Caffe Network File : ..\..\test\testvecs\config\caffe_jacinto_models\trained\image_detection\512x512\deploy.prototxt  
Caffe Model File   : ..\..\test\testvecs\config\caffe_jacinto_models\trained\image_detection\512x512\voc0712-512x512_mobiledetnet-0.5_iter_4000.caffemodel  
TIDL Network File  : ..\..\test\testvecs\config\tidl_models\jdetnet\NET_OD.BIN  
TIDL Model File    : ..\..\test\testvecs\config\tidl_models\jdetnet\PRM_OD.BIN  
Name of the Network : mobiledetnet-0.5_deploy 
Num Inputs :               1 
Could not find detection_out Params
 Num of Layer Detected :  70 
  0, TIDL_DataLayer                , data                                      0,  -1 ,  1 ,   x ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  0 ,       0 ,       0 ,       0 ,       0 ,       1 ,       3 ,     512 ,     512 ,         0 ,
  1, TIDL_BatchNormLayer           , data/bias                                 1,   1 ,  1 ,   0 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  1 ,       1 ,       3 ,     512 ,     512 ,       1 ,       3 ,     512 ,     512 ,    786432 ,
  2, TIDL_ConvolutionLayer         , conv1                                     1,   1 ,  1 ,   1 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  2 ,       1 ,       3 ,     512 ,     512 ,       1 ,      16 ,     256 ,     256 ,  28311552 ,
  3, TIDL_ConvolutionLayer         , conv2_1/dw                                1,   1 ,  1 ,   2 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  3 ,       1 ,      16 ,     256 ,     256 ,       1 ,      16 ,     256 ,     256 ,   9437184 ,
  4, TIDL_ConvolutionLayer         , conv2_1/sep                               1,   1 ,  1 ,   3 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  4 ,       1 ,      16 ,     256 ,     256 ,       1 ,      32 ,     256 ,     256 ,  33554432 ,
  5, TIDL_ConvolutionLayer         , conv2_2/dw                                1,   1 ,  1 ,   4 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  5 ,       1 ,      32 ,     256 ,     256 ,       1 ,      32 ,     128 ,     128 ,   4718592 ,
  6, TIDL_ConvolutionLayer         , conv2_2/sep                               1,   1 ,  1 ,   5 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  6 ,       1 ,      32 ,     128 ,     128 ,       1 ,      64 ,     128 ,     128 ,  33554432 ,
  7, TIDL_ConvolutionLayer         , conv3_1/dw                                1,   1 ,  1 ,   6 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  7 ,       1 ,      64 ,     128 ,     128 ,       1 ,      64 ,     128 ,     128 ,   9437184 ,
  8, TIDL_ConvolutionLayer         , conv3_1/sep                               1,   1 ,  1 ,   7 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  8 ,       1 ,      64 ,     128 ,     128 ,       1 ,      64 ,     128 ,     128 ,  67108864 ,
  9, TIDL_ConvolutionLayer         , conv3_2/dw                                1,   1 ,  1 ,   8 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  9 ,       1 ,      64 ,     128 ,     128 ,       1 ,      64 ,      64 ,      64 ,   2359296 ,
 10, TIDL_ConvolutionLayer         , conv3_2/sep                               1,   1 ,  1 ,   9 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 10 ,       1 ,      64 ,      64 ,      64 ,       1 ,     128 ,      64 ,      64 ,  33554432 ,
 11, TIDL_ConvolutionLayer         , conv4_1/dw                                1,   1 ,  1 ,  10 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 11 ,       1 ,     128 ,      64 ,      64 ,       1 ,     128 ,      64 ,      64 ,   4718592 ,
 12, TIDL_ConvolutionLayer         , conv4_1/sep                               1,   1 ,  1 ,  11 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 12 ,       1 ,     128 ,      64 ,      64 ,       1 ,     128 ,      64 ,      64 ,  67108864 ,
 13, TIDL_ConvolutionLayer         , conv4_2/dw                                1,   1 ,  1 ,  12 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 13 ,       1 ,     128 ,      64 ,      64 ,       1 ,     128 ,      32 ,      32 ,   1179648 ,
 14, TIDL_ConvolutionLayer         , conv4_2/sep                               1,   1 ,  1 ,  13 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 14 ,       1 ,     128 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,  33554432 ,
 15, TIDL_ConvolutionLayer         , conv5_1/dw                                1,   1 ,  1 ,  14 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 15 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,   2359296 ,
 16, TIDL_ConvolutionLayer         , conv5_1/sep                               1,   1 ,  1 ,  15 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 16 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,  67108864 ,
 17, TIDL_ConvolutionLayer         , conv5_2/dw                                1,   1 ,  1 ,  16 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 17 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,   2359296 ,
 18, TIDL_ConvolutionLayer         , conv5_2/sep                               1,   1 ,  1 ,  17 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 18 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,  67108864 ,
 19, TIDL_ConvolutionLayer         , conv5_3/dw                                1,   1 ,  1 ,  18 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 19 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,   2359296 ,
 20, TIDL_ConvolutionLayer         , conv5_3/sep                               1,   1 ,  1 ,  19 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 20 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,  67108864 ,
 21, TIDL_ConvolutionLayer         , conv5_4/dw                                1,   1 ,  1 ,  20 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 21 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,   2359296 ,
 22, TIDL_ConvolutionLayer         , conv5_4/sep                               2,   1 ,  1 ,  21 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 22 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,  67108864 ,
 23, TIDL_ConvolutionLayer         , conv5_5/dw                                1,   1 ,  1 ,  22 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 23 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,   2359296 ,
 24, TIDL_ConvolutionLayer         , conv5_5/sep                               2,   1 ,  1 ,  23 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 24 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,  67108864 ,
