1 /******************************************************************************/\r
2 /*!\r
3 * \file timlCNNForwardPropagation.c\r
4 */\r
5 /* Copyright (C) 2015 Texas Instruments Incorporated - http://www.ti.com/\r
6 *\r
7 * Redistribution and use in source and binary forms, with or without\r
8 * modification, are permitted provided that the following conditions\r
9 * are met:\r
10 *\r
11 * Redistributions of source code must retain the above copyright\r
12 * notice, this list of conditions and the following disclaimer.\r
13 *\r
14 * Redistributions in binary form must reproduce the above copyright\r
15 * notice, this list of conditions and the following disclaimer in the\r
16 * documentation and/or other materials provided with the\r
17 * distribution.\r
18 *\r
19 * Neither the name of Texas Instruments Incorporated nor the names of\r
20 * its contributors may be used to endorse or promote products derived\r
21 * from this software without specific prior written permission.\r
22 *\r
23 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS\r
24 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT\r
25 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR\r
26 * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT\r
27 * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,\r
28 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT\r
29 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,\r
30 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY\r
31 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\r
32 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\r
33 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\r
34 *\r
35 ******************************************************************************/\r
36 \r
37 \r
38 /*******************************************************************************\r
39 *\r
40 * INCLUDES\r
41 *\r
42 ******************************************************************************/\r
43 \r
44 #include "../api/timl.h"\r
45 \r
46 /******************************************************************************/\r
47 /*!\r
48 * \ingroup cnn\r
49 * \brief Forward propagate data to the CNN\r
50 * \param[in,out] cnn\r
51 * \param[in] data Data ptr\r
52 * \param[in] dim Data dimension\r
53 * \return Error code\r
54 */\r
55 /******************************************************************************/\r
56 \r
57 int timlCNNForwardPropagation(timlConvNeuralNetwork *cnn)\r
58 {\r
59 int err;\r
60 timlCNNLayer *layer;\r
61 char str[100];\r
62 FILE *fp;\r
63 \r
64 err = 0;\r
65 if (cnn == NULL) {\r
66 return ERROR_CNN_NULL_PTR;\r
67 }\r
68 layer = cnn->head;\r
69 err = timlCNNInputForwardPropagation(layer);\r
70 \r
71 \r
72 \r
73 while (layer->next != NULL) {\r
74 // sprintf(str, "gpu_level_%d_layer_%d_fm", layer->allocatorLevel, layer->id);\r
75 // fp = fopen(str, "w");\r
76 // timlUtilFwrite(layer->featureMap, sizeof(float), layer->row*layer->col*layer->channel*layer->maxBatchSize, fp);\r
77 // fclose(fp);\r
78 switch (layer->next->type) {\r
79 case CNN_Accuracy:\r
80 err = timlCNNAccuracyForwardPropagation(layer);\r
81 if (err) return err;\r
82 break;\r
83 case CNN_Conv:\r
84 err = timlCNNConvForwardPropagation(layer);\r
85 if (err) return err;\r
86 break;\r
87 case CNN_Norm:\r
88 err = timlCNNNormForwardPropagation(layer);\r
89 if (err) return err;\r
90 break;\r
91 case CNN_Pooling:\r
92 err = timlCNNPoolingForwardPropagation(layer);\r
93 if (err) return err;\r
94 break;\r
95 case CNN_Linear:\r
96 err = timlCNNLinearForwardPropagation(layer);\r
97 if (err) return err;\r
98 break;\r
99 case CNN_Nonlinear:\r
100 err = timlCNNNonlinearForwardPropagation(layer);\r
101 break;\r
102 case CNN_Dropout:\r
103 err = timlCNNDropoutForwardPropagation(layer);\r
104 if (err) return err;\r
105 break;\r
106 case CNN_SoftmaxCost:\r
107 err = timlCNNSoftmaxCostForwardPropagation(layer);\r
108 if (err) return err;\r
109 break;\r
110 case CNN_Softmax:\r
111 err = timlCNNSoftmaxForwardPropagation(layer);\r
112 if (err) return err;\r
113 break;\r
114 default:\r
115 break;\r
116 }\r
117 layer = layer->next;\r
118 \r
119 }\r
120 \r
121 // sprintf(str, "gpu_level_%d_layer_%d_fm", layer->allocatorLevel, layer->id);\r
122 // fp = fopen(str, "w");\r
123 // timlUtilFwrite(layer->featureMap, sizeof(float), layer->row*layer->col*layer->channel*layer->maxBatchSize, fp);\r
124 // fclose(fp);\r
125 \r
126 return err;\r
127 }\r