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
|
/*
* Copyright (c) 2018, 2023 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 "BatchToSpaceLayer.h"
#include "arm_compute/core/Validate.h"
#include "tests/validation/Helpers.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
// Batch to Space
template <typename T>
SimpleTensor<T> batch_to_space(const SimpleTensor<T> &src, const std::vector<int32_t> &block_shape, const CropInfo &crop_info, const TensorShape &dst_shape)
{
ARM_COMPUTE_ERROR_ON(block_shape[0] < 1);
ARM_COMPUTE_ERROR_ON(block_shape[1] < 1);
const auto expected_dst_shape = misc::shape_calculator::compute_batch_to_space_shape(DataLayout::NCHW, src.shape(), block_shape[0], block_shape[1], crop_info);
ARM_COMPUTE_ERROR_ON(arm_compute::detail::have_different_dimensions(expected_dst_shape, dst_shape, 0));
ARM_COMPUTE_UNUSED(expected_dst_shape);
SimpleTensor<T> result(dst_shape, src.data_type());
int out_pos = 0;
const auto width_out = static_cast<int>(dst_shape[0]);
const auto height_out = static_cast<int>(dst_shape[1]);
const auto z_out = static_cast<int>(dst_shape[2]);
const auto batch_out = static_cast<int>(dst_shape[3]);
for(int batch = 0; batch < batch_out; ++batch)
{
for(int z = 0; z < z_out; ++z)
{
for(int y = 0; y < height_out; ++y)
{
for(int x = 0; x < width_out; ++x)
{
const int x_c = x + crop_info.left;
const int y_c = y + crop_info.top;
const int in_batch = batch + ((x_c % block_shape[0]) + (y_c % block_shape[1]) * (block_shape[0])) * dst_shape[3];
const int in_x = x_c / block_shape[0];
const int in_y = y_c / block_shape[1];
const int in_pos = in_x + src.shape()[0] * in_y + z * src.shape()[0] * src.shape()[1] + in_batch * src.shape()[0] * src.shape()[1] * src.shape()[2];
result[out_pos] = src[in_pos];
++out_pos;
}
}
}
}
return result;
}
template SimpleTensor<float> batch_to_space(const SimpleTensor<float> &src, const std::vector<int32_t> &block_shape, const CropInfo &crop_info, const TensorShape &dst_shape);
template SimpleTensor<half> batch_to_space(const SimpleTensor<half> &src, const std::vector<int32_t> &block_shape, const CropInfo &crop_info, const TensorShape &dst_shape);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
|