 25, TIDL_ConvolutionLayer         , conv5_6/dw                                1,   1 ,  1 ,  24 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 25 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      16 ,      16 ,    589824 ,
 26, TIDL_ConvolutionLayer         , conv5_6/sep                               2,   1 ,  1 ,  25 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 26 ,       1 ,     256 ,      16 ,      16 ,       1 ,     512 ,      16 ,      16 ,  33554432 ,
 27, TIDL_ConvolutionLayer         , conv6/dw                                  1,   1 ,  1 ,  26 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 27 ,       1 ,     512 ,      16 ,      16 ,       1 ,     512 ,      16 ,      16 ,   1179648 ,
 28, TIDL_ConvolutionLayer         , conv6/sep                                 2,   1 ,  1 ,  27 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 28 ,       1 ,     512 ,      16 ,      16 ,       1 ,     512 ,      16 ,      16 ,  67108864 ,
 29, TIDL_PoolingLayer             , pool6                                     1,   1 ,  1 ,  28 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 29 ,       1 ,     512 ,      16 ,      16 ,       1 ,     512 ,       8 ,       8 ,    131072 ,
 30, TIDL_PoolingLayer             , pool7                                     2,   1 ,  1 ,  29 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 30 ,       1 ,     512 ,       8 ,       8 ,       1 ,     512 ,       4 ,       4 ,     32768 ,
 31, TIDL_PoolingLayer             , pool8                                     1,   1 ,  1 ,  30 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 31 ,       1 ,     512 ,       4 ,       4 ,       1 ,     512 ,       2 ,       2 ,      8192 ,
 32, TIDL_ConvolutionLayer         , ctx_output1/dw                            2,   1 ,  1 ,  24 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 32 ,       1 ,     256 ,      32 ,      32 ,       1 ,     256 ,      32 ,      32 ,   2359296 ,
 33, TIDL_ConvolutionLayer         , ctx_output1/sep                           1,   1 ,  1 ,  32 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 33 ,       1 ,     256 ,      32 ,      32 ,       1 ,     512 ,      32 ,      32 , 134217728 ,
 34, TIDL_ConvolutionLayer         , ctx_output2/dw                            2,   1 ,  1 ,  28 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 34 ,       1 ,     512 ,      16 ,      16 ,       1 ,     512 ,      16 ,      16 ,   1179648 ,
 35, TIDL_ConvolutionLayer         , ctx_output2/sep                           1,   1 ,  1 ,  34 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 35 ,       1 ,     512 ,      16 ,      16 ,       1 ,     512 ,      16 ,      16 ,  67108864 ,
 36, TIDL_ConvolutionLayer         , ctx_output3/dw                            2,   1 ,  1 ,  29 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 36 ,       1 ,     512 ,       8 ,       8 ,       1 ,     512 ,       8 ,       8 ,    294912 ,
 37, TIDL_ConvolutionLayer         , ctx_output3/sep                           1,   1 ,  1 ,  36 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 37 ,       1 ,     512 ,       8 ,       8 ,       1 ,     512 ,       8 ,       8 ,  16777216 ,
 38, TIDL_ConvolutionLayer         , ctx_output4/dw                            2,   1 ,  1 ,  30 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 38 ,       1 ,     512 ,       4 ,       4 ,       1 ,     512 ,       4 ,       4 ,     73728 ,
 39, TIDL_ConvolutionLayer         , ctx_output4/sep                           1,   1 ,  1 ,  38 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 39 ,       1 ,     512 ,       4 ,       4 ,       1 ,     512 ,       4 ,       4 ,   4194304 ,
 40, TIDL_ConvolutionLayer         , ctx_output5/dw                            2,   1 ,  1 ,  31 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 40 ,       1 ,     512 ,       2 ,       2 ,       1 ,     512 ,       2 ,       2 ,     18432 ,
 41, TIDL_ConvolutionLayer         , ctx_output5/sep                           2,   1 ,  1 ,  40 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 41 ,       1 ,     512 ,       2 ,       2 ,       1 ,     512 ,       2 ,       2 ,   1048576 ,
 42, TIDL_ConvolutionLayer         , ctx_output1/sep/relu_mbox_loc             2,   1 ,  1 ,  33 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 42 ,       1 ,     512 ,      32 ,      32 ,       1 ,      16 ,      32 ,      32 ,   8388608 ,
 43, TIDL_FlattenLayer             , ctx_output1/sep/relu_mbox_loc_perm        2,   1 ,  1 ,  42 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 43 ,       1 ,      16 ,      32 ,      32 ,       1 ,       1 ,       1 ,   16384 ,         1 ,
 44, TIDL_ConvolutionLayer         , ctx_output1/sep/relu_mbox_conf            0,   1 ,  1 ,  33 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 44 ,       1 ,     512 ,      32 ,      32 ,       1 ,      84 ,      32 ,      32 ,  44040192 ,
 45, TIDL_FlattenLayer             , ctx_output1/sep/relu_mbox_conf_perm       1,   1 ,  1 ,  44 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 45 ,       1 ,      84 ,      32 ,      32 ,       1 ,       1 ,       1 ,   86016 ,         1 ,
 47, TIDL_ConvolutionLayer         , ctx_output2/sep/relu_mbox_loc             1,   1 ,  1 ,  35 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 47 ,       1 ,     512 ,      16 ,      16 ,       1 ,      24 ,      16 ,      16 ,   3145728 ,
 48, TIDL_FlattenLayer             , ctx_output2/sep/relu_mbox_loc_perm        1,   1 ,  1 ,  47 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 48 ,       1 ,      24 ,      16 ,      16 ,       1 ,       1 ,       1 ,    6144 ,         1 ,
 49, TIDL_ConvolutionLayer         , ctx_output2/sep/relu_mbox_conf            1,   1 ,  1 ,  35 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 49 ,       1 ,     512 ,      16 ,      16 ,       1 ,     126 ,      16 ,      16 ,  16515072 ,
 50, TIDL_FlattenLayer             , ctx_output2/sep/relu_mbox_conf_perm       1,   1 ,  1 ,  49 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 50 ,       1 ,     126 ,      16 ,      16 ,       1 ,       1 ,       1 ,   32256 ,         1 ,
 52, TIDL_ConvolutionLayer         , ctx_output3/sep/relu_mbox_loc             1,   1 ,  1 ,  37 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 52 ,       1 ,     512         1 file(s) copied.

