v_int32x4>() |
|
.test_loadstore() |
|
.test_interleave() |
|
.test_expand() |
|
.test_addsub() |
|
.test_mul() |
|
.test_abs() |
|
.test_cmp() |
|
.test_popcount() |
|
.test_shift<1>().test_shift<8>() |
|
.test_logic() |
|
.test_min_max() |
|
.test_absdiff() |
|
.test_reduce() |
|
.test_mask() |
|
.test_pack<1>().test_pack<2>().test_pack<15>().test_pack<32>() |
|
.test_unpack() |
|
.test_extract<0>().test_extract<1>().test_extract<2>().test_extract<3>() |
|
.test_float_cvt32() |
|
.test_float_cvt64() |
|
.test_transpose() |
|
; |
|
} |
|
|
|
//============= 64-bit integer ===================================================================== |
|
|
|
TEST(hal_intrin, uint64x2) { |
|
TheTest<v_uint64x2>() |
|
.test_loadstore() |
|
.test_addsub() |
|
.test_shift<1>().test_shift<8>() |
|
.test_logic() |
|
.test_extract<0>().test_extract<1>() |
|
; |
|
} |
|
|
|
TEST(hal_intrin, int64x2) { |
|
TheTest<v_int64x2>() |
|
.test_loadstore() |
|
.test_addsub() |
|
.test_shift<1>().test_shift<8>() |
|
.test_logic() |
|
.test_extract<0>().test_extract<1>() |
|
; |
|
} |
|
|
|
//============= Floating point ===================================================================== |
|
|
|
TEST(hal_intrin, float32x4) { |
|
TheTest<v_float32x4>() |
|
.test_loadstore() |
|
.test_interleave() |
|
.test_interleave_2channel() |
|
.test_addsub() |
|
.test_mul() |
|
.test_div() |
|
.test_cmp() |
|
.test_sqrt_abs() |
|
.test_min_max() |
|
.test_float_absdiff() |
|
.test_reduce() |
|
.test_mask() |
|
.test_unpack() |
|
.test_float_math() |
|
.test_float_cvt64() |
|
.test_matmul() |
|
.test_transpose() |
|
.test_reduce_sum4() |
|
; |
|
} |
|
|
|
#if CV_SIMD128_64F |
|
TEST(hal_intrin, float64x2) { |
|
TheTest<v_float64x2>() |
|
.test_loadstore() |
|
.test_addsub() |
|
.test_mul() |
|
.test_div() |
|
.test_cmp() |
|
.test_sqrt_abs() |
|
.test_min_max() |
|
.test_float_absdiff() |
|
.test_mask() |
|
.test_unpack() |
|
.test_float_math() |
|
.test_float_cvt32() |
|
; |
|
} |
|
#endif |
|
|
|
#if CV_FP16 && CV_SIMD128 |
|
TEST(hal_intrin, float16x4) { |
|
TheTest<v_float16x4>() |
|
.test_loadstore_fp16() |
|
.test_float_cvt_fp16() |
|
; |
|
} |
|
#endif |
|
|
|
}; |
|
|
|
};
|
|
|