1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
|
/*
* Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/core/NEON/kernels/NEDequantizationLayerKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include <arm_neon.h>
using namespace arm_compute;
NEDequantizationLayerKernel::NEDequantizationLayerKernel()
: _input(nullptr), _output(nullptr), _min_max(nullptr)
{
}
void NEDequantizationLayerKernel::configure(const ITensor *input, ITensor *output, const ITensor *min_max)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
ARM_COMPUTE_ERROR_ON_NULLPTR(output);
ARM_COMPUTE_ERROR_ON_NULLPTR(min_max);
ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() < 3);
// Output tensor auto initialization if not yet initialized
auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, DataType::F32, 0);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
_input = input;
_output = output;
_min_max = min_max;
constexpr unsigned int num_elems_processed_per_iteration = 8;
// Configure window
Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
AccessWindowStatic min_max_access(min_max->info(), 0, 0, 2, min_max->info()->dimension(1));
// Update window and padding
update_window_and_padding(win, input_access, output_access, min_max_access);
output_access.set_valid_region(win, input->info()->valid_region());
INEKernel::configure(win);
}
void NEDequantizationLayerKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
Window window_input_output(window);
window_input_output.set(3, Window::Dimension(0, 1, 1));
Window window_min_max;
window_min_max.use_tensor_dimensions(_min_max->info()->tensor_shape());
window_min_max.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator input(_input, window_input_output);
Iterator output(_output, window_input_output);
Iterator min_max(_min_max, window_min_max);
execute_window_loop(window_min_max, [&](const Coordinates & id_batch)
{
// Get the min and max
const float min = *(reinterpret_cast<const float *>(min_max.ptr()) + 0);
const float max = *(reinterpret_cast<const float *>(min_max.ptr()) + 1);
const float32x4_t vmin = vdupq_n_f32(min);
const float range = max - min;
const float32x4_t scaling = vdupq_n_f32(range / 255.0f);
// Uniformly map values to range 8bit integers, i.e. [min, max] -> [0, 255]
execute_window_loop(window_input_output, [&](const Coordinates & id)
{
// Get the input values
const auto input_ptr = reinterpret_cast<const uint8_t *>(input.ptr() + id_batch[1] * _input->info()->strides_in_bytes()[3]);
const uint8x8_t val_u8 = vld1_u8(input_ptr);
const uint16x8_t val_u16 = vmovl_u8(val_u8);
const uint32x4_t val_u32_low = vmovl_u16(vget_low_u16(val_u16));
const uint32x4_t val_u32_high = vmovl_u16(vget_high_u16(val_u16));
float32x4_t val_low = vcvtq_f32_u32(val_u32_low);
float32x4_t val_high = vcvtq_f32_u32(val_u32_high);
// Dequantize -> (q / 255.0 * range) + min
val_low = vmulq_f32(val_low, scaling);
val_high = vmulq_f32(val_high, scaling);
val_low = vaddq_f32(val_low, vmin);
val_high = vaddq_f32(val_high, vmin);
const float32x4x2_t dequantized = vuzpq_f32(val_low, val_high);
// Store the dequantized values
auto output_ptr = reinterpret_cast<float *>(output.ptr() + id_batch[1] * _output->info()->strides_in_bytes()[3]);
vst2q_f32(output_ptr, dequantized);
},
input, output);
},
min_max);
}
|
