8e1aee62d0
## Motivation Resolved: SWDEV-566226 The current implementation of agents inside of rocprof-systems keeps just the minimal necessary set of information required for populating the `info_agent` table inside of rocpd database. There is a sufficient amount of data that is being left out from database, so this change should fix that and store the additional agent information as an `extdata` row inside of `info_agent` table. ## Technical Details This PR introduces additional filed inside of `agent` structure inside which is representing the JSON formatted string of all the additional information we can acquire about particular agent. This data is processed and added during the initial fetching of agents, and afterwards pushed inside of the database. --------- Co-authored-by: David Galiffi <David.Galiffi@amd.com> * SWDEV-557412 - Incorporate proper chunk offset when remapping virtual memory (#1848) * SWDEV-557412 - Incorporate proper offset when remapping virtual memory * Fix condition to check if VMHeap allocation address matches a chunk address * Move offset calculation outside if/else block --------- Co-authored-by: JeniferC99 <150404595+JeniferC99@users.noreply.github.com> * SWDEV-567852 - Clean-up hip::init() (#1948) * SWDEV-559267 - Use CLPrint to DevLogPrintf with Log Level - detail debug. (#1160) * SWDEV-548892 - Stop using ocml isinf wrapper (#1854) * SWDEV-562708 - change default maximum SVM size to 256GB (#1731) * SWDEV-503089 - Fix and enable disabled HIP tests from math group (#1319) * SWDEV-503089 - Fix and enable disabled HIP tests from math group * SWDEV-503089 - Move single precision reduced run to a common function * SWDEV-548892 - Stop using ockl steadyctr function (#1882) Directly use the builtin * Implement PTL support (#1957) * Implement PTL support Signed-off-by: adapryor <Adam.pryor@amd.com> (cherry picked from commit 45bc31292e7940a3b8fca044ef7df22047b95733) Signed-off-by: Maisam Arif <Maisam.Arif@amd.com> --------- Signed-off-by: adapryor <Adam.pryor@amd.com> Signed-off-by: Maisam Arif <Maisam.Arif@amd.com> Co-authored-by: Maisam Arif <Maisam.Arif@amd.com> * SWDEV-558080 - Add recommended granularity (#1176) * Add recommended granularity * Improve granularity testing * Update based on feedback * Fix and enable VMM tests on cuda (#1855) * Fix and enable VMM tests on cuda * Minor syntax fixes --------- Co-authored-by: Rahul Manocha <rmanocha@amd.com> * [rocprofiler-systems] Add support for ompt_callback_thread_begin (#1681) * Add thread_begin callback * Make OMPT callbacks that are instant have start_ts = end_ts * SWDEV-567514: Remove default stream wait (#1977) - when virtual map command is called - can create deadlock Signed-off-by: sdashmiz <shadi.dashmiz@amd.com> * Fix flaky test Unit_hipStreamAddCallback_StrmSyncTiming (#2022) * Review comments * skip the 3 failing tests to merge hip-tests rocm-systems PR --------- Signed-off-by: Bindhiya Kanangot Balakrishnan <Bindhiya.KanangotBalakrishnan@amd.com> Signed-off-by: adapryor <Adam.pryor@amd.com> Signed-off-by: Maisam Arif <Maisam.Arif@amd.com> Signed-off-by: sdashmiz <shadi.dashmiz@amd.com> Co-authored-by: GunaShekar <agunashe@amd.com> Co-authored-by: agunashe <ajay.gunashekar@amd.com> Co-authored-by: Ethan Trinh <Ethan.Trinh@amd.com> Co-authored-by: JeniferC99 <150404595+JeniferC99@users.noreply.github.com> Co-authored-by: Victor Zhang <111778801+victzhan@users.noreply.github.com> Co-authored-by: German Andryeyev <56892148+gandryey@users.noreply.github.com> Co-authored-by: usrihari123 <srihari.u@amd.com> Co-authored-by: Bindhiya Kanangot Balakrishnan <Bindhiya.KanangotBalakrishnan@amd.com> Co-authored-by: anujshuk-amd <anujshuk@amd.com> Co-authored-by: itrowbri <Ian.Trowbridge@amd.com> Co-authored-by: marantic-amd <marantic@amd.com> Co-authored-by: David Galiffi <David.Galiffi@amd.com> Co-authored-by: cadolphe-amd <chris.adolphe@amd.com> Co-authored-by: Karthik Jayaprakash <54370791+kjayapra-amd@users.noreply.github.com> Co-authored-by: Matt Arsenault <Matthew.Arsenault@amd.com> Co-authored-by: Todd tiantuo Li <88386084+lttamd@users.noreply.github.com> Co-authored-by: amilanov-amd <Aleksandar.Milanov@amd.com> Co-authored-by: Adam Pryor <61172547+adam360x@users.noreply.github.com> Co-authored-by: Maisam Arif <Maisam.Arif@amd.com> Co-authored-by: AidanBeltonS <abeltons@amd.com> Co-authored-by: Rahul Manocha <153310294+manocharahul@users.noreply.github.com> Co-authored-by: Rahul Manocha <rmanocha@amd.com> Co-authored-by: Kian Cossettini <Kian.Cossettini@amd.com> Co-authored-by: Shadi Dashmiz <94885391+shadidashmiz@users.noreply.github.com> Co-authored-by: Ioannis Assiouras <38722728+iassiour@users.noreply.github.com> Co-authored-by: Ajay GunaShekar <86270081+agunashe@users.noreply.github.com>
469 خطوط
15 KiB
C++
469 خطوط
15 KiB
C++
/*
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Copyright (c) 2023 Advanced Micro Devices, Inc. All rights reserved.
