1 /*****************************************************************************/
2 /*!
3 * \file timlCNNClassifyTopNBatchMode.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,
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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] cnn CNN
52 * \param[in] data Data batch
53 * \param[in] dim Data dimension
54 * \param[in] num Data number
55 * \param[out] label Label array ptr, size = num*topN
56 * \param[out] percent Percent array ptr, size = num*topN
57 * \param[out] topN Output the top N labels and the corresponding percentage
58 * \return Error code
59 */
60 /******************************************************************************/
62 int timlCNNClassifyTopNBatchMode(timlConvNeuralNetwork *cnn, float *data, int dim, int num, int *label, float *percent, int topN)
63 {
64 int i;
65 int j;
66 int t;
67 int k;
68 int outputDim;
69 int *index;
70 int err;
72 err = 0;
73 outputDim = cnn->tail->row*cnn->tail->col*cnn->tail->channel;
74 index = malloc(sizeof(int)*outputDim); // multiple copies for each thread
76 for (j = 0; j < num; j++) {
77 err = timlCNNForwardPropagation(cnn, data + j*dim, dim); // fp
78 if (err) return err;
79 err = timlUtilVectorSortIndexFloat(cnn->tail->featureMap, index, outputDim); // sort
80 if (err) return err;
81 for (i = 0; i < topN; i++) {
82 label[j*topN + i] = index[outputDim - i - 1]; // record label
83 if (percent != NULL) {
84 timlUtilBLASscopy(1, cnn->tail->featureMap + index[outputDim - i - 1], percent + j*topN + i, cnn->deviceId, cnn->threadId);
85 }
86 }
87 }
88 free(index);
90 return err;
91 }