1 /*
2 * Copyright (c) 2018-2020 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/NETileKernel.h"
25
26 #include "arm_compute/core/Error.h"
27 #include "arm_compute/core/Helpers.h"
28 #include "arm_compute/core/ITensor.h"
29 #include "arm_compute/core/TensorInfo.h"
30 #include "arm_compute/core/Validate.h"
31 #include "arm_compute/core/Window.h"
32 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
33 #include "src/core/helpers/AutoConfiguration.h"
34 #include "src/core/helpers/WindowHelpers.h"
35
36 namespace arm_compute
37 {
38 namespace
39 {
validate_arguments(const ITensorInfo * input,const ITensorInfo * output,const Multiples & multiples)40 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Multiples &multiples)
41 {
42 ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
43 ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
44 ARM_COMPUTE_RETURN_ERROR_ON(multiples.size() > 4);
45 ARM_COMPUTE_RETURN_ERROR_ON(multiples.empty());
46 ARM_COMPUTE_RETURN_ERROR_ON(std::any_of(multiples.begin(), multiples.end(), [](uint32_t e)
47 {
48 return e == 0;
49 }));
50
51 // Validate output if initialized
52 if(output->total_size() != 0)
53 {
54 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(misc::shape_calculator::compute_tiled_shape(input->tensor_shape(), multiples), output->tensor_shape());
55 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
56 }
57
58 return Status{};
59 }
60 } // namespace
61
NETileKernel()62 NETileKernel::NETileKernel()
63 : _input(nullptr), _output(nullptr)
64 {
65 }
66
configure(const ITensor * input,ITensor * output,const Multiples & multiples)67 void NETileKernel::configure(const ITensor *input, ITensor *output, const Multiples &multiples)
68 {
69 ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
70
71 // Auto initialize output
72 TensorShape tiled_shape = misc::shape_calculator::compute_tiled_shape(input->info()->tensor_shape(), multiples);
73 auto_init_if_empty(*output->info(), tiled_shape, 1, input->info()->data_type());
74
75 // Validate
76 ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), multiples));
77
78 _input = input;
79 _output = output;
80
81 // Configure window without padding
82 Window win = calculate_max_window(*output->info());
83 INEKernel::configure(win);
84 }
85
validate(const ITensorInfo * input,const ITensorInfo * output,const Multiples & multiples)86 Status NETileKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Multiples &multiples)
87 {
88 ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, multiples));
89 return Status{};
90 }
91
run(const Window & window,const ThreadInfo & info)92 void NETileKernel::run(const Window &window, const ThreadInfo &info)
93 {
94 ARM_COMPUTE_UNUSED(info);
95 ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
96 ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
97
98 Window output_window{ window };
99 output_window.set(Window::DimX, Window::Dimension(output_window.x().start(), output_window.x().end(), _input->info()->dimension(0)));
100 Window out_slice = output_window.first_slice_window_1D();
101
102 const auto src_shape = _input->info()->tensor_shape();
103 do
104 {
105 Iterator output_it(_output, out_slice);
106
107 execute_window_loop(out_slice, [&](const Coordinates & id)
108 {
109 const size_t x = id.x();
110 const size_t y = id.y();
111 const size_t z = id.z();
112 const size_t w = id[3];
113 Coordinates input_coords{ x % src_shape[0], y % src_shape[1], z % src_shape[2], w % src_shape[3] };
114 memcpy(output_it.ptr(), _input->ptr_to_element(input_coords), _input->info()->dimension(0) * _input->info()->element_size());
115 },
116 output_it);
117 }
118 while(output_window.slide_window_slice_1D(out_slice));
119 }
120 } // namespace arm_compute
121