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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*/
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#include <hip/hip_fp16.h>
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#include <algorithm>
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#include <cmath>
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#include <hip_test_common.hh>
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#include <limits>
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__global__ void fp16_arith_gpu(float* a, float* b, float* c) {
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c[0] = __half2float(__hadd(__float2half_rn(a[0]), __float2half_rn(b[0])));
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c[1] = __half2float(__hsub(__float2half_rn(a[1]), __float2half_rn(b[1])));
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c[2] = __half2float(__hmul(__float2half_rn(a[2]), __float2half_rn(b[2])));
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c[3] = __half2float(__hdiv(__float2half_rn(a[3]), __float2half_rn(b[3])));
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c[4] = __half2float(hfloor(__float2half_rn(a[4])));
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c[5] = __half2float(htrunc(__float2half_rn(a[5])));
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c[6] = __half2float(hceil(__float2half_rn(a[6])));
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c[7] = __half2float(hrint(__float2half_rn(a[7])));
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c[8] = __half2float(hsin(__float2half_rn(a[8])));
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c[9] = __half2float(hcos(__float2half_rn(a[9])));
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c[10] = __half2float(hexp(__float2half_rn(a[10])));
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c[11] = __half2float(hexp2(__float2half_rn(a[11])));
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c[12] = __half2float(hlog2(__float2half_rn(a[12])));
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c[13] = __half2float(hlog(__float2half_rn(a[13])));
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c[14] = __half2float(hlog10(__float2half_rn(a[14])));
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c[15] = __half2float(hsqrt(__float2half_rn(a[15])));
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c[16] = __half2float(__hneg(__float2half_rn(a[16])));
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c[17] = __half2float(hrcp(__float2half_rn(a[17])));
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}
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void fp16_arith_cpu(const std::vector<float>& a, const std::vector<float>& b,
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std::vector<float>& c) {
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c[0] = a[0] + b[0];
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c[1] = a[0] - b[0];
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c[2] = a[0] * b[0];
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c[3] = a[0] / b[0];
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c[4] = std::floorf(a[4]);
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c[5] = std::truncf(a[5]);
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c[6] = std::ceilf(a[6]);
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c[7] = std::rintf(a[7]);
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c[8] = std::sinf(a[8]);
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c[9] = std::cosf(a[9]);
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c[10] = std::expf(a[10]);
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c[11] = std::exp2f(a[11]);
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c[12] = std::log2f(a[12]);
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c[13] = std::logf(a[13]);
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c[14] = std::log10f(a[14]);
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c[15] = std::sqrtf(a[15]);
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c[16] = -a[16];
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c[17] = 1.0f / a[17];
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}
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TEST_CASE("Unit_fp16_arith") {
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constexpr size_t num_of_ops = 18;
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constexpr size_t iters = 100;
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Catch::Generators::RandomFloatingGenerator<float> input1_gen(2.2f, 10.f, /*seed*/ 0x1234);
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constexpr float input2 = 1.1f;
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for (size_t iter = 0; iter < iters; iter++) {
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auto input1 = input1_gen.get();
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std::vector<float> in1(num_of_ops, input1);
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std::vector<float> in2(num_of_ops, input2);
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float *din1, *din2, *dout;
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HIP_CHECK(hipMalloc(&dout, sizeof(float) * num_of_ops));
