1 /*
2 * Copyright (c) 2019-2020 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 #include "arm_compute/core/CPP/kernels/CPPTopKVKernel.h"
25
26 #include "arm_compute/core/Helpers.h"
27 #include "arm_compute/core/TensorInfo.h"
28 #include "arm_compute/core/utils/misc/Traits.h"
29
30 #include "src/core/helpers/AutoConfiguration.h"
31 #include "src/core/helpers/WindowHelpers.h"
32
33 namespace arm_compute
34 {
35 namespace
36 {
37 template <typename T,
38 typename std::enable_if<utils::traits::is_floating_point<T>::value, int>::type = 0>
greater_than(T a,T b)39 inline bool greater_than(T a, T b)
40 {
41 const T epsilon = std::numeric_limits<T>::epsilon();
42 return (a - b > epsilon);
43 }
44
45 template < typename T,
46 typename std::enable_if < !utils::traits::is_floating_point<T>::value, int >::type = 0 >
greater_than(T a,T b)47 inline bool greater_than(T a, T b)
48 {
49 return (a > b);
50 }
51
validate_arguments(const ITensorInfo * predictions,const ITensorInfo * targets,ITensorInfo * output,const unsigned int k)52 Status validate_arguments(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k)
53 {
54 ARM_COMPUTE_UNUSED(k);
55 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(predictions, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32, DataType::F16, DataType::F32);
56 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(targets, 1, DataType::U32);
57
58 ARM_COMPUTE_RETURN_ERROR_ON(predictions->num_dimensions() > 2);
59 ARM_COMPUTE_RETURN_ERROR_ON(targets->num_dimensions() > 1);
60 ARM_COMPUTE_RETURN_ERROR_ON(targets->dimension(0) != predictions->dimension(1));
61 // Validate configured output
62 if(output->total_size() != 0)
63 {
64 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), targets->tensor_shape());
65 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
66 }
67
68 return Status{};
69 }
70 } // namespace
71
72 template <typename T>
run_topkv()73 void CPPTopKVKernel::run_topkv()
74 {
75 for(unsigned int i = 0; i < _batch_size; ++i)
76 {
77 const auto target_class_id = *reinterpret_cast<uint32_t *>(_targets->ptr_to_element(Coordinates{ i }));
78 const auto predicted_value = *reinterpret_cast<T *>(_predictions->ptr_to_element(Coordinates{ target_class_id, i }));
79
80 // The variable rank indicates how many values there are before the target_class_id
81 unsigned int rank = 0;
82 for(unsigned int j = 0; (j < _num_classes) && (rank < _k); ++j)
83 {
84 const auto current_prediction = *reinterpret_cast<T *>(_predictions->ptr_to_element(Coordinates{ j, i }));
85 if(greater_than(current_prediction, predicted_value))
86 {
87 rank++;
88 }
89 }
90 *(_output->ptr_to_element(Coordinates{ i })) = static_cast<uint8_t>(rank < _k);
91 }
92 }
93
CPPTopKVKernel()94 CPPTopKVKernel::CPPTopKVKernel()
95 : _predictions(nullptr), _targets(nullptr), _output(nullptr), _k(), _batch_size(), _num_classes()
96 {
97 }
98
configure(const ITensor * predictions,const ITensor * targets,ITensor * output,const unsigned int k)99 void CPPTopKVKernel::configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k)
100 {
101 ARM_COMPUTE_ERROR_ON_NULLPTR(predictions, targets, output);
102
103 // Perform validation step
104 ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(predictions->info(), targets->info(), output->info(), k));
105 auto_init_if_empty(*output->info(), targets->info()->tensor_shape(), 1, DataType::U8);
106
107 _predictions = predictions;
108 _targets = targets;
109 _output = output;
110
111 _k = k;
112 _batch_size = predictions->info()->dimension(1);
113 _num_classes = predictions->info()->dimension(0);
114
115 ICPPKernel::configure(Window()); // Default 1 iteration window
116 }
117
validate(const ITensorInfo * predictions,const ITensorInfo * targets,ITensorInfo * output,const unsigned int k)118 Status CPPTopKVKernel::validate(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k)
119 {
120 ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(predictions, targets, output, k));
121 return Status{};
122 }
123
is_parallelisable() const124 bool CPPTopKVKernel::is_parallelisable() const
125 {
126 return false;
127 }
128
run(const Window & window,const ThreadInfo & info)129 void CPPTopKVKernel::run(const Window &window, const ThreadInfo &info)
130 {
131 ARM_COMPUTE_UNUSED(window, info);
132 switch(_predictions->info()->data_type())
133 {
134 case DataType::F32:
135 run_topkv<float>();
136 break;
137 case DataType::F16:
138 run_topkv<half>();
139 break;
140 case DataType::S32:
141 run_topkv<int>();
142 break;
143 case DataType::QASYMM8:
144 run_topkv<uint8_t>();
145 break;
146 case DataType::QASYMM8_SIGNED:
147 run_topkv<int8_t>();
148 break;
149 default:
150 ARM_COMPUTE_ERROR("Not supported");
151 }
152 }
153 } // namespace arm_compute
154