blob: e27846c726ca18f9e3f9b80f879042bee351a618 [file] [log] [blame]
Giorgio Arena657bdb32018-04-26 18:52:01 +01001/*
2 * Copyright (c) 2018 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
26namespace arm_compute
27{
28namespace test
29{
30namespace validation
31{
32namespace reference
33{
34template <typename T>
35SimpleTensor<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
Georgios Pinitas7d66a8e2018-07-17 12:28:42 +010039 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
Giorgio Arena657bdb32018-04-26 18:52:01 +010045 const bool is_nchw_to_nhwc = training_data_layout == DataLayout::NCHW;
Georgios Pinitas7d66a8e2018-07-17 12:28:42 +010046 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];
Giorgio Arena657bdb32018-04-26 18:52:01 +010048 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 for(int i = 0; i < src.num_elements(); ++i)
52 {
53 const Coordinates coords_in = index2coords(src.shape(), i);
54 const Coordinates coords_out(coords_in.x(), coords_in.y() % factor_1 * factor_2 + coords_in.y() / factor_1);
55
56 dst[coords2index(dst.shape(), coords_out)] = src[i];
57 }
58
59 return dst;
60}
61
62template SimpleTensor<uint8_t> convert_fully_connected_weights(const SimpleTensor<uint8_t> &src, const TensorShape &original_input_shape,
63 const DataLayout training_data_layout);
64template SimpleTensor<half> convert_fully_connected_weights(const SimpleTensor<half> &src, const TensorShape &original_input_shape,
65 const DataLayout training_data_layout);
66template SimpleTensor<float> convert_fully_connected_weights(const SimpleTensor<float> &src, const TensorShape &original_input_shape,
67 const DataLayout training_data_layout);
68} // namespace reference
69} // namespace validation
70} // namespace test
71} // namespace arm_compute