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 "UpsampleLayer.h"
25
26 #include "support/Requires.h"
27 #include "tests/validation/Helpers.h"
28
29 namespace arm_compute
30 {
31 namespace test
32 {
33 namespace validation
34 {
35 namespace reference
36 {
37 template <typename T>
upsample_layer(const SimpleTensor<T> & src,const Size2D & info,const InterpolationPolicy policy)38 SimpleTensor<T> upsample_layer(const SimpleTensor<T> &src, const Size2D &info, const InterpolationPolicy policy)
39 {
40 ARM_COMPUTE_ERROR_ON(policy != InterpolationPolicy::NEAREST_NEIGHBOR);
41 ARM_COMPUTE_UNUSED(policy);
42
43 TensorShape output_shape = src.shape();
44 output_shape.set(0, src.shape().x() * info.x());
45 output_shape.set(1, src.shape().y() * info.y());
46
47 // Create reference
48 const int stride_x = info.x();
49 const int stride_y = info.y();
50 int width_out = output_shape.x();
51 int height_out = output_shape.y();
52 SimpleTensor<T> out{ output_shape, src.data_type(), 1, src.quantization_info() };
53
54 const int width_in = src.shape().x();
55 const int height_in = src.shape().y();
56 const int num_2d_slices = src.shape().total_size() / (width_in * height_in);
57
58 for(int slice = 0; slice < num_2d_slices; ++slice)
59 {
60 const int offset_slice_in = slice * width_in * height_in;
61 const int offset_slice_out = slice * height_out * width_out;
62 for(int y = 0; y < height_out; ++y)
63 {
64 for(int x = 0; x < width_out; ++x)
65 {
66 const int out_offset = y * width_out + x;
67 const int in_offset = (y / stride_y) * width_in + x / stride_x;
68
69 T *_out = out.data() + offset_slice_out + out_offset;
70 const T *in = src.data() + offset_slice_in + in_offset;
71 *_out = *in;
72 }
73 }
74 }
75 return out;
76 }
77
78 template SimpleTensor<float> upsample_layer(const SimpleTensor<float> &src,
79 const Size2D &info, const InterpolationPolicy policy);
80 template SimpleTensor<half> upsample_layer(const SimpleTensor<half> &src,
81 const Size2D &info, const InterpolationPolicy policy);
82 template SimpleTensor<uint8_t> upsample_layer(const SimpleTensor<uint8_t> &src,
83 const Size2D &info, const InterpolationPolicy policy);
84 template SimpleTensor<int8_t> upsample_layer(const SimpleTensor<int8_t> &src,
85 const Size2D &info, const InterpolationPolicy policy);
86 } // namespace reference
87 } // namespace validation
88 } // namespace test
89 } // namespace arm_compute
90