Processing config file .\tempDir\qunat_stats_config.txt !
  0, TIDL_DataLayer                ,  0,  -1 ,  1 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  0 ,    0 ,    0 ,    0 ,    0 ,    1 ,    3 ,  512 ,  512 ,
  1, TIDL_BatchNormLayer           ,  1,   1 ,  1 ,  0 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  1 ,    1 ,    3 ,  512 ,  512 ,    1 ,    3 ,  512 ,  512 ,
  2, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  1 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  2 ,    1 ,    3 ,  512 ,  512 ,    1 ,   16 ,  256 ,  256 ,
  3, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  2 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  3 ,    1 ,   16 ,  256 ,  256 ,    1 ,   16 ,  256 ,  256 ,
  4, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  3 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  4 ,    1 ,   16 ,  256 ,  256 ,    1 ,   32 ,  256 ,  256 ,
  5, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  4 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  5 ,    1 ,   32 ,  256 ,  256 ,    1 ,   32 ,  128 ,  128 ,
  6, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  5 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  6 ,    1 ,   32 ,  128 ,  128 ,    1 ,   64 ,  128 ,  128 ,
  7, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  6 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  7 ,    1 ,   64 ,  128 ,  128 ,    1 ,   64 ,  128 ,  128 ,
  8, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  7 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  8 ,    1 ,   64 ,  128 ,  128 ,    1 ,   64 ,  128 ,  128 ,
  9, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  8 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  9 ,    1 ,   64 ,  128 ,  128 ,    1 ,   64 ,   64 ,   64 ,
 10, TIDL_ConvolutionLayer         ,  1,   1 ,  1 ,  9 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 10 ,    1 ,   64 ,   64 ,   64 ,    1 ,  128 ,   64 ,   64 ,
 11, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 10 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 11 ,    1 ,  128 ,   64 ,   64 ,    1 ,  128 ,   64 ,   64 ,
 12, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 11 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 12 ,    1 ,  128 ,   64 ,   64 ,    1 ,  128 ,   64 ,   64 ,
 13, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 12 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 13 ,    1 ,  128 ,   64 ,   64 ,    1 ,  128 ,   32 ,   32 ,
 14, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 13 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 14 ,    1 ,  128 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 15, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 14 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 15 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 16, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 15 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 16 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 17, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 16 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 17 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 18, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 17 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 18 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 19, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 18 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 19 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 20, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 19 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 20 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 21, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 20 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 21 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 22, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 21 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 22 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 23, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 22 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 23 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 24, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 23 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 24 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 25, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 24 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 25 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   16 ,   16 ,
 26, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 25 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 26 ,    1 ,  256 ,   16 ,   16 ,    1 ,  512 ,   16 ,   16 ,
 27, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 26 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 27 ,    1 ,  512 ,   16 ,   16 ,    1 ,  512 ,   16 ,   16 ,
 28, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 27 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 28 ,    1 ,  512 ,   16 ,   16 ,    1 ,  512 ,   16 ,   16 ,
 29, TIDL_PoolingLayer             ,  1,   1 ,  1 , 28 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 29 ,    1 ,  512 ,   16 ,   16 ,    1 ,  512 ,    8 ,    8 ,
 30, TIDL_PoolingLayer             ,  1,   1 ,  1 , 29 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 30 ,    1 ,  512 ,    8 ,    8 ,    1 ,  512 ,    4 ,    4 ,
 31, TIDL_PoolingLayer             ,  1,   1 ,  1 , 30 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 31 ,    1 ,  512 ,    4 ,    4 ,    1 ,  512 ,    2 ,    2 ,
 32, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 24 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 32 ,    1 ,  256 ,   32 ,   32 ,    1 ,  256 ,   32 ,   32 ,
 33, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 32 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 33 ,    1 ,  256 ,   32 ,   32 ,    1 ,  512 ,   32 ,   32 ,
 34, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 28 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 34 ,    1 ,  512 ,   16 ,   16 ,    1 ,  512 ,   16 ,   16 ,
 35, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 34 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 35 ,    1 ,  512 ,   16 ,   16 ,    1 ,  512 ,   16 ,   16 ,
 36, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 29 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 36 ,    1 ,  512 ,    8 ,    8 ,    1 ,  512 ,    8 ,    8 ,
 37, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 36 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 37 ,    1 ,  512 ,    8 ,    8 ,    1 ,  512 ,    8 ,    8 ,
