[ti-machine-learning/ti-machine-learning.git] / debian / ti-timl / usr / src / timl / src / common / cnn / timlCNNLinearInitialize.c
1 /******************************************************************************/
2 /*!
3 * \file timlCNNLinearInitialize.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 linear layer
51 * \param[in] layer Layer ptr
52 * \return Error code
53 */
54 /******************************************************************************/
56 int timlCNNLinearInitialize(timlCNNLayer *layer)
57 {
58 int prevDim;
59 int dim;
60 timlConvNeuralNetwork *cnn;
62 prevDim = layer->linearParams.prevDim;
63 dim = layer->linearParams.dim;
64 cnn = layer->cnn;
66 // common to level 1, 2, 3
67 if (layer->linearParams.shared == false) {
68 // allocate weight
69 if (timlUtilMalloc((void**) &(layer->linearParams.weight), sizeof(float)*prevDim*dim) != 0) {
70 return ERROR_CNN_LAYER_ALLOCATION;
71 }
72 // allocate bias
73 if (timlUtilMalloc((void**) &(layer->linearParams.bias), sizeof(float)*dim) != 0) {
74 return ERROR_CNN_LAYER_ALLOCATION;
75 }
76 }
78 // level 1
79 if (layer->allocatorLevel == Util_AllocatorLevel1) {
80 // allocate feature map
81 if (timlUtilMalloc((void**) &(layer->featureMap), sizeof(float)*dim) != 0) {
82 return ERROR_CNN_LAYER_ALLOCATION;
83 }
85 // allocate feature map delta
86 if (timlUtilMalloc((void**) &(layer->delta), sizeof(float)*dim) != 0) {
87 return ERROR_CNN_LAYER_ALLOCATION;
88 }
90 if (layer->linearParams.shared == false) {
91 // allocate weightInc
92 if (timlUtilMalloc((void**) &(layer->linearParams.weightInc), sizeof(float)*prevDim*dim) != 0) {
93 return ERROR_CNN_LAYER_ALLOCATION;
94 }
96 // allocate weight GradAccum
97 if (timlUtilMalloc((void**) &(layer->linearParams.weightGradAccum), sizeof(float)*prevDim*dim) != 0) {
98 return ERROR_CNN_LAYER_ALLOCATION;
99 }
101 // allocate biasGradAccum
102 if (timlUtilMalloc((void**) &(layer->linearParams.biasGradAccum), sizeof(float)*dim) != 0) {
103 return ERROR_CNN_LAYER_ALLOCATION;
104 }
106 // allocate biasInc
107 if (timlUtilMalloc((void**) &(layer->linearParams.biasInc), sizeof(float)*dim) != 0) {
108 return ERROR_CNN_LAYER_ALLOCATION;
109 }
110 }
111 }
113 // level 2
114 if (layer->allocatorLevel == Util_AllocatorLevel2) {
115 // allocate feature map
116 if (timlUtilMalloc((void**) &(layer->featureMap), sizeof(float)*dim) != 0) {
117 return ERROR_CNN_LAYER_ALLOCATION;
118 }
119 }
121 // level 3
122 if (layer->allocatorLevel == Util_AllocatorLevel3) {
123 if (layer->id%2 == 0) { // layer 2, 4, 6 8, ... allocate at the back end
124 layer->featureMap = cnn->memPool + cnn->memPoolSize - layer->channel*layer->row*layer->col;
125 }
126 else { // layer 1, 3, 5, ... allocate at the front end
127 layer->featureMap = cnn->memPool;
128 }
129 }
131 return 0;
132 }