nihui
/
ncnn
Not watched
1
0
Fork 0
Code
Releases 46 Wiki evaluate Activity
Issues 0 Pull Requests 0 Datasets Model Cloudbrain HPC
You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.
Tree: a3a2548aa2
Branches Tags
${ item.name }
Create branch ${ searchTerm }
from 'a3a2548aa2'
${ noResults }
ncnn/benchmark/mobilenet_yolo.param

135 lines
12 kB
Raw Blame History 

  1. 7767517

  2. 132 134

  3. Input            data             0 1 data 0=416 1=416 2=3

  4. Convolution      conv0            1 1 data conv0 0=32 1=3 2=1 3=2 4=1 5=0 6=864

  5. BatchNorm        conv0/bn         1 1 conv0 conv0_conv0/bn 0=32

  6. Scale            conv0/scale      1 1 conv0_conv0/bn conv0_conv0/scale 0=32 1=1

  7. ReLU             conv0/relu       1 1 conv0_conv0/scale conv0_conv0/relu

  8. ConvolutionDepthWise conv1/dw         1 1 conv0_conv0/relu conv1/dw 0=32 1=3 2=1 3=1 4=1 5=0 6=288 7=32

  9. BatchNorm        conv1/dw/bn      1 1 conv1/dw conv1/dw_conv1/dw/bn 0=32

  10. Scale            conv1/dw/scale   1 1 conv1/dw_conv1/dw/bn conv1/dw_conv1/dw/scale 0=32 1=1

  11. ReLU             conv1/dw/relu    1 1 conv1/dw_conv1/dw/scale conv1/dw_conv1/dw/relu

  12. Convolution      conv1            1 1 conv1/dw_conv1/dw/relu conv1 0=64 1=1 2=1 3=1 4=0 5=0 6=2048

  13. BatchNorm        conv1/bn         1 1 conv1 conv1_conv1/bn 0=64

  14. Scale            conv1/scale      1 1 conv1_conv1/bn conv1_conv1/scale 0=64 1=1

  15. ReLU             conv1/relu       1 1 conv1_conv1/scale conv1_conv1/relu

  16. ConvolutionDepthWise conv2/dw         1 1 conv1_conv1/relu conv2/dw 0=64 1=3 2=1 3=2 4=1 5=0 6=576 7=64

  17. BatchNorm        conv2/dw/bn      1 1 conv2/dw conv2/dw_conv2/dw/bn 0=64

  18. Scale            conv2/dw/scale   1 1 conv2/dw_conv2/dw/bn conv2/dw_conv2/dw/scale 0=64 1=1

  19. ReLU             conv2/dw/relu    1 1 conv2/dw_conv2/dw/scale conv2/dw_conv2/dw/relu

  20. Convolution      conv2            1 1 conv2/dw_conv2/dw/relu conv2 0=128 1=1 2=1 3=1 4=0 5=0 6=8192

  21. BatchNorm        conv2/bn         1 1 conv2 conv2_conv2/bn 0=128

  22. Scale            conv2/scale      1 1 conv2_conv2/bn conv2_conv2/scale 0=128 1=1

  23. ReLU             conv2/relu       1 1 conv2_conv2/scale conv2_conv2/relu

  24. ConvolutionDepthWise conv3/dw         1 1 conv2_conv2/relu conv3/dw 0=128 1=3 2=1 3=1 4=1 5=0 6=1152 7=128

  25. BatchNorm        conv3/dw/bn      1 1 conv3/dw conv3/dw_conv3/dw/bn 0=128

  26. Scale            conv3/dw/scale   1 1 conv3/dw_conv3/dw/bn conv3/dw_conv3/dw/scale 0=128 1=1

  27. ReLU             conv3/dw/relu    1 1 conv3/dw_conv3/dw/scale conv3/dw_conv3/dw/relu

  28. Convolution      conv3            1 1 conv3/dw_conv3/dw/relu conv3 0=128 1=1 2=1 3=1 4=0 5=0 6=16384

  29. BatchNorm        conv3/bn         1 1 conv3 conv3_conv3/bn 0=128

  30. Scale            conv3/scale      1 1 conv3_conv3/bn conv3_conv3/scale 0=128 1=1

  31. ReLU             conv3/relu       1 1 conv3_conv3/scale conv3_conv3/relu

  32. ConvolutionDepthWise conv4/dw         1 1 conv3_conv3/relu conv4/dw 0=128 1=3 2=1 3=2 4=1 5=0 6=1152 7=128