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HIP_CHECK(hipMalloc(&din1, sizeof(float) * num_of_ops));
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HIP_CHECK(hipMalloc(&din2, sizeof(float) * num_of_ops));
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HIP_CHECK(hipMemcpy(din1, in1.data(), sizeof(float) * in1.size(), hipMemcpyHostToDevice));
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HIP_CHECK(hipMemcpy(din2, in2.data(), sizeof(float) * in2.size(), hipMemcpyHostToDevice));
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fp16_arith_gpu<<<1, 1>>>(din1, din2, dout);
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std::vector<float> cpuout(num_of_ops, 0.0f);
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fp16_arith_cpu(in1, in2, cpuout);
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std::vector<float> out(num_of_ops, 0.0f);
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HIP_CHECK(hipMemcpy(out.data(), dout, sizeof(float) * out.size(), hipMemcpyDeviceToHost));
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for (size_t i = 0; i < out.size(); i++) {
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INFO("Iter: " << i << " In1: " << in1[i] << " CPU res: " << cpuout[i]
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<< " GPU res: " << out[i]);
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REQUIRE(out[i] == Catch::Approx(cpuout[i]).epsilon(0.1));
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}
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HIP_CHECK(hipFree(dout));
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HIP_CHECK(hipFree(din1));
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HIP_CHECK(hipFree(din2));
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}
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}
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__device__ void fp162_arith_impl(float2* a, float2* b, float2* c) {
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c[0] = __half22float2(__hadd2(__float22half2_rn(a[0]), __float22half2_rn(b[0])));
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c[1] = __half22float2(__hsub2(__float22half2_rn(a[1]), __float22half2_rn(b[1])));
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c[2] = __half22float2(__hmul2(__float22half2_rn(a[2]), __float22half2_rn(b[2])));
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c[3] = __half22float2(__h2div(__float22half2_rn(a[3]), __float22half2_rn(b[3])));
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c[4] = __half22float2(h2floor(__float22half2_rn(a[4])));
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c[5] = __half22float2(h2trunc(__float22half2_rn(a[5])));
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c[6] = __half22float2(h2ceil(__float22half2_rn(a[6])));
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c[7] = __half22float2(h2rint(__float22half2_rn(a[7])));
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c[8] = __half22float2(h2sin(__float22half2_rn(a[8])));
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c[9] = __half22float2(h2cos(__float22half2_rn(a[9])));
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c[10] = __half22float2(h2exp(__float22half2_rn(a[10])));
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c[11] = __half22float2(h2exp2(__float22half2_rn(a[11])));
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c[12] = __half22float2(h2log2(__float22half2_rn(a[12])));
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c[13] = __half22float2(h2log(__float22half2_rn(a[13])));
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c[14] = __half22float2(h2log10(__float22half2_rn(a[14])));
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c[15] = __half22float2(h2sqrt(__float22half2_rn(a[15])));
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c[16] = __half22float2(__hneg2(__float22half2_rn(a[16])));
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c[17] = __half22float2(h2rcp(__float22half2_rn(a[17])));
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}
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__global__ void fp162_arith_gpu(float2* a, float2* b, float2* c) { fp162_arith_impl(a, b, c); }
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void fp162_arith_cpu(std::vector<float2>& a, std::vector<float2>& b, std::vector<float2>& c) {
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c[0] = a[0] + b[0];
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c[1] = a[1] - b[1];
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c[2] = a[2] * b[2];
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c[3] = a[3] / b[3];
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c[4] = {std::floorf(a[4].x), std::floorf(a[4].y)};
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c[5] = {std::truncf(a[5].x), std::truncf(a[5].y)};
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c[6] = {std::ceilf(a[6].x), std::ceilf(a[6].y)};
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c[7] = {std::rintf(a[7].x), std::rintf(a[7].y)};
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c[8] = {std::sinf(a[8].x), std::sinf(a[8].y)};
