[ti-machine-learning/ti-machine-learning.git] / debian / ti-timl / usr / src / timl / src / common / cnn / timlCNNNormInitialize.c
1 /******************************************************************************/
2 /*!
3 * \file timlCNNNormInitialize.c
4 */
5 /* Copyright (C) 2015 Texas Instruments Incorporated - http://www.ti.com/
6 *
7 * Redistribution and use in source and binary forms, with or without
8 * modification, are permitted provided that the following conditions
9 * are met:
10 *
11 * Redistributions of source code must retain the above copyright
12 * notice, this list of conditions and the following disclaimer.
13 *
14 * Redistributions in binary form must reproduce the above copyright
15 * notice, this list of conditions and the following disclaimer in the
16 * documentation and/or other materials provided with the
17 * distribution.
18 *
19 * Neither the name of Texas Instruments Incorporated nor the names of
20 * its contributors may be used to endorse or promote products derived
21 * from this software without specific prior written permission.
22 *
23 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
24 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
25 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
26 * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
27 * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
28 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
29 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
30 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
31 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
32 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
33 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
34 *
35 ******************************************************************************/
38 /*******************************************************************************
39 *
40 * INCLUDES
41 *
42 ******************************************************************************/
44 #include "../api/timl.h"
47 /******************************************************************************/
48 /*!
49 * \ingroup cnn
50 * \brief Initialize the norm layer
51 * \param[in] layer Layer ptr
52 * \return Error code
53 */
54 /******************************************************************************/
56 int timlCNNNormInitialize(timlCNNLayer *layer)
57 {
58 timlConvNeuralNetwork *cnn = layer->cnn;
60 // allocate denom
61 if (timlUtilMalloc((void**) &(layer->normParams.denom), sizeof(float)*layer->row*layer->col*layer->channel) != 0) {
62 return ERROR_CNN_LAYER_ALLOCATION;
63 }
65 if (layer->allocatorLevel == Util_AllocatorLevel1) {
66 // allocate feature map
67 if (timlUtilMalloc((void**) &(layer->featureMap), sizeof(float)*layer->row*layer->col*layer->channel) != 0) {
68 return ERROR_CNN_LAYER_ALLOCATION;
69 }
71 // allocate delta
72 if (timlUtilMalloc((void**) &(layer->delta), sizeof(float)*layer->row*layer->col*layer->channel) != 0) {
73 return ERROR_CNN_LAYER_ALLOCATION;
74 }
75 }
77 if (layer->allocatorLevel == Util_AllocatorLevel2) {
78 // allocate feature map
79 if (timlUtilMalloc((void**) &(layer->featureMap), sizeof(float)*layer->row*layer->col*layer->channel) != 0) {
80 return ERROR_CNN_LAYER_ALLOCATION;
81 }
82 }
84 if (layer->allocatorLevel == Util_AllocatorLevel3) {
85 if (layer->id%2 == 0) { // layer 2, 4, 6 8, ... allocate at the back end
86 layer->featureMap = cnn->memPool + cnn->memPoolSize - layer->channel*layer->row*layer->col;
87 }
88 else { // layer 1, 3, 5, ... allocate at the front end
89 layer->featureMap = cnn->memPool;
90 }
91 }
93 return 0;
94 }