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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-init.h>
20 #include <xnnpack/params.h>
21 
22 
23 class VBinOpMicrokernelTester {
24  public:
25   enum class OpType {
26     Add,
27     Div,
28     Max,
29     Min,
30     Mul,
31     Sub,
32   };
33 
34   enum class Variant {
35     Native,
36     Scalar,
37   };
38 
batch_size(size_t batch_size)39   inline VBinOpMicrokernelTester& batch_size(size_t batch_size) {
40     assert(batch_size != 0);
41     this->batch_size_ = batch_size;
42     return *this;
43   }
44 
batch_size()45   inline size_t batch_size() const {
46     return this->batch_size_;
47   }
48 
inplace_a(bool inplace_a)49   inline VBinOpMicrokernelTester& inplace_a(bool inplace_a) {
50     this->inplace_a_ = inplace_a;
51     return *this;
52   }
53 
inplace_a()54   inline bool inplace_a() const {
55     return this->inplace_a_;
56   }
57 
inplace_b(bool inplace_b)58   inline VBinOpMicrokernelTester& inplace_b(bool inplace_b) {
59     this->inplace_b_ = inplace_b;
60     return *this;
61   }
62 
inplace_b()63   inline bool inplace_b() const {
64     return this->inplace_b_;
65   }
66 
qmin(uint8_t qmin)67   inline VBinOpMicrokernelTester& qmin(uint8_t qmin) {
68     this->qmin_ = qmin;
69     return *this;
70   }
71 
qmin()72   inline uint8_t qmin() const {
73     return this->qmin_;
74   }
75 
qmax(uint8_t qmax)76   inline VBinOpMicrokernelTester& qmax(uint8_t qmax) {
77     this->qmax_ = qmax;
78     return *this;
79   }
80 
qmax()81   inline uint8_t qmax() const {
82     return this->qmax_;
83   }
84 
iterations(size_t iterations)85   inline VBinOpMicrokernelTester& iterations(size_t iterations) {
86     this->iterations_ = iterations;
87     return *this;
88   }
89 
iterations()90   inline size_t iterations() const {
91     return this->iterations_;
92   }
93 
94   void Test(xnn_f32_vbinary_ukernel_function vbinary, OpType op_type, Variant variant = Variant::Native) const {
95     std::random_device random_device;
96     auto rng = std::mt19937(random_device());
97     auto f32rng = std::bind(std::uniform_real_distribution<float>(0.01f, 1.0f), rng);
98 
99     std::vector<float> a(batch_size() + XNN_EXTRA_BYTES / sizeof(float));
100     std::vector<float> b(batch_size() + XNN_EXTRA_BYTES / sizeof(float));
101     std::vector<float> y(batch_size() + (inplace_a() || inplace_b() ? XNN_EXTRA_BYTES / sizeof(float) : 0));
102     std::vector<float> y_ref(batch_size());
103     for (size_t iteration = 0; iteration < iterations(); iteration++) {
104       std::generate(a.begin(), a.end(), std::ref(f32rng));
105       std::generate(b.begin(), b.end(), std::ref(f32rng));
106       if (inplace_a() || inplace_b()) {
107         std::generate(y.begin(), y.end(), std::ref(f32rng));
108       } else {
109         std::fill(y.begin(), y.end(), nanf(""));
110       }
111       const float* a_data = inplace_a() ? y.data() : a.data();
112       const float* b_data = inplace_b() ? y.data() : b.data();
113 
114       // Compute reference results.
115       for (size_t i = 0; i < batch_size(); i++) {
116         switch (op_type) {
117           case OpType::Add:
118             y_ref[i] = a_data[i] + b_data[i];
119             break;
120           case OpType::Div:
121             y_ref[i] = a_data[i] / b_data[i];
122             break;
123           case OpType::Max:
124             y_ref[i] = std::max<float>(a_data[i], b_data[i]);
125             break;
126           case OpType::Min:
127             y_ref[i] = std::min<float>(a_data[i], b_data[i]);
128             break;
129           case OpType::Mul:
130             y_ref[i] = a_data[i] * b_data[i];
131             break;
132           case OpType::Sub:
133             y_ref[i] = a_data[i] - b_data[i];
134             break;
135         }
136       }
137       const float accumulated_min = *std::min_element(y_ref.cbegin(), y_ref.cend());
138       const float accumulated_max = *std::max_element(y_ref.cbegin(), y_ref.cend());
139       const float accumulated_range = accumulated_max - accumulated_min;
140       const float y_max = accumulated_range > 0.0f ?
141         (accumulated_max - accumulated_range / 255.0f * float(255 - qmax())) :
142         +std::numeric_limits<float>::infinity();
143       const float y_min = accumulated_range > 0.0f ?
144         (accumulated_min + accumulated_range / 255.0f * float(qmin())) :
145         -std::numeric_limits<float>::infinity();
146       for (size_t i = 0; i < batch_size(); i++) {
147         y_ref[i] = std::max<float>(std::min<float>(y_ref[i], y_max), y_min);
148       }
149 
150       // Prepare output parameters.
151       xnn_f32_output_params output_params = { };
152       switch (variant) {
153         case Variant::Native:
154           output_params = xnn_init_f32_output_params(y_min, y_max);
155           break;
156         case Variant::Scalar:
157           output_params = xnn_init_scalar_f32_output_params(y_min, y_max);
158           break;
159       }
160 
161       // Call optimized micro-kernel.
162       vbinary(batch_size() * sizeof(float), a_data, b_data, y.data(), &output_params);
163 
164       // Verify results.
165       for (size_t i = 0; i < batch_size(); i++) {
166         ASSERT_NEAR(y[i], y_ref[i], std::abs(y_ref[i]) * 1.0e-6f)
167           << "at " << i << " / " << batch_size();
168       }
169     }
170   }
171 
172  private:
173   size_t batch_size_{1};
174   bool inplace_a_{false};
175   bool inplace_b_{false};
176   uint8_t qmin_{0};
177   uint8_t qmax_{255};
178   size_t iterations_{15};
179 };
180