 38, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 30 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 38 ,    1 ,  512 ,    4 ,    4 ,    1 ,  512 ,    4 ,    4 ,
 39, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 38 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 39 ,    1 ,  512 ,    4 ,    4 ,    1 ,  512 ,    4 ,    4 ,
 40, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 31 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 40 ,    1 ,  512 ,    2 ,    2 ,    1 ,  512 ,    2 ,    2 ,
 41, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 40 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 41 ,    1 ,  512 ,    2 ,    2 ,    1 ,  512 ,    2 ,    2 ,
 42, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 33 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 42 ,    1 ,  512 ,   32 ,   32 ,    1 ,   16 ,   32 ,   32 ,
 43, TIDL_FlattenLayer             ,  1,   1 ,  1 , 42 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 43 ,    1 ,   16 ,   32 ,   32 ,    1 ,    1 ,    1 ,16384 ,
 44, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 33 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 44 ,    1 ,  512 ,   32 ,   32 ,    1 ,   84 ,   32 ,   32 ,
 45, TIDL_FlattenLayer             ,  1,   1 ,  1 , 44 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 45 ,    1 ,   84 ,   32 ,   32 ,    1 ,    1 ,    1 ,86016 ,
 46, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 35 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 47 ,    1 ,  512 ,   16 ,   16 ,    1 ,   24 ,   16 ,   16 ,
 47, TIDL_FlattenLayer             ,  1,   1 ,  1 , 47 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 48 ,    1 ,   24 ,   16 ,   16 ,    1 ,    1 ,    1 , 6144 ,
 48, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 35 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 49 ,    1 ,  512 ,   16 ,   16 ,    1 ,  126 ,   16 ,   16 ,
 49, TIDL_FlattenLayer             ,  1,   1 ,  1 , 49 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 50 ,    1 ,  126 ,   16 ,   16 ,    1 ,    1 ,    1 ,32256 ,
 50, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 37 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 52 ,    1 ,  512 ,    8 ,    8 ,    1 ,   24 ,    8 ,    8 ,
 51, TIDL_FlattenLayer             ,  1,   1 ,  1 , 52 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 53 ,    1 ,   24 ,    8 ,    8 ,    1 ,    1 ,    1 , 1536 ,
 52, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 37 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 54 ,    1 ,  512 ,    8 ,    8 ,    1 ,  126 ,    8 ,    8 ,
 53, TIDL_FlattenLayer             ,  1,   1 ,  1 , 54 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 55 ,    1 ,  126 ,    8 ,    8 ,    1 ,    1 ,    1 , 8064 ,
 54, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 39 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 57 ,    1 ,  512 ,    4 ,    4 ,    1 ,   16 ,    4 ,    4 ,
 55, TIDL_FlattenLayer             ,  1,   1 ,  1 , 57 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 58 ,    1 ,   16 ,    4 ,    4 ,    1 ,    1 ,    1 ,  256 ,
 56, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 39 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 59 ,    1 ,  512 ,    4 ,    4 ,    1 ,   84 ,    4 ,    4 ,
 57, TIDL_FlattenLayer             ,  1,   1 ,  1 , 59 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 60 ,    1 ,   84 ,    4 ,    4 ,    1 ,    1 ,    1 , 1344 ,
 58, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 41 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 62 ,    1 ,  512 ,    2 ,    2 ,    1 ,   16 ,    2 ,    2 ,
 59, TIDL_FlattenLayer             ,  1,   1 ,  1 , 62 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 63 ,    1 ,   16 ,    2 ,    2 ,    1 ,    1 ,    1 ,   64 ,
 60, TIDL_ConvolutionLayer         ,  1,   1 ,  1 , 41 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 64 ,    1 ,  512 ,    2 ,    2 ,    1 ,   84 ,    2 ,    2 ,
 61, TIDL_FlattenLayer             ,  1,   1 ,  1 , 64 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 65 ,    1 ,   84 ,    2 ,    2 ,    1 ,    1 ,    1 ,  336 ,
 62, TIDL_ConcatLayer              ,  1,   5 ,  1 , 43 , 48 , 53 , 58 , 63 ,  x ,  x ,  x , 67 ,    1 ,    1 ,    1 ,16384 ,    1 ,    1 ,    1 ,24384 ,
 63, TIDL_ConcatLayer              ,  1,   5 ,  1 , 45 , 50 , 55 , 60 , 65 ,  x ,  x ,  x , 68 ,    1 ,    1 ,    1 ,86016 ,    1 ,    1 ,    1 ,128016 ,
 64, TIDL_DetectionOutputLayer     ,  1,   2 ,  1 , 67 , 68 ,  x ,  x ,  x ,  x ,  x ,  x , 69 ,    1 ,    1 ,    1 ,24384 ,    1 ,    1 ,    1 ,  560 ,
 65, TIDL_DataLayer                ,  0,   1 , -1 , 69 ,  x ,  x ,  x ,  x ,  x ,  x ,  x ,  0 ,    1 ,    1 ,    1 ,  560 ,    0 ,    0 ,    0 ,    0 ,
Layer ID    ,inBlkWidth  ,inBlkHeight ,inBlkPitch  ,outBlkWidth ,outBlkHeight,outBlkPitch ,numInChs    ,numOutChs   ,numProcInChs,numLclInChs ,numLclOutChs,numProcItrs ,numAccItrs  ,numHorBlock ,numVerBlock ,inBlkChPitch,outBlkChPitc,alignOrNot 
      2           72           68           72           32           32           32            3           16            3            1            8            1            3            8            8         4896         1024            1    
      3           40           34           40           32           32           32            1            1            1            1            1            1            1            8            8         1360         1024            1    
      4           32           32           32           32           32           32           16           32           16            7            8            1            3            8            8         1024         1024            1    
      5           72           68           72           32           32           32            1            1            1            1            1            1            1            4            4         4896         1024            1    
      6           32           32           32           32           32           32           32           64           32            7            8            1            5            4            4         1024         1024            1    
      7           40           34           40           32           32           32            1            1            1            1            1            1            1            4            4         1360         1024            1    
      8           32           32           32           32           32           32           64           64           64            7            8            1           10            4            4         1024         1024            1    
