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 "ConvertFullyConnectedWeights.h"
25
26 namespace arm_compute
27 {
28 namespace test
29 {
30 namespace validation
31 {
32 namespace reference
33 {
34 template <typename T>
convert_fully_connected_weights(const SimpleTensor<T> & src,const TensorShape & original_input_shape,const DataLayout training_data_layout)35 SimpleTensor<T> convert_fully_connected_weights(const SimpleTensor<T> &src, const TensorShape &original_input_shape, const DataLayout training_data_layout)
36 {
37 SimpleTensor<T> dst(src.shape(), src.data_type());
38
39 const DataLayout original_input_data_layout = (training_data_layout == DataLayout::NCHW) ? DataLayout::NHWC : DataLayout::NCHW;
40
41 const int width_idx = get_data_layout_dimension_index(original_input_data_layout, DataLayoutDimension::WIDTH);
42 const int height_idx = get_data_layout_dimension_index(original_input_data_layout, DataLayoutDimension::HEIGHT);
43 const int channel_idx = get_data_layout_dimension_index(original_input_data_layout, DataLayoutDimension::CHANNEL);
44
45 const bool is_nchw_to_nhwc = training_data_layout == DataLayout::NCHW;
46 const unsigned int num_elems_per_input_plane = original_input_shape[width_idx] * original_input_shape[height_idx];
47 const unsigned int num_channels = original_input_shape[channel_idx];
48 const unsigned int factor_1 = is_nchw_to_nhwc ? num_elems_per_input_plane : num_channels;
49 const unsigned int factor_2 = is_nchw_to_nhwc ? num_channels : num_elems_per_input_plane;
50
51 const uint32_t num_elements = src.num_elements();
52 #if defined(_OPENMP)
53 #pragma omp parallel for
54 #endif /* _OPENMP */
55 for(uint32_t i = 0; i < num_elements; ++i)
56 {
57 const Coordinates coords_in = index2coords(src.shape(), i);
58 const Coordinates coords_out(coords_in.x(), coords_in.y() % factor_1 * factor_2 + coords_in.y() / factor_1);
59
60 dst[coords2index(dst.shape(), coords_out)] = src[i];
61 }
62
63 return dst;
64 }
65
66 template SimpleTensor<uint8_t> convert_fully_connected_weights(const SimpleTensor<uint8_t> &src, const TensorShape &original_input_shape,
67 const DataLayout training_data_layout);
68 template SimpleTensor<half> convert_fully_connected_weights(const SimpleTensor<half> &src, const TensorShape &original_input_shape,
69 const DataLayout training_data_layout);
70 template SimpleTensor<float> convert_fully_connected_weights(const SimpleTensor<float> &src, const TensorShape &original_input_shape,
71 const DataLayout training_data_layout);
72 } // namespace reference
73 } // namespace validation
74 } // namespace test
75 } // namespace arm_compute
76