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Manuel Bottini10b38262021-02-19 18:16:44 +00001/*
2 * Copyright (c) 2021 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 */
Georgios Pinitas7891a732021-08-20 21:39:25 +010024#include "src/cpu/operators/CpuScale.h"
Manuel Bottini10b38262021-02-19 18:16:44 +000025
26#include "arm_compute/core/Helpers.h"
27#include "arm_compute/core/TensorInfo.h"
28#include "arm_compute/core/Validate.h"
29#include "arm_compute/runtime/NEON/NEScheduler.h"
Manuel Bottini10b38262021-02-19 18:16:44 +000030#include "src/core/utils/ScaleUtils.h"
Georgios Pinitas7891a732021-08-20 21:39:25 +010031#include "src/cpu/kernels/CpuScaleKernel.h"
Manuel Bottini10b38262021-02-19 18:16:44 +000032#include "support/Rounding.h"
33
34namespace arm_compute
35{
36namespace cpu
37{
38namespace
39{
40void precompute_dx_dy_offsets(ITensor *dx, ITensor *dy, ITensor *offsets, float wr, float hr, SamplingPolicy sampling_policy, bool align_corners)
41{
42 ARM_COMPUTE_ERROR_ON(offsets == nullptr);
43 float sampling_offset = 0.0f;
44 if(sampling_policy == SamplingPolicy::CENTER)
45 {
46 sampling_offset = 0.5f;
47 }
48
49 Window win;
50 win.set(Window::DimX, Window::Dimension(0, offsets->info()->dimension(0), 1));
51 win.set(Window::DimY, Window::Dimension(0, offsets->info()->dimension(1), 1));
52
53 if(dx != nullptr && dy != nullptr)
54 {
55 // Pre-compute the offset and pixel's distance for BILINEAR interpolation
56 Iterator offsets_it(offsets, win);
57 Iterator dx_it(dx, win);
58 Iterator dy_it(dy, win);
59
60 execute_window_loop(win, [&](const Coordinates & id)
61 {
62 const float in_x = (id.x() + sampling_offset) * wr - sampling_offset;
63 const float in_y = (id.y() + sampling_offset) * hr - sampling_offset;
64 const int in_xi = std::floor(in_x);
65 const int in_yi = std::floor(in_y);
66
67 *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi;
68 *reinterpret_cast<float *>(dx_it.ptr()) = in_x - in_xi;
69 *reinterpret_cast<float *>(dy_it.ptr()) = in_y - in_yi;
70 },
71 offsets_it, dx_it, dy_it);
72 }
73 else
74 {
75 // Pre-compute the offset for NEAREST interpolation
76 Iterator offsets_it(offsets, win);
77
78 execute_window_loop(win, [&](const Coordinates & id)
79 {
80 const float float_in_xi = (id.x() + sampling_offset) * wr;
81 const auto in_xi = static_cast<size_t>(align_corners ? arm_compute::utils::rounding::round_half_away_from_zero(float_in_xi) : std::floor(float_in_xi));
82 *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi;
83 },
84 offsets_it);
85 }
86}
87} // namespace
88
Manuel Bottini10b38262021-02-19 18:16:44 +000089void CpuScale::configure(ITensorInfo *src, ITensorInfo *dst, const ScaleKernelInfo &info)
90{
91 ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
92 ARM_COMPUTE_ERROR_THROW_ON(CpuScale::validate(src, dst, info));
93
Georgios Pinitas2eb5d162021-07-02 09:01:49 +010094 _scale_info = info;
95 _is_prepared = false;
Manuel Bottini10b38262021-02-19 18:16:44 +000096
97 // Get data layout and width/height indices
Georgios Pinitas2eb5d162021-07-02 09:01:49 +010098 _data_layout = _scale_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : _scale_info.data_layout;
99 const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
100 const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
Manuel Bottini10b38262021-02-19 18:16:44 +0000101
102 // Compute the ratio between source width/height and destination width/height
103 const bool is_align_corners_used = _scale_info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(_scale_info.sampling_policy);
104 const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_width), dst->dimension(idx_width), is_align_corners_used);
105 const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_height), dst->dimension(idx_height), is_align_corners_used);
106
107 // Area interpolation behaves as Nearest Neighbour in case of up-sampling
108 InterpolationPolicy policy_to_use = (_scale_info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f
109 && hr <= 1.f) ?
