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
130
131
|
/*
* Copyright (c) 2016, 2017 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/NEGEMMMatrixVectorMultiplyKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/NEON/INEKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include <arm_neon.h>
#include <cstddef>
#include <cstdint>
#include <tuple>
using namespace arm_compute;
NEGEMMMatrixVectorMultiplyKernel::NEGEMMMatrixVectorMultiplyKernel()
: _input0(nullptr), _input1(nullptr), _output(nullptr)
{
}
void NEGEMMMatrixVectorMultiplyKernel::configure(const ITensor *input0, const ITensor *input1, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output);
ARM_COMPUTE_ERROR_ON(input0->info()->dimension(2) != input1->info()->dimension(1));
_input0 = input0;
_input1 = input1;
_output = output;
// Configure kernel window
const unsigned int num_elems_read_per_iteration = 4;
Window win = calculate_max_window(*input0->info(), Steps(num_elems_read_per_iteration));
AccessWindowHorizontal input0_access(input0->info(), 0, num_elems_read_per_iteration);
AccessWindowHorizontal input1_access(input1->info(), 0, num_elems_read_per_iteration);
AccessWindowHorizontal output_access(output->info(), 0, 1);
update_window_and_padding(win, input0_access, input1_access, output_access);
_output->info()->set_valid_region(ValidRegion(Coordinates(), _output->info()->tensor_shape()));
INEKernel::configure(win);
}
void NEGEMMMatrixVectorMultiplyKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
Window window_slice = window.first_slice_window_3D();
Window window_in(window);
Window window_weights(window_slice);
Window window_out(window);
// Setup input0 slice
window_in.set(Window::DimX, Window::Dimension(0, _input0->info()->dimension(0), _input0->info()->dimension(0)));
window_in.set(Window::DimY, Window::Dimension(0, _input0->info()->dimension(1), 1));
window_in.set(Window::DimZ, Window::Dimension(0, _input0->info()->dimension(2), 1));
// Setup input1 and output slice. Their dimensions are increased in the kernel.
window_weights.set(Window::DimX, Window::Dimension(0, 0, 0));
window_weights.set(Window::DimY, Window::Dimension(0, 0, 0));
window_weights.set(Window::DimZ, Window::Dimension(0, 0, 0));
window_out.set(Window::DimX, Window::Dimension(0, 0, 0));
window_out.set(Window::DimY, Window::Dimension(0, 0, 0));
window_out.set(Window::DimZ, Window::Dimension(0, 0, 0));
Iterator in(_input0, window_in);
Iterator in2(_input1, window_weights);
Iterator out(_output, window_out);
const int input_w = _input0->info()->dimension(0);
const int input_h = _input0->info()->dimension(1);
const int input_stride_x = _input0->info()->strides_in_bytes().x();
const int weights_stride_x = _input1->info()->strides_in_bytes().x();
const int weights_stride_y = _input1->info()->strides_in_bytes().y();
const int output_stride_x = _output->info()->strides_in_bytes().x();
execute_window_loop(window_in, [&](const Coordinates & id)
{
// Get pointers
const uint8_t *const input_ptr = in.ptr();
const uint8_t *const weights_ptr = in2.ptr() + id.z() * weights_stride_y;
auto output_ptr = reinterpret_cast<float *>(out.ptr() + (id.y() + id.z() * input_h) * output_stride_x);
float32x4_t row_dot = vdupq_n_f32(0.f);
for(int i = 0; i < input_w; i += 4)
{
const auto input = vld1q_f32(reinterpret_cast<const float *>(input_ptr + i * input_stride_x));
const auto weights = vld1q_f32(reinterpret_cast<const float *>(weights_ptr + i * weights_stride_x));
row_dot = vaddq_f32(row_dot, vmulq_f32(input, weights));
}
auto temp = vadd_f32(vget_high_f32(row_dot), vget_low_f32(row_dot));
temp = vpadd_f32(temp, temp);
*output_ptr = vget_lane_f32(temp, 0);
},
in, in2, out);
}
|