      9           72           68           72           32           32           32            1            1            1            1            1            1            1            2            2         4896         1024            1    
     10           32           32           32           32           32           32           64          128           64            7            8            1           10            2            2         1024         1024            1    
     11           40           34           40           32           32           32            1            1            1            1            1            1            1            2            2         1360         1024            1    
     12           32           32           32           32           32           32          128          128          128            7            8            1           19            2            2         1024         1024            1    
     13           72           68           72           32           32           32            1            1            1            1            1            1            1            1            1         4896         1024            1    
     14           32           32           32           32           32           32          128          256          128            7            8            1           19            1            1         1024         1024            1    
     15           40           34           40           32           32           32            1            1            1            1            1            1            1            1            1         1360         1024            1    
     16           32           32           32           32           32           32          256          256          256            7            8            1           37            1            1         1024         1024            1    
     17           34           34           34           32           32           32            1            1            1            1            1            1            1            1            1         1156         1024            1    
     18           32            8           32           32            8           32          256          256          256           32            8            1            8            1            4          256          256            1    
     19           34           34           34           32           32           32            1            1            1            1            1            1            1            1            1         1156         1024            1    
     20           32            8           32           32            8           32          256          256          256           32            8            1            8            1            4          256          256            1    
     21           34           34           34           32           32           32            1            1            1            1            1            1            1            1            1         1156         1024            1    
     22           32            8           32           32            8           32          256          256          256           32            8            1            8            1            4          256          256            1    
     23           34           34           34           32           32           32            1            1            1            1            1            1            1            1            1         1156         1024            1    
     24           32            8           32           32            8           32          256          256          256           32            8            1            8            1            4          256          256            1    
     25           40           36           40           16           16           16            1            1            1            1            1            1            1            1            1         1440          256            1    
     26           16            8           16           16            8           16          256          512          256           32           32            1            8            1            2          128          128            1    
     27           18           18           18           16           16           16            1            1            1            1            1            1            1            1            1          324          256            1    
     28           16            8           16           16            8           16          512          512          512           32           32            1           16            1            2          128          128            1    
     32           34           34           34           32           32           32            1            1            1            1            1            1            1            1            1         1156         1024            1    
     33           32            8           32           32            8           32          256          512          256           32            8            1            8            1            4          256          256            1    
     34           18           18           18           16           16           16            1            1            1            1            1            1            1            1            1          324          256            1    
     35           16            8           16           16            8           16          512          512          512           32           32            1           16            1            2          128          128            1    
     36           10           10           10            8            8            8            1            1            1            1            1            1            1            1            1          100           64            1    
     37            8            8            8            8            8            8          512          512          512           32           32            1           16            1            1           64           64            1    
     38            6            6            6            4            4            4            1            1            1            1            1            1            1            1            1           36           16            1    