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c[9] = {std::cosf(a[9].x), std::cosf(a[9].y)};
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c[10] = {std::expf(a[10].x), std::expf(a[10].y)};
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c[11] = {std::exp2f(a[11].x), std::exp2f(a[11].y)};
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c[12] = {std::log2f(a[12].x), std::log2f(a[12].y)};
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c[13] = {std::logf(a[13].x), std::logf(a[13].y)};
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c[14] = {std::log10f(a[14].x), std::log10f(a[14].y)};
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c[15] = {std::sqrtf(a[15].x), std::sqrtf(a[15].y)};
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c[16] = {-a[16].x, -a[16].y};
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c[17] = {1.0f / a[17].x, 1.0f / a[17].y};
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}
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TEST_CASE("Unit_fp162_arith") {
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constexpr size_t num_of_ops = 18;
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constexpr size_t iters = 100;
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Catch::Generators::RandomFloatingGenerator<float> input1_gen(2.2f, 10.f, /* seed */ 0x1234);
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for (size_t iter = 0; iter < iters; iter++) {
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auto input1 = input1_gen.get();
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auto input2 = input1_gen.get();
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std::vector<float2> in1(num_of_ops, float2{input1, input2});
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std::vector<float2> in2(num_of_ops, float2{input1_gen.get(), input1_gen.get()});
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float2 *din1, *din2, *dout;
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HIP_CHECK(hipMalloc(&dout, sizeof(float2) * num_of_ops));
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HIP_CHECK(hipMalloc(&din1, sizeof(float2) * num_of_ops));
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HIP_CHECK(hipMalloc(&din2, sizeof(float2) * num_of_ops));
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HIP_CHECK(hipMemcpy(din1, in1.data(), sizeof(float2) * in1.size(), hipMemcpyHostToDevice));
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HIP_CHECK(hipMemcpy(din2, in2.data(), sizeof(float2) * in2.size(), hipMemcpyHostToDevice));
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fp162_arith_gpu<<<1, 1>>>(din1, din2, dout);
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std::vector<float2> cpuout(num_of_ops, float2{0.0f, 0.0f});
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fp162_arith_cpu(in1, in2, cpuout);
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std::vector<float2> out(num_of_ops, float2{0.0f, 0.0f});
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HIP_CHECK(hipMemcpy(out.data(), dout, sizeof(float2) * out.size(), hipMemcpyDeviceToHost));
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for (size_t i = 0; i < out.size(); i++) {
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INFO("Iter: " << i << " In1: " << in1[i].x << " - " << in1[i].y << " CPU res: " << cpuout[i].x
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<< " - " << cpuout[i].y << " GPU res: " << out[i].x << " - " << out[i].y);
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REQUIRE(out[i].x == Catch::Approx(cpuout[i].x).epsilon(0.1));
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REQUIRE(out[i].y == Catch::Approx(cpuout[i].y).epsilon(0.1));
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}
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HIP_CHECK(hipFree(dout));
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HIP_CHECK(hipFree(din1));
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HIP_CHECK(hipFree(din2));
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}
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}
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TEST_CASE("Unit_fp16_host_operations") {
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std::vector<float> f_a, f_b;
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f_a.reserve(50);
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f_b.reserve(50);
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for (int i = -10; i <= 10; i++) {
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if (i == 0) continue; // skip to cause issue with 0/0
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f_a.push_back(static_cast<float>(i));
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f_b.push_back(static_cast<float>(i));
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}
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std::reverse(f_b.begin(), f_b.end());
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std::vector<__half> d_a, d_b;
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d_a.reserve(f_a.size());
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d_b.reserve(f_b.size());
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for (size_t i = 0; i < f_a.size(); i++) {