110 InterpolationPolicy::NEAREST_NEIGHBOR :
111 _scale_info.interpolation_policy;
112
113 // Get the tensor shape
114 TensorShape shape(dst->dimension(idx_width));
115 shape.set(1, dst->dimension(idx_height), false);
116
117 TensorInfo tensor_info_offsets(shape, Format::S32);
118 TensorInfo tensor_info_dxdy(shape, Format::F32);
119
120 auto dx = std::make_unique<TensorInfo>(tensor_info_dxdy);
121 auto dy = std::make_unique<TensorInfo>(tensor_info_dxdy);
122 auto offsets = std::make_unique<TensorInfo>(tensor_info_offsets);
123 auto scale_kernel = std::make_unique<kernels::CpuScaleKernel>();
124 switch(policy_to_use)
125 {
126 case InterpolationPolicy::NEAREST_NEIGHBOR:
127 {
128 scale_kernel->configure(src, nullptr, nullptr, offsets.get(), dst, info);
129 break;
130 }
131 case InterpolationPolicy::BILINEAR:
132 {
133 scale_kernel->configure(src, dx.get(), dy.get(), offsets.get(), dst, info);
134 break;
135 }
136 case InterpolationPolicy::AREA:
137 {
138 scale_kernel->configure(src, nullptr, nullptr, nullptr, dst, info);
139 break;
140 }
141 default:
142 ARM_COMPUTE_ERROR("Unsupported interpolation mode");
143 }
144 _kernel = std::move(scale_kernel);
145}
146
147Status CpuScale::validate(const ITensorInfo *src, const ITensorInfo *dst, const ScaleKernelInfo &info)
148{
149 ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
150 ARM_COMPUTE_RETURN_ERROR_ON(info.sampling_policy != SamplingPolicy::CENTER && info.sampling_policy != SamplingPolicy::TOP_LEFT);
151
152 ITensorInfo *offsets = nullptr;
153 ITensorInfo *dx = nullptr;
154 ITensorInfo *dy = nullptr;
155
156 // Get data layout and width/height indices
157 const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout;
158 const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
159 const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
160
161 // Compute the ratio between source width/height and destination width/height
162 const bool is_align_corners_used = info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(info.sampling_policy);
163 const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_width), dst->dimension(idx_width), is_align_corners_used);
164 const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_height), dst->dimension(idx_height), is_align_corners_used);
165
166 // Area interpolation behaves as Nearest Neighbour in case of up-sampling
167 InterpolationPolicy policy_to_use = (info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : info.interpolation_policy;
168
169 // Get the tensor shape of auxilary buffers
170 const TensorShape shape(dst->dimension(idx_width), dst->dimension(idx_height));
171 TensorInfo tensor_info_offsets(shape, Format::S32);
172 TensorInfo tensor_info_dx(shape, Format::F32);
173 TensorInfo tensor_info_dy(shape, Format::F32);
174 switch(policy_to_use)
175 {
176 case InterpolationPolicy::NEAREST_NEIGHBOR:
177 offsets = &tensor_info_offsets;
178 break;
179 case InterpolationPolicy::BILINEAR:
180 offsets = &tensor_info_offsets;
181 dx = &tensor_info_dx;
182 dy = &tensor_info_dy;
183 break;
184 default:
185 break;
186 }
187
188 ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuScaleKernel::validate(src->clone().get(), dx, dy, offsets, dst->clone().get(), info));
189 return Status{};
190}
191
192void CpuScale::prepare(ITensorPack &tensors)
193{
194 if(!_is_prepared)
195 {
196 _is_prepared = true;
197 const auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
198 auto dst = tensors.get_tensor(TensorType::ACL_DST);
199 auto dx = tensors.get_tensor(TensorType::ACL_INT_0);
200 auto dy = tensors.get_tensor(TensorType::ACL_INT_1);
201 auto offsets = tensors.get_tensor(TensorType::ACL_INT_2);
202
203 // Get data layout and width/height indices
Georgios Pinitas2eb5d162021-07-02 09:01:49 +0100204 const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
205 const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
Manuel Bottini10b38262021-02-19 18:16:44 +0000206
207 // Compute the ratio between source width/height and destination width/height
208 const bool is_align_corners_used = _scale_info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(_scale_info.sampling_policy);
209 const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->info()->dimension(idx_width), dst->info()->dimension(idx_width), is_align_corners_used);
210 const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->info()->dimension(idx_height), dst->info()->dimension(idx_height), is_align_corners_used);
211
212 // Area interpolation behaves as Nearest Neighbour in case of up-sampling
213 InterpolationPolicy policy_to_use = (_scale_info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f
214 && hr <= 1.f) ?
215 InterpolationPolicy::NEAREST_NEIGHBOR :
216 _scale_info.interpolation_policy;
217 const SamplingPolicy sampling_policy = _scale_info.sampling_policy;
218
219 switch(policy_to_use)
220 {
221 case InterpolationPolicy::NEAREST_NEIGHBOR:
222 {
223 // Pre-compute offsets for nearest interpolation
224 precompute_dx_dy_offsets(nullptr, nullptr, offsets, wr, hr, sampling_policy, is_align_corners_used);
225 break;
226 }
227 case InterpolationPolicy::BILINEAR:
228 {
229 // Pre-compute dx, dy and offsets for bilinear interpolation
230 precompute_dx_dy_offsets(dx, dy, offsets, wr, hr, sampling_policy, is_align_corners_used);
231 break;
232 }
233 case InterpolationPolicy::AREA:
234 {
235 break;
236 }
237 default:
238 ARM_COMPUTE_ERROR("Unsupported interpolation mode");
239 }
240 }
241}
242
243void CpuScale::run(ITensorPack &tensors)
244{
245 ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided");
246 prepare(tensors);
247 NEScheduler::get().schedule_op(_kernel.get(), Window::DimY, _kernel->window(), tensors);
248}
249} // namespace cpu
250} // namespace arm_compute