     39            4            4            4            4            4            4          512          512          512           32           32            1           16            1            1           16           16            1    
     40            4            4            4            2            2            2            1            1            1            1            1            1            1            1            1           16            4            1    
     41            2            2            2            2            2            2          512          512          512           32           32            1           16            1            1            4            4            1    
     42           32            8           32           32            8           32          512           16          512           32           16            1           16            1            4          256          256            1    
     44           32            8           32           32            8           32          512           96          512           32           16            1           16            1            4          256          256            1    
     46           16           16           16           16           16           16          512           24          512            8            8            1           64            1            1          256          256            1    
     48           16           16           16           16           16           16          512          128          512            8            8            1           64            1            1          256          256            1    
     50           16            8           16           16            8           16          512           24          512            8            8            1           64            1            1          128          128            1    
     52           16            8           16           16            8           16          512          128          512            8            8            1           64            1            1          128          128            1    
     54           16            4           16           16            4           16          512           16          512            8            8            1           64            1            1           64           64            1    
     56           16            4           16           16            4           16          512           88          512            8            8            1           64            1            1           64           64            1    
     58           16            2           16           16            2           16          512           16          512            8            8            1           64            1            1           32           32            1    
     60           16            2           16           16            2           16          512           88          512            8            8            1           64            1            1           32           32            1    

Processing Frame Number : 0 

 Layer    1 : Max PASS : -2147483648 :    64897 Out Q :      254 ,   131846, TIDL_BatchNormLayer  , PASSED  #MMACs =     0.79,     0.00,     0.79, Sparsity :   0.00, 100.00
 Layer    2 : Max PASS : -2147483648 :    46899 Out Q :     5221 ,    47083, TIDL_ConvolutionLayer, PASSED  #MMACs =    28.31,     8.52,    11.01, Sparsity :  61.11,  69.91
 Layer    3 : Max PASS : -2147483648 :     3735 Out Q :    12603 ,     3750, TIDL_ConvolutionLayer, PASSED  #MMACs =     9.44,     3.28,     4.46, Sparsity :  52.78,  65.28
 Layer    4 : Max PASS : -2147483648 :    15246 Out Q :    17371 ,    15306, TIDL_ConvolutionLayer, PASSED  #MMACs =    33.55,    10.88,    20.19, Sparsity :  39.84,  67.58
 Layer    5 : Max PASS : -2147483648 :     1704 Out Q :    13361 ,     1711, TIDL_ConvolutionLayer, PASSED  #MMACs =     4.72,     3.21,     3.93, Sparsity :  16.67,  31.94
 Layer    6 : Max PASS : -2147483648 :    16359 Out Q :    19913 ,    16423, TIDL_ConvolutionLayer, PASSED  #MMACs =    33.55,    24.33,    31.00, Sparsity :   7.62,  27.49
 Layer    7 : Max PASS : -2147483648 :    13811 Out Q :     8846 ,    13865, TIDL_ConvolutionLayer, PASSED  #MMACs =     9.44,     8.68,    11.01, Sparsity : -16.67,   7.99
 Layer    8 : Max PASS : -2147483648 :    17454 Out Q :    16488 ,    17522, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,    58.20,    75.89, Sparsity : -13.09,  13.28
 Layer    9 : Max PASS : -2147483648 :    12523 Out Q :    14344 ,    12572, TIDL_ConvolutionLayer, PASSED  #MMACs =     2.36,     2.27,     2.98, Sparsity : -26.39,   3.82
 Layer   10 : Max PASS : -2147483648 :    32030 Out Q :    20993 ,    32156, TIDL_ConvolutionLayer, PASSED  #MMACs =    33.55,    29.54,    38.70, Sparsity : -15.33,  11.98
 Layer   11 : Max PASS : -2147483648 :     8532 Out Q :    13370 ,     8565, TIDL_ConvolutionLayer, PASSED  #MMACs =     4.72,     4.45,     5.49, Sparsity : -16.32,   5.64
 Layer   12 : Max PASS : -2147483648 :    39238 Out Q :    14527 ,    39392, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,    60.35,    75.38, Sparsity : -12.33,  10.08
 Layer   13 : Max PASS : -2147483648 :     2932 Out Q :    13560 ,     2943, TIDL_ConvolutionLayer, PASSED  #MMACs =     1.18,     1.14,     1.47, Sparsity : -24.65,   3.30
 Layer   14 : Max PASS : -2147483648 :    25368 Out Q :    37711 ,    25467, TIDL_ConvolutionLayer, PASSED  #MMACs =    33.55,    30.26,    37.95, Sparsity : -13.11,   9.82
 Layer   15 : Max PASS : -2147483648 :     1928 Out Q :    18037 ,     1936, TIDL_ConvolutionLayer, PASSED  #MMACs =     2.36,     1.56,     1.94, Sparsity :  17.88,  33.72
 Layer   16 : Max PASS : -2147483648 :    27031 Out Q :    43423 ,    27137, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,    61.21,    75.54, Sparsity : -12.57,   8.79
 Layer   17 : Max PASS : -2147483648 :    14375 Out Q :    21572 ,    14431, TIDL_ConvolutionLayer, PASSED  #MMACs =     2.36,     0.00,     2.36, Sparsity :   0.00, 100.00
 Layer   18 : Max PASS : -2147483648 :   126725 Out Q :    11995 ,   127222, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,     0.00,    67.11, Sparsity :   0.00, 100.00
 Layer   19 : Max PASS : -2147483648 :     3005 Out Q :    19140 ,     3017, TIDL_ConvolutionLayer, PASSED  #MMACs =     2.36,     0.00,     2.36, Sparsity :   0.00, 100.00
 Layer   20 : Max PASS : -2147483648 :    30728 Out Q :    47853 ,    30849, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,     0.00,    67.11, Sparsity :   0.00, 100.00