  33. BatchNorm        conv4/dw/bn      1 1 conv4/dw conv4/dw_conv4/dw/bn 0=128

  34. Scale            conv4/dw/scale   1 1 conv4/dw_conv4/dw/bn conv4/dw_conv4/dw/scale 0=128 1=1

  35. ReLU             conv4/dw/relu    1 1 conv4/dw_conv4/dw/scale conv4/dw_conv4/dw/relu

  36. Convolution      conv4            1 1 conv4/dw_conv4/dw/relu conv4 0=256 1=1 2=1 3=1 4=0 5=0 6=32768

  37. BatchNorm        conv4/bn         1 1 conv4 conv4_conv4/bn 0=256

  38. Scale            conv4/scale      1 1 conv4_conv4/bn conv4_conv4/scale 0=256 1=1

  39. ReLU             conv4/relu       1 1 conv4_conv4/scale conv4_conv4/relu

  40. ConvolutionDepthWise conv5/dw         1 1 conv4_conv4/relu conv5/dw 0=256 1=3 2=1 3=1 4=1 5=0 6=2304 7=256

  41. BatchNorm        conv5/dw/bn      1 1 conv5/dw conv5/dw_conv5/dw/bn 0=256

  42. Scale            conv5/dw/scale   1 1 conv5/dw_conv5/dw/bn conv5/dw_conv5/dw/scale 0=256 1=1

  43. ReLU             conv5/dw/relu    1 1 conv5/dw_conv5/dw/scale conv5/dw_conv5/dw/relu

  44. Convolution      conv5            1 1 conv5/dw_conv5/dw/relu conv5 0=256 1=1 2=1 3=1 4=0 5=0 6=65536

  45. BatchNorm        conv5/bn         1 1 conv5 conv5_conv5/bn 0=256

  46. Scale            conv5/scale      1 1 conv5_conv5/bn conv5_conv5/scale 0=256 1=1

  47. ReLU             conv5/relu       1 1 conv5_conv5/scale conv5_conv5/relu

  48. ConvolutionDepthWise conv6/dw         1 1 conv5_conv5/relu conv6/dw 0=256 1=3 2=1 3=2 4=1 5=0 6=2304 7=256

  49. BatchNorm        conv6/dw/bn      1 1 conv6/dw conv6/dw_conv6/dw/bn 0=256

  50. Scale            conv6/dw/scale   1 1 conv6/dw_conv6/dw/bn conv6/dw_conv6/dw/scale 0=256 1=1

  51. ReLU             conv6/dw/relu    1 1 conv6/dw_conv6/dw/scale conv6/dw_conv6/dw/relu

  52. Convolution      conv6            1 1 conv6/dw_conv6/dw/relu conv6 0=512 1=1 2=1 3=1 4=0 5=0 6=131072

  53. BatchNorm        conv6/bn         1 1 conv6 conv6_conv6/bn 0=512

  54. Scale            conv6/scale      1 1 conv6_conv6/bn conv6_conv6/scale 0=512 1=1

  55. ReLU             conv6/relu       1 1 conv6_conv6/scale conv6_conv6/relu

  56. ConvolutionDepthWise conv7/dw         1 1 conv6_conv6/relu conv7/dw 0=512 1=3 2=1 3=1 4=1 5=0 6=4608 7=512

  57. BatchNorm        conv7/dw/bn      1 1 conv7/dw conv7/dw_conv7/dw/bn 0=512

  58. Scale            conv7/dw/scale   1 1 conv7/dw_conv7/dw/bn conv7/dw_conv7/dw/scale 0=512 1=1

  59. ReLU             conv7/dw/relu    1 1 conv7/dw_conv7/dw/scale conv7/dw_conv7/dw/relu

  60. Convolution      conv7            1 1 conv7/dw_conv7/dw/relu conv7 0=512 1=1 2=1 3=1 4=0 5=0 6=262144

  61. BatchNorm        conv7/bn         1 1 conv7 conv7_conv7/bn 0=512

  62. Scale            conv7/scale      1 1 conv7_conv7/bn conv7_conv7/scale 0=512 1=1

  63. ReLU             conv7/relu       1 1 conv7_conv7/scale conv7_conv7/relu

  64. ConvolutionDepthWise conv8/dw         1 1 conv7_conv7/relu conv8/dw 0=512 1=3 2=1 3=1 4=1 5=0 6=4608 7=512

  65. BatchNorm        conv8/dw/bn      1 1 conv8/dw conv8/dw_conv8/dw/bn 0=512