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d_a.push_back(f_a[i]);
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d_b.push_back(f_b[i]);
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}
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SECTION("plus equal op - host") {
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auto res = d_a;
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for (size_t i = 0; i < res.size(); i++) {
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res[i] += d_b[i];
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}
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for (size_t i = 0; i < res.size(); i++) {
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auto f_res = f_a[i] + f_b[i];
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INFO("Float res: " << f_res << " half res: " << float(res[i]));
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REQUIRE(__half(f_res) == res[i]);
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}
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}
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SECTION("minus equal op - host") {
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auto res = d_a;
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for (size_t i = 0; i < res.size(); i++) {
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res[i] -= d_b[i];
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}
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for (size_t i = 0; i < res.size(); i++) {
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auto f_res = f_a[i] - f_b[i];
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INFO("Float res: " << f_res << " half res: " << float(res[i]));
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REQUIRE(__half(f_res) == res[i]);
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}
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}
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SECTION("mul equal op - host") {
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auto res = d_a;
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for (size_t i = 0; i < res.size(); i++) {
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res[i] *= d_b[i];
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}
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for (size_t i = 0; i < res.size(); i++) {
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auto f_res = f_a[i] * f_b[i];
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INFO("Float res: " << f_res << " half res: " << float(res[i]));
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REQUIRE(__half(f_res) == res[i]);
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}
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}
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SECTION("div equal op - host") {
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auto res = d_a;
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for (size_t i = 0; i < res.size(); i++) {
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res[i] /= d_b[i];
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}
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for (size_t i = 0; i < res.size(); i++) {
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auto f_res = f_a[i] / f_b[i];
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INFO("Float res: " << f_res << " half res: " << float(res[i]));
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REQUIRE(__half(f_res) == res[i]);
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}
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}
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SECTION("++ op - host") {
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auto res = d_a;
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for (size_t i = 0; i < res.size(); i++) {
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res[i]++;
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}
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for (size_t i = 0; i < res.size(); i++) {
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auto f_res = f_a[i] + 1;
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INFO("Float res: " << f_res << " half res: " << float(res[i]));
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REQUIRE(__half(f_res) == res[i]);
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}
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}
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SECTION("-- op - host") {
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auto res = d_a;
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for (size_t i = 0; i < res.size(); i++) {
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res[i]--;
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}
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for (size_t i = 0; i < res.size(); i++) {
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auto f_res = f_a[i] - 1;
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INFO("Float res: " << f_res << " half res: " << float(res[i]));
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REQUIRE(__half(f_res) == res[i]);
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}