 Layer   21 : Max PASS : -2147483648 :     5720 Out Q :    19451 ,     5742, TIDL_ConvolutionLayer, PASSED  #MMACs =     2.36,     0.00,     2.36, Sparsity :   0.00, 100.00
 Layer   22 : Max PASS : -2147483648 :    63443 Out Q :    19249 ,    63692, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,     0.00,    67.11, Sparsity :   0.00, 100.00
 Layer   23 : Max PASS : -2147483648 :    10367 Out Q :    15606 ,    10408, TIDL_ConvolutionLayer, PASSED  #MMACs =     2.36,     0.00,     2.36, Sparsity :   0.00, 100.00
 Layer   24 : Max PASS : -2147483648 :    27749 Out Q :    50035 ,    27858, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,     0.00,    67.11, Sparsity :   0.00, 100.00
 Layer   25 : Max PASS : -2147483648 :     8425 Out Q :    23349 ,     8458, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.59,     0.57,     0.75, Sparsity : -26.91,   2.73
 Layer   26 : Max PASS : -2147483648 :    25143 Out Q :    73897 ,    25242, TIDL_ConvolutionLayer, PASSED  #MMACs =    33.55,     0.00,    33.55, Sparsity :   0.00, 100.00
 Layer   27 : Max PASS : -2147483648 :    11147 Out Q :    29708 ,    11191, TIDL_ConvolutionLayer, PASSED  #MMACs =     1.18,     0.00,     1.18, Sparsity :   0.00, 100.00
 Layer   28 : Max PASS : -2147483648 :    23158 Out Q :     9720 ,    23249, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,     0.00,    67.11, Sparsity :   0.00, 100.00
 Layer   29 :TIDL_PoolingLayer,     PASSED  #MMACs =     0.03,     0.00,     0.03, Sparsity :   0.00, 100.00
 Layer   30 :TIDL_PoolingLayer,     PASSED  #MMACs =     0.01,     0.00,     0.01, Sparsity :   0.00, 100.00
 Layer   31 :TIDL_PoolingLayer,     PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :   0.00, 100.00
 Layer   32 : Max PASS : -2147483648 :     1006 Out Q :     6787 ,     1010, TIDL_ConvolutionLayer, PASSED  #MMACs =     2.36,     0.00,     2.36, Sparsity :   0.00, 100.00
 Layer   33 : Max PASS : -2147483648 :    35661 Out Q :    11838 ,    35801, TIDL_ConvolutionLayer, PASSED  #MMACs =   134.22,     0.00,   134.22, Sparsity :   0.00, 100.00
 Layer   34 : Max PASS : -2147483648 :    10888 Out Q :    15735 ,    10931, TIDL_ConvolutionLayer, PASSED  #MMACs =     1.18,     0.00,     1.18, Sparsity :   0.00, 100.00
 Layer   35 : Max PASS : -2147483648 :    68713 Out Q :    19296 ,    68982, TIDL_ConvolutionLayer, PASSED  #MMACs =    67.11,     0.00,    67.11, Sparsity :   0.00, 100.00
 Layer   36 : Max PASS : -2147483648 :    11597 Out Q :    17934 ,    11642, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.29,     0.00,     0.29, Sparsity :   0.00, 100.00
 Layer   37 : Max PASS : -2147483648 :    63379 Out Q :    22013 ,    63628, TIDL_ConvolutionLayer, PASSED  #MMACs =    16.78,     0.00,    16.78, Sparsity :   0.00, 100.00
 Layer   38 : Max PASS : -2147483648 :    18907 Out Q :    14856 ,    18981, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.07,     0.00,     0.07, Sparsity :   0.00, 100.00
 Layer   39 : Max PASS : -2147483648 :    52496 Out Q :    22721 ,    52702, TIDL_ConvolutionLayer, PASSED  #MMACs =     4.19,     0.00,     4.19, Sparsity :   0.00, 100.00
 Layer   40 : Max PASS : -2147483648 :     8120 Out Q :    32495 ,     8152, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.02,     0.00,     0.02, Sparsity :   0.00, 100.00
 Layer   41 : Max PASS : -2147483648 :    73260 Out Q :    34031 ,    73547, TIDL_ConvolutionLayer, PASSED  #MMACs =     1.05,     0.00,     1.05, Sparsity :   0.00, 100.00
 Layer   42 : Max PASS : -2147483648 :    85993 Out Q :     6573 ,   188277, TIDL_ConvolutionLayer, PASSED  #MMACs =     8.39,     0.00,     8.39, Sparsity :   0.00, 100.00
 Layer   43 :TIDL_FlattenLayer, PASSED  #MMACs =     0.02,     0.00,     0.02, Sparsity :   0.00, 100.00
 Layer   44 : Max PASS : -2147483648 :  1017846 Out Q :      461 ,  2051721, TIDL_ConvolutionLayer, PASSED  #MMACs =    44.04,     0.00,    50.33, Sparsity : -14.29, 100.00
 Layer   45 :TIDL_FlattenLayer, PASSED  #MMACs =     0.09,     0.00,     0.09, Sparsity :   0.00, 100.00
 Layer   46 : Max PASS : -2147483648 :    97578 Out Q :    11530 ,   223478, TIDL_ConvolutionLayer, PASSED  #MMACs =     3.15,     3.09,     3.15, Sparsity :   0.00,   1.69
 Layer   47 :TIDL_FlattenLayer, PASSED  #MMACs =     0.01,     0.00,     0.01, Sparsity :   0.00, 100.00
 Layer   48 : Max PASS : -2147483648 :   237822 Out Q :     4672 ,   479389, TIDL_ConvolutionLayer, PASSED  #MMACs =    16.52,    16.43,    16.78, Sparsity :  -1.59,   0.52
 Layer   49 :TIDL_FlattenLayer, PASSED  #MMACs =     0.03,     0.00,     0.03, Sparsity :   0.00, 100.00
 Layer   50 : Max PASS : -2147483648 :   104415 Out Q :    12999 ,   210474, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.79,     0.77,     0.79, Sparsity :   0.00,   2.28
 Layer   51 :TIDL_FlattenLayer, PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :   0.00, 100.00
 Layer   52 : Max PASS : -2147483648 :   245100 Out Q :     5286 ,   494060, TIDL_ConvolutionLayer, PASSED  #MMACs =     4.13,     4.11,     4.19, Sparsity :  -1.59,   0.46
 Layer   53 :TIDL_FlattenLayer, PASSED  #MMACs =     0.01,     0.00,     0.01, Sparsity :   0.00, 100.00
 Layer   54 : Max PASS : -2147483648 :    86076 Out Q :    16038 ,   204211, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.13,     0.13,     0.13, Sparsity :   0.00,   1.88
 Layer   55 :TIDL_FlattenLayer, PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :   0.00, 100.00
 Layer   56 : Max PASS : -2147483648 :   245523 Out Q :     5529 ,   494913, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.69,     0.71,     0.72, Sparsity :  -4.76,  -2.69
 Layer   57 :TIDL_FlattenLayer, PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :   0.00, 100.00
 Layer   58 : Max PASS : -2147483648 :   131808 Out Q :    18546 ,   278734, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.03,     0.03,     0.03, Sparsity :   0.00,   1.56
 Layer   59 :TIDL_FlattenLayer, PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :   0.00, 100.00
 Layer   60 : Max PASS : -2147483648 :   300721 Out Q :     7062 ,   606178, TIDL_ConvolutionLayer, PASSED  #MMACs =     0.17,     0.18,     0.18, Sparsity :  -4.76,  -2.72
 Layer   61 :TIDL_FlattenLayer, PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :   0.00, 100.00
 Layer   62 : Max PASS : -2147483648 :    64770 Out Q :     6599 ,    65024, TIDL_ConcatLayer, PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :  -1.#J,  -1.#J
 Layer   63 : Max PASS : -2147483648 :    65025 Out Q :      461 ,    65280, TIDL_ConcatLayer, PASSED  #MMACs =     0.00,     0.00,     0.00, Sparsity :  -1.#J,  -1.#J
 Layer   64 : #MMACs =     0.00,     0.00,     0.00, Sparsity :   0.00, 100.00
End of config list found !
