1 /*
2 * Copyright (c) 2018-2021 Arm Limited.
3 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
24 #ifndef ARM_COMPUTE_TEST_RANGE_FIXTURE
25 #define ARM_COMPUTE_TEST_RANGE_FIXTURE
26
27 #include "arm_compute/core/TensorShape.h"
28 #include "arm_compute/core/Types.h"
29 #include "tests/AssetsLibrary.h"
30 #include "tests/Globals.h"
31 #include "tests/IAccessor.h"
32 #include "tests/framework/Asserts.h"
33 #include "tests/framework/Fixture.h"
34 #include "tests/validation/Helpers.h"
35 #include "tests/validation/reference/Range.h"
36
37 #include <algorithm>
38
39 namespace arm_compute
40 {
41 namespace test
42 {
43 namespace validation
44 {
45 namespace
46 {
num_of_elements_in_range(float start,float end,float step)47 size_t num_of_elements_in_range(float start, float end, float step)
48 {
49 ARM_COMPUTE_ERROR_ON(step == 0);
50 return size_t(std::ceil((end - start) / step));
51 }
52 }
53
54 template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
55 class RangeFixture : public framework::Fixture
56 {
57 public:
58 template <typename...>
59 void setup(const DataType data_type0, float start, float step, const QuantizationInfo qinfo0 = QuantizationInfo())
60 {
61 _target = compute_target(data_type0, qinfo0, start, step);
62 _reference = compute_reference(data_type0, qinfo0, start, step);
63 }
64
65 protected:
get_random_end(const DataType output_data_type,const QuantizationInfo qinfo_out,float start,float step)66 float get_random_end(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step)
67 {
68 std::uniform_real_distribution<float> distribution(1, 100);
69 std::mt19937 gen(library->seed());
70 float end = start;
71 switch(output_data_type)
72 {
73 case DataType::U8:
74 end += std::max((uint8_t)1, static_cast<uint8_t>(distribution(gen))) * step;
75 return utility::clamp<float, uint8_t>(end);
76 case DataType::U16:
77 end += std::max((uint16_t)1, static_cast<uint16_t>(distribution(gen))) * step;
78 return utility::clamp<float, uint16_t>(end);
79 case DataType::U32:
80 end += std::max((uint32_t)1, static_cast<uint32_t>(distribution(gen))) * step;
81 return utility::clamp<float, uint32_t>(end);
82 case DataType::S8:
83 end += std::max((int8_t)1, static_cast<int8_t>(distribution(gen))) * step;
84 return utility::clamp<float, int8_t>(end);
85 case DataType::S16:
86 end += std::max((int16_t)1, static_cast<int16_t>(distribution(gen))) * step;
87 return utility::clamp<float, int16_t>(end);
88 case DataType::S32:
89 end += std::max((int32_t)1, static_cast<int32_t>(distribution(gen))) * step;
90 return utility::clamp<float, int32_t>(end);
91 case DataType::F32:
92 end += std::max(1.0f, static_cast<float>(distribution(gen))) * step;
93 return end;
94 case DataType::F16:
95 end += std::max(half(1.0f), static_cast<half>(distribution(gen))) * step;
96 return utility::clamp<float, half>(end);
97 case DataType::QASYMM8:
98 return utility::clamp<float, uint8_t>(end + (float)distribution(gen) * step,
99 dequantize_qasymm8(0, qinfo_out.uniform()),
100 dequantize_qasymm8(std::numeric_limits<uint8_t>::max(), qinfo_out.uniform()));
101 default:
102 return 0;
103 }
104 }
105
compute_target(const DataType output_data_type,const QuantizationInfo qinfo_out,float start,float step)106 TensorType compute_target(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step)
107 {
108 float end = get_random_end(output_data_type, qinfo_out, start, step);
109 size_t num_of_elements = num_of_elements_in_range(start, end, step);
110 // Create tensor
111 TensorType dst = create_tensor<TensorType>(TensorShape(num_of_elements), output_data_type, 1, qinfo_out);
112 // Create and configure function
113 FunctionType range_func;
114 range_func.configure(&dst, start, end, step);
115
116 ARM_COMPUTE_ASSERT(dst.info()->is_resizable());
117 // Allocate tensors
118 dst.allocator()->allocate();
119
120 ARM_COMPUTE_ASSERT(!dst.info()->is_resizable());
121
122 // Compute function
123 range_func.run();
124 return dst;
125 }
126
compute_reference(const DataType output_data_type,const QuantizationInfo qinfo_out,float start,float step)127 SimpleTensor<T> compute_reference(const DataType output_data_type, const QuantizationInfo qinfo_out, float start, float step)
128 {
129 // Create tensor
130 const float end = get_random_end(output_data_type, qinfo_out, start, step);
131 size_t num_of_elements = num_of_elements_in_range(start, end, step);
132 SimpleTensor<T> ref_dst{ TensorShape(num_of_elements ? num_of_elements : 1), output_data_type, 1, qinfo_out };
133 return reference::range<T>(ref_dst, start, num_of_elements, step);
134 }
135
136 TensorType _target{};
137 SimpleTensor<T> _reference{};
138 };
139 } // namespace validation
140 } // namespace test
141 } // namespace arm_compute
142 #endif /* ARM_COMPUTE_TEST_RANGE_FIXTURE */
143