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 "src/core/NEON/kernels/NEMeanStdDevNormalizationKernel.h"
25
26 #include "arm_compute/core/Helpers.h"
27 #include "arm_compute/core/ITensor.h"
28 #include "arm_compute/core/TensorInfo.h"
29 #include "arm_compute/core/Types.h"
30 #include "arm_compute/core/Window.h"
31 #include "src/core/CPP/Validate.h"
32 #include "src/core/NEON/NEMath.h"
33 #include "src/core/NEON/wrapper/wrapper.h"
34 #include "src/core/helpers/AutoConfiguration.h"
35 #include "src/core/helpers/WindowHelpers.h"
36
37 namespace arm_compute
38 {
39 namespace
40 {
validate_arguments(const ITensorInfo * input,const ITensorInfo * output,float epsilon)41 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float epsilon)
42 {
43 ARM_COMPUTE_UNUSED(epsilon);
44 ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
45 ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
46 ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 2, "Input tensor cannot have more than 2 dimensions");
47 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
48
49 // Checks performed when output is configured
50 if((output != nullptr) && (output->total_size() != 0))
51 {
52 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
53 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
54 }
55 return Status{};
56 }
57
validate_and_configure_window(ITensorInfo * input,ITensorInfo * output)58 std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
59 {
60 if(output != nullptr)
61 {
62 ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
63 // Output auto inizialitation if not yet initialized
64 auto_init_if_empty(*output, *input);
65 }
66
67 // This kernel doesn't need padding. A left-over for loop on dimension X, we cannot have any read or write out of memory
68 // For this reason num_elems_processed_per_iteration is set to 1
69 Window win = calculate_max_window(*input, Steps());
70 if(output != nullptr)
71 {
72 output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape()));
73 }
74
75 return std::make_pair(Status{}, win);
76 }
77 } // namespace
78
79 template <typename ScalarType, int size>
mean_stddev_normalization(const Window & window)80 void NEMeanStdDevNormalizationKernel::mean_stddev_normalization(const Window &window)
81 {
82 using ExactTagType = typename wrapper::traits::neon_vector<ScalarType, size>::tag_type;
83
84 // Set build options
85 Window win = window;
86 win.set(Window::DimX, Window::Dimension(0, 1, 1));
87
88 const int window_step_x = size;
89 const auto window_start_x = static_cast<int>(window.x().start());
90 const auto window_end_x = static_cast<int>(window.x().end());
91
92 Iterator input(_input, win);
93 Iterator output(_output, win);
94
95 execute_window_loop(win, [&](const Coordinates &)
96 {
97 int x = window_start_x;
98 auto in_ptr = reinterpret_cast<const ScalarType *>(input.ptr());
99 auto out_ptr = reinterpret_cast<ScalarType *>(output.ptr());
100
101 auto sum_vec = wrapper::vdup_n(static_cast<ScalarType>(0.f), ExactTagType{});
102 auto sum_sq_vec = wrapper::vdup_n(static_cast<ScalarType>(0.f), ExactTagType{});
103
104 for(; x <= (window_end_x - window_step_x); x += window_step_x)
105 {
106 auto data = wrapper::vloadq(in_ptr + x);
107 sum_vec = wrapper::vadd(sum_vec, data);
108 sum_sq_vec = wrapper::vadd(sum_sq_vec, wrapper::vmul(data, data));
109 }
110
111 auto sum_carry_res = wrapper::vpadd(wrapper::vgethigh(sum_vec), wrapper::vgetlow(sum_vec));
112 auto sum_sq_carry_res = wrapper::vpadd(wrapper::vgethigh(sum_sq_vec), wrapper::vgetlow(sum_sq_vec));
113 for(int i = 0; i < size / 4; ++i)
114 {
115 sum_carry_res = wrapper::vpadd(sum_carry_res, sum_carry_res);
116 sum_sq_carry_res = wrapper::vpadd(sum_sq_carry_res, sum_sq_carry_res);
117 }
118
119 auto sum = wrapper::vgetlane(sum_carry_res, 0);
120 auto sum_sq = wrapper::vgetlane(sum_sq_carry_res, 0);
121
122 // Compute left-over elements
123 for(; x < window_end_x; ++x)
124 {
125 ScalarType data = *(in_ptr + x);
126 sum += data;
127 sum_sq += data * data;
128 }
129
130 ScalarType mean = sum / _input->info()->dimension(0);
131 ScalarType var = (sum_sq / _input->info()->dimension(0)) - (mean * mean);
132 ScalarType stddev_inv = 1.f / sqrt(var + _epsilon);
133
134 auto mean_vec = wrapper::vdup_n(mean, ExactTagType{});
135 auto stddev_inv_vec = wrapper::vdup_n(stddev_inv, ExactTagType{});
136 for(x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
137 {
138 auto data = wrapper::vloadq(in_ptr + x);
139 auto res = wrapper::vmul(wrapper::vsub(data, mean_vec), stddev_inv_vec);
140 // Store results
141 wrapper::vstore(out_ptr + x, res);
142 }
143 for(; x < window_end_x; ++x)
144 {
145 *(out_ptr + x) = (*(in_ptr + x) - mean) * stddev_inv;
146 }
147 },
148 input, output);
149 }
150
NEMeanStdDevNormalizationKernel()151 NEMeanStdDevNormalizationKernel::NEMeanStdDevNormalizationKernel()
152 : _input(nullptr), _output(nullptr), _epsilon(1e-8f), _func(nullptr)
153 {
154 }
155
configure(ITensor * input,ITensor * output,float epsilon)156 void NEMeanStdDevNormalizationKernel::configure(ITensor *input, ITensor *output, float epsilon)
157 {
158 ARM_COMPUTE_ERROR_ON_NULLPTR(input);
159
160 ARM_COMPUTE_ERROR_THROW_ON(NEMeanStdDevNormalizationKernel::validate(input->info(), (output != nullptr) ? output->info() : nullptr, epsilon));
161
162 _input = input;
163 _output = (output == nullptr) ? input : output;
164 _epsilon = epsilon;
165
166 // Configure kernel window
167 auto win_config = validate_and_configure_window(input->info(), (output == nullptr) ? nullptr : output->info());
168 ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
169 ICPPKernel::configure(win_config.second);
170
171 // Configure function to run based on different data types
172 const DataType data_type = input->info()->data_type();
173 switch(data_type)
174 {
175 case DataType::F32:
176 _func = &NEMeanStdDevNormalizationKernel::mean_stddev_normalization<float, 4>;
177 break;
178 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
179 case DataType::F16:
180 _func = &NEMeanStdDevNormalizationKernel::mean_stddev_normalization<float16_t, 8>;
181 break;
182 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
183 default:
184 ARM_COMPUTE_ERROR("Not Supported");
185 break;
186 }
187 }
188
validate(const ITensorInfo * input,const ITensorInfo * output,float epsilon)189 Status NEMeanStdDevNormalizationKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float epsilon)
190 {
191 ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, epsilon));
192 ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (output != nullptr) ? output->clone().get() : nullptr).first);
193 return Status{};
194 }
195
run(const Window & window,const ThreadInfo & info)196 void NEMeanStdDevNormalizationKernel::run(const Window &window, const ThreadInfo &info)
197 {
198 ARM_COMPUTE_UNUSED(info);
199 ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
200 ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
201 ARM_COMPUTE_ERROR_ON(_func == nullptr);
202
203 (this->*_func)(window);
204 }
205 } // namespace arm_compute
206