,       8 ,       8 ,       1 ,      24 ,       8 ,       8 ,    786432 ,
 53, TIDL_FlattenLayer             , ctx_output3/sep/relu_mbox_loc_perm        1,   1 ,  1 ,  52 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 53 ,       1 ,      24 ,       8 ,       8 ,       1 ,       1 ,       1 ,    1536 ,         1 ,
 54, TIDL_ConvolutionLayer         , ctx_output3/sep/relu_mbox_conf            1,   1 ,  1 ,  37 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 54 ,       1 ,     512 ,       8 ,       8 ,       1 ,     126 ,       8 ,       8 ,   4128768 ,
 55, TIDL_FlattenLayer             , ctx_output3/sep/relu_mbox_conf_perm       1,   1 ,  1 ,  54 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 55 ,       1 ,     126 ,       8 ,       8 ,       1 ,       1 ,       1 ,    8064 ,         1 ,
 57, TIDL_ConvolutionLayer         , ctx_output4/sep/relu_mbox_loc             1,   1 ,  1 ,  39 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 57 ,       1 ,     512 ,       4 ,       4 ,       1 ,      16 ,       4 ,       4 ,    131072 ,
 58, TIDL_FlattenLayer             , ctx_output4/sep/relu_mbox_loc_perm        1,   1 ,  1 ,  57 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 58 ,       1 ,      16 ,       4 ,       4 ,       1 ,       1 ,       1 ,     256 ,         1 ,
 59, TIDL_ConvolutionLayer         , ctx_output4/sep/relu_mbox_conf            1,   1 ,  1 ,  39 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 59 ,       1 ,     512 ,       4 ,       4 ,       1 ,      84 ,       4 ,       4 ,    688128 ,
 60, TIDL_FlattenLayer             , ctx_output4/sep/relu_mbox_conf_perm       1,   1 ,  1 ,  59 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 60 ,       1 ,      84 ,       4 ,       4 ,       1 ,       1 ,       1 ,    1344 ,         1 ,
 62, TIDL_ConvolutionLayer         , ctx_output5/sep/relu_mbox_loc             1,   1 ,  1 ,  41 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 62 ,       1 ,     512 ,       2 ,       2 ,       1 ,      16 ,       2 ,       2 ,     32768 ,
 63, TIDL_FlattenLayer             , ctx_output5/sep/relu_mbox_loc_perm        1,   1 ,  1 ,  62 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 63 ,       1 ,      16 ,       2 ,       2 ,       1 ,       1 ,       1 ,      64 ,         1 ,
 64, TIDL_ConvolutionLayer         , ctx_output5/sep/relu_mbox_conf            1,   1 ,  1 ,  41 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 64 ,       1 ,     512 ,       2 ,       2 ,       1 ,      84 ,       2 ,       2 ,    172032 ,
 65, TIDL_FlattenLayer             , ctx_output5/sep/relu_mbox_conf_perm       1,   1 ,  1 ,  64 ,  x ,  x ,  x ,  x ,  x ,  x ,  x , 65 ,       1 ,      84 ,       2 ,       2 ,       1 ,       1 ,       1 ,     336 ,         1 ,
 67, TIDL_ConcatLayer              , mbox_loc                                  1,   5 ,  1 ,  43 , 48 , 53 , 58 , 63 ,  x ,  x ,  x , 67 ,       1 ,       1 ,       1 ,   16384 ,       1 ,       1 ,       1 ,   24384 ,         1 ,
 68, TIDL_ConcatLayer              , mbox_conf                                 1,   5 ,  1 ,  45 , 50 , 55 , 60 , 65 ,  x ,  x ,  x , 68 ,       1 ,       1 ,       1 ,   86016 ,       1 ,       1 ,       1 ,  128016 ,         1 ,
 69, TIDL_DetectionOutputLayer     , detection_out                             1,   2 ,  1 ,  67 , 68 ,  x ,  x ,  x ,  x ,  x ,  x , 69 ,       1 ,       1 ,       1 ,   24384 ,       1 ,       1 ,       1 ,     560 ,         1 ,
Total Giga Macs : 1.0846