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}
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}
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TEST_CASE("Unit_half_isnan_host") {
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std::vector<__half> in{std::nanf(""),
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|
std::nanf("1"),
|
|
std::nanf("2"),
|
|
-std::nanf(""),
|
|
-std::nanf("1"),
|
|
-std::nanf("2"),
|
|
std::numeric_limits<float>::infinity(),
|
|
-std::numeric_limits<float>::infinity(),
|
|
HIPRT_MAX_NORMAL_FP16,
|
|
-0.0f,
|
|
0.0f};
|
|
|
|
std::vector<__half> h_in;
|
|
h_in.reserve(in.size());
|
|
for (const auto& i : in) {
|
|
h_in.push_back(i);
|
|
}
|
|
|
|
SECTION("isnan") {
|
|
for (const auto& i : in) {
|
|
if (std::isnan(float(i))) {
|
|
INFO("isnan check: " << float(i));
|
|
REQUIRE(__hisnan(i));
|
|
} else {
|
|
INFO("not isnan check: " << float(i));
|
|
REQUIRE(!__hisnan(i));
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
SECTION("isinf") {
|
|
for (const auto& i : in) {
|
|
if (std::isinf(float(i))) {
|
|
INFO("isinf check: " << float(i));
|
|
REQUIRE(__hisinf(i));
|
|
} else {
|
|
INFO("not isnan check: " << float(i));
|
|
REQUIRE(!__hisinf(i));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST_CASE("Unit_half_abs_host") {
|
|
std::vector<float> f_a;
|
|
f_a.reserve(1000);
|
|
|
|
for (int i = -100; i <= 100; i++) {
|
|
f_a.push_back(static_cast<float>(i));
|
|
}
|
|
|
|
std::vector<__half> d_a;
|
|
d_a.reserve(f_a.size());
|
|
|
|
for (size_t i = 0; i < f_a.size(); i++) {
|
|
d_a.push_back(f_a[i]);
|
|
}
|
|
|
|
SECTION("habs") {
|
|
for (const auto& i : d_a) {
|
|
INFO("Abs of: " << float(i));
|
|
REQUIRE(__habs(i) == __half(std::abs(float(i))));
|
|
}
|
|
}
|
|
|
|
SECTION("habs2") {
|
|
for (size_t i = 0; i < d_a.size(); i++) {
|
|
__half2 tmp{d_a[i], d_a[i]};
|
|
auto abs_res = __habs2(tmp);
|
|
INFO("Abs of: " << float(d_a[i]));
|
|
REQUIRE(abs_res == __half2{std::abs(float(d_a[i])), std::abs(float(d_a[i]))});
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST_CASE("Unit_half_min_max_host") {
|
|
std::vector<float> f_a;
|
|
f_a.reserve(1000);
|
|
|
|
for (int i = -100; i <= 100; i++) {
|
|
f_a.push_back(static_cast<float>(i));
|
|
}
|
|
|
|
std::vector<__half> d_a, d_b;
|
|
d_a.reserve(f_a.size());
|
|
|
|
for (size_t i = 0; i < f_a.size(); i++) {
|
|
d_a.push_back(f_a[i]);
|
|
}
|
|
|
|
d_b = d_a;
|
|
std::reverse(d_b.begin(), d_b.end());
|
|
|
|
auto p_nan = __half(std::nan(""));
|
|
auto n_nan = __half(-p_nan);
|
|
|
|
SECTION("min") {
|
|
for (size_t i = 0; i < d_a.size(); i++) {
|
|
float f_1 = float(d_a[i]), f_2 = float(d_b[i]);
|
|
INFO("Checking min of " << f_1 << ", " << f_2);
|
|
REQUIRE(__hmin(d_a[i], d_b[i]) == __half(std::min(f_1, f_2)));
|
|
}
|
|
}
|
|
|
|
SECTION("max") {
|
|
for (size_t i = 0; i < d_a.size(); i++) {
|
|
float f_1 = float(d_a[i]), f_2 = float(d_b[i]);
|
|
INFO("Checking min of " << f_1 << ", " << f_2);
|
|
REQUIRE(__hmax(d_a[i], d_b[i]) == __half(std::max(f_1, f_2)));
|
|
}
|
|
}
|
|
|
|
SECTION("min with nan") {
|
|
__half one = 1.0f;
|
|
REQUIRE(__hmin(p_nan, one) == one);
|
|
REQUIRE(__hmin(one, p_nan) == one);
|
|
REQUIRE(__hmin(n_nan, one) == one);
|
|
REQUIRE(__hmin(one, n_nan) == one);
|
|
|
|
REQUIRE(__hisnan(__hmin(p_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmin(n_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmin(p_nan, n_nan)));
|
|
REQUIRE(__hisnan(__hmin(n_nan, n_nan)));
|
|
}
|
|
|
|
|
|
SECTION("max with nan") {
|
|
__half one = 1.0f;
|
|
REQUIRE(__hmax(p_nan, one) == one);
|
|
REQUIRE(__hmax(one, p_nan) == one);
|
|
REQUIRE(__hmax(n_nan, one) == one);
|
|
REQUIRE(__hmax(one, n_nan) == one);
|
|
|
|
REQUIRE(__hisnan(__hmax(p_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmax(n_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmax(p_nan, n_nan)));
|
|
REQUIRE(__hisnan(__hmax(n_nan, n_nan)));
|
|
}
|
|
|
|
SECTION("hmin_nan") {
|
|
__half one = 1.0f;
|
|
__half n_one = -one;
|
|
REQUIRE(__hisnan(__hmin_nan(p_nan, one)));
|
|
REQUIRE(__hisnan(__hmin_nan(one, p_nan)));
|
|
REQUIRE(__hisnan(__hmin_nan(n_nan, one)));
|
|
REQUIRE(__hisnan(__hmin_nan(one, n_nan)));
|
|
REQUIRE(__hisnan(__hmin_nan(p_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmin_nan(n_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmin_nan(p_nan, n_nan)));
|
|
REQUIRE(__hisnan(__hmin_nan(n_nan, n_nan)));
|
|
|
|
REQUIRE(__hmin_nan(one, n_one) == n_one);
|
|
REQUIRE(__hmin_nan(n_one, one) == n_one);
|
|
REQUIRE(__hmin_nan(one, one) == one);
|
|
REQUIRE(__hmin_nan(n_one, n_one) == n_one);
|
|
}
|
|
|
|
|
|
SECTION("hmax_nan") {
|
|
__half one = 1.0f;
|
|
__half n_one = -one;
|
|
REQUIRE(__hisnan(__hmax_nan(p_nan, one)));
|
|
REQUIRE(__hisnan(__hmax_nan(one, p_nan)));
|
|
REQUIRE(__hisnan(__hmax_nan(n_nan, one)));
|
|
REQUIRE(__hisnan(__hmax_nan(one, n_nan)));
|
|
REQUIRE(__hisnan(__hmax_nan(p_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmax_nan(n_nan, p_nan)));
|
|
REQUIRE(__hisnan(__hmax_nan(p_nan, n_nan)));
|
|
REQUIRE(__hisnan(__hmax_nan(n_nan, n_nan)));
|
|
|
|
REQUIRE(__hmax_nan(one, n_one) == one);
|
|
REQUIRE(__hmax_nan(n_one, one) == one);
|
|
REQUIRE(__hmax_nan(one, one) == one);
|
|
REQUIRE(__hmax_nan(n_one, n_one) == n_one);
|
|
}
|
|
}
|