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1 // Copyright 2019 Google LLC
2 //
3 // This source code is licensed under the BSD-style license found in the
4 // LICENSE file in the root directory of this source tree.
5 
6 #pragma once
7 
8 #include <gtest/gtest.h>
9 
10 #include <algorithm>
11 #include <cassert>
12 #include <cstddef>
13 #include <cstdlib>
14 #include <functional>
15 #include <random>
16 #include <vector>
17 
18 #include <xnnpack.h>
19 #include <xnnpack/params.h>
20 
21 
22 class RAddExpMinusMaxMicrokernelTester {
23  public:
elements(size_t elements)24   inline RAddExpMinusMaxMicrokernelTester& elements(size_t elements) {
25     assert(elements != 0);
26     this->elements_ = elements;
27     return *this;
28   }
29 
elements()30   inline size_t elements() const {
31     return this->elements_;
32   }
33 
iterations(size_t iterations)34   inline RAddExpMinusMaxMicrokernelTester& iterations(size_t iterations) {
35     this->iterations_ = iterations;
36     return *this;
37   }
38 
iterations()39   inline size_t iterations() const {
40     return this->iterations_;
41   }
42 
Test(xnn_f32_raddexpminusmax_ukernel_function raddexpminusmax)43   void Test(xnn_f32_raddexpminusmax_ukernel_function raddexpminusmax) const {
44     std::random_device random_device;
45     auto rng = std::mt19937(random_device());
46     // Choose such range that expf(x[i]) overflows, but expf(x[i] - x_max) doesn't.
47     // However, the range is still narrow enough that double-precision exp doesn't overflow.
48     auto f32rng = std::bind(std::uniform_real_distribution<float>(90.0f, 100.0f), rng);
49 
50     std::vector<float> x(elements() + XNN_EXTRA_BYTES / sizeof(float));
51     for (size_t iteration = 0; iteration < iterations(); iteration++) {
52       std::generate(x.begin(), x.end(), std::ref(f32rng));
53 
54       // Compute reference results.
55       double sum_ref = 0.0f;
56       const float x_max = *std::max_element(x.begin(), x.begin() + elements());
57       for (size_t i = 0; i < elements(); i++) {
58         sum_ref += exp(x[i] - x_max);
59       }
60 
61       // Call optimized micro-kernel.
62       float sum = std::nanf("");
63       raddexpminusmax(elements() * sizeof(float), x.data(), &sum, x_max);
64 
65       // Verify results.
66       ASSERT_NEAR(sum_ref, double(sum), std::abs(sum_ref) * 1.0e-6)
67         << "elements = " << elements() << ", x_max = " << x_max;
68     }
69   }
70 
71  private:
72   size_t elements_{1};
73   size_t iterations_{15};
74 };
75