[ti-machine-learning/ti-machine-learning.git] / src / common / cnn / timlCNNClassifyAccuracyTeamModeOpenMP.c
1 /*****************************************************************************/
2 /*!
3 * \file timlCNNClassifyAccuracyTeamModeOpenMP.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
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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 Batch classification
51 * \param[in,out] cnnTeam CNN team
52 * \param[in] teamNum CNN team number
53 * \param[in] data Data batch
54 * \param[in] dataDim Data dimension
55 * \param[in] num Data number
56 * \param[out] label Label array ptr
57 * \param[out] labelDim Label dimension
58 * \param[out] success Number of successful classification
59 * \return Error code
60 */
61 /******************************************************************************/
63 int timlCNNClassifyAccuracyTeamModeOpenMP(timlConvNeuralNetwork **cnnTeam, int teamNum, float *image, int row, int col, int channel, int *label, int labelRow, int labelCol, int num, int *success)
64 {
65 int i;
66 int batchSize;
67 int batchNum;
68 int err;
69 int successLocal;
70 int thread;
71 int t;
72 int dataDim;
73 int labelDim;
74 timlConvNeuralNetwork *cnn;
76 cnn = cnnTeam[0];
77 err = 0;
78 successLocal = 0;
79 batchSize = cnn->params.batchSize;
80 batchNum = num/batchSize;
81 dataDim = row*col*channel;
82 labelDim = labelRow*labelCol;
85 if (cnn->tail->type != CNN_Accuracy) {
86 return ERROR_CNN_CLASS;
87 }
89 thread = omp_get_max_threads();
90 if (thread > teamNum) { // more thread than cnn copies
91 thread = teamNum;
92 }
94 #pragma omp parallel num_threads(thread) private(t, i, err)
95 {
96 #pragma omp for reduction(+:successLocal)
97 for (i = 0; i < batchNum; i++) {
98 t = omp_get_thread_num(); // get thread id
99 err = timlCNNLoadImage(cnnTeam[t], image + i*dataDim*batchSize, row, col, channel, batchSize);
100 err = timlCNNLoadLabel(cnnTeam[t], label + i*labelDim*batchSize, labelRow, labelCol, batchSize);
101 err = timlCNNForwardPropagation(cnnTeam[t]);
102 successLocal += cnnTeam[t]->tail->accuracyParams.success;
103 }
104 }
106 *success = successLocal;
107 return err;
108 }