  66. Scale            conv8/dw/scale   1 1 conv8/dw_conv8/dw/bn conv8/dw_conv8/dw/scale 0=512 1=1

  67. ReLU             conv8/dw/relu    1 1 conv8/dw_conv8/dw/scale conv8/dw_conv8/dw/relu

  68. Convolution      conv8            1 1 conv8/dw_conv8/dw/relu conv8 0=512 1=1 2=1 3=1 4=0 5=0 6=262144

  69. BatchNorm        conv8/bn         1 1 conv8 conv8_conv8/bn 0=512

  70. Scale            conv8/scale      1 1 conv8_conv8/bn conv8_conv8/scale 0=512 1=1

  71. ReLU             conv8/relu       1 1 conv8_conv8/scale conv8_conv8/relu

  72. ConvolutionDepthWise conv9/dw         1 1 conv8_conv8/relu conv9/dw 0=512 1=3 2=1 3=1 4=1 5=0 6=4608 7=512

  73. BatchNorm        conv9/dw/bn      1 1 conv9/dw conv9/dw_conv9/dw/bn 0=512

  74. Scale            conv9/dw/scale   1 1 conv9/dw_conv9/dw/bn conv9/dw_conv9/dw/scale 0=512 1=1

  75. ReLU             conv9/dw/relu    1 1 conv9/dw_conv9/dw/scale conv9/dw_conv9/dw/relu

  76. Convolution      conv9            1 1 conv9/dw_conv9/dw/relu conv9 0=512 1=1 2=1 3=1 4=0 5=0 6=262144

  77. BatchNorm        conv9/bn         1 1 conv9 conv9_conv9/bn 0=512

  78. Scale            conv9/scale      1 1 conv9_conv9/bn conv9_conv9/scale 0=512 1=1

  79. ReLU             conv9/relu       1 1 conv9_conv9/scale conv9_conv9/relu

  80. ConvolutionDepthWise conv10/dw        1 1 conv9_conv9/relu conv10/dw 0=512 1=3 2=1 3=1 4=1 5=0 6=4608 7=512

  81. BatchNorm        conv10/dw/bn     1 1 conv10/dw conv10/dw_conv10/dw/bn 0=512

  82. Scale            conv10/dw/scale  1 1 conv10/dw_conv10/dw/bn conv10/dw_conv10/dw/scale 0=512 1=1

  83. ReLU             conv10/dw/relu   1 1 conv10/dw_conv10/dw/scale conv10/dw_conv10/dw/relu

  84. Convolution      conv10           1 1 conv10/dw_conv10/dw/relu conv10 0=512 1=1 2=1 3=1 4=0 5=0 6=262144

  85. BatchNorm        conv10/bn        1 1 conv10 conv10_conv10/bn 0=512

  86. Scale            conv10/scale     1 1 conv10_conv10/bn conv10_conv10/scale 0=512 1=1

  87. ReLU             conv10/relu      1 1 conv10_conv10/scale conv10_conv10/relu

  88. ConvolutionDepthWise conv11/dw        1 1 conv10_conv10/relu conv11/dw 0=512 1=3 2=1 3=1 4=1 5=0 6=4608 7=512

  89. BatchNorm        conv11/dw/bn     1 1 conv11/dw conv11/dw_conv11/dw/bn 0=512

  90. Scale            conv11/dw/scale  1 1 conv11/dw_conv11/dw/bn conv11/dw_conv11/dw/scale 0=512 1=1

  91. ReLU             conv11/dw/relu   1 1 conv11/dw_conv11/dw/scale conv11/dw_conv11/dw/relu

  92. Convolution      conv11           1 1 conv11/dw_conv11/dw/relu conv11 0=512 1=1 2=1 3=1 4=0 5=0 6=262144

  93. BatchNorm        conv11/bn        1 1 conv11 conv11_conv11/bn 0=512

  94. Scale            conv11/scale     1 1 conv11_conv11/bn conv11_conv11/scale 0=512 1=1

  95. ReLU             conv11/relu      1 1 conv11_conv11/scale conv11_conv11/relu

  96. Split            splitncnn_0      1 2 conv11_conv11/relu conv11_conv11/relu_splitncnn_0 conv11_conv11/relu_splitncnn_1

  97. ConvolutionDepthWise conv12/dw        1 1 conv11_conv11/relu_splitncnn_1 conv12/dw 0=512 1=3 2=1 3=2 4=1 5=0 6=4608 7=512

  98. BatchNorm        conv12/dw/bn     1 1 conv12/dw conv12/dw_conv12/dw/bn 0=512

  99. Scale            conv12/dw/scale  1 1 conv12/dw_conv12/dw/bn conv12/dw_conv12/dw/scale 0=512 1=1

  100. ReLU             conv12/dw/relu   1 1 conv12/dw_conv12/dw/scale conv12/dw_conv12/dw/relu

  101. Convolution      conv12           1 1 conv12/dw_conv12/dw/relu conv12 0=1024 1=1 2=1 3=1 4=0 5=0 6=524288

  102. BatchNorm        conv12/bn        1 1 conv12 conv12_conv12/bn 0=1024

  103. Scale            conv12/scale     1 1 conv12_conv12/bn conv12_conv12/scale 0=1024 1=1

  104. ReLU             conv12/relu      1 1 conv12_conv12/scale conv12_conv12/relu

  105. ConvolutionDepthWise conv13/dw        1 1 conv12_conv12/relu conv13/dw 0=1024 1=3 2=1 3=1 4=1 5=0 6=9216 7=1024

  106. BatchNorm        conv13/dw/bn     1 1 conv13/dw conv13/dw_conv13/dw/bn 0=1024

  107. Scale            conv13/dw/scale  1 1 conv13/dw_conv13/dw/bn conv13/dw_conv13/dw/scale 0=1024 1=1

  108. ReLU             conv13/dw/relu   1 1 conv13/dw_conv13/dw/scale conv13/dw_conv13/dw/relu

  109. Convolution      conv13           1 1 conv13/dw_conv13/dw/relu conv13 0=1024 1=1 2=1 3=1 4=0 5=0 6=1048576

  110. BatchNorm        conv13/bn        1 1 conv13 conv13_conv13/bn 0=1024

  111. Scale            conv13/scale     1 1 conv13_conv13/bn conv13_conv13/scale 0=1024 1=1

  112. ReLU             conv13/relu      1 1 conv13_conv13/scale conv13_conv13/relu

  113. ConvolutionDepthWise conv16/dw        1 1 conv13_conv13/relu conv16/dw 0=1024 1=3 2=1 3=1 4=1 5=0 6=9216 7=1024

  114. BatchNorm        conv16/dw/bn     1 1 conv16/dw conv16/dw_conv16/dw/bn 0=1024

  115. Scale            conv16/dw/scale  1 1 conv16/dw_conv16/dw/bn conv16/dw_conv16/dw/scale 0=1024 1=1

  116. ReLU             conv16/dw/relu   1 1 conv16/dw_conv16/dw/scale conv16/dw_conv16/dw/relu

  117. Convolution      conv17           1 1 conv16/dw_conv16/dw/relu conv17 0=1024 1=1 2=1 3=1 4=0 5=0 6=1048576

  118. BatchNorm        conv17/bn        1 1 conv17 conv17_conv17/bn 0=1024

  119. Scale            conv17/scale     1 1 conv17_conv17/bn conv17_conv17/scale 0=1024 1=1

  120. ReLU             conv17/relu      1 1 conv17_conv17/scale conv17_conv17/relu

  121. Split            splitncnn_1      1 2 conv17_conv17/relu conv17_conv17/relu_splitncnn_0 conv17_conv17/relu_splitncnn_1

  122. DeconvolutionDepthWise upsample         1 1 conv17_conv17/relu_splitncnn_1 upsample 0=512 1=4 2=1 3=2 4=1 5=0 6=16384 7=512

  123. Eltwise          conv_18/sum      2 1 conv11_conv11/relu_splitncnn_0 upsample conv_18/sum 0=1 -23301=0

  124. ConvolutionDepthWise conv19/dw        1 1 conv_18/sum conv19/dw 0=512 1=3 2=1 3=1 4=1 5=0 6=4608 7=512

  125. BatchNorm        conv19/dw/bn     1 1 conv19/dw conv19/dw_conv19/dw/bn 0=512

  126. Scale            conv19/dw/scale  1 1 conv19/dw_conv19/dw/bn conv19/dw_conv19/dw/scale 0=512 1=1

  127. ReLU             conv19/dw/relu   1 1 conv19/dw_conv19/dw/scale conv19/dw_conv19/dw/relu

  128. Convolution      conv20           1 1 conv19/dw_conv19/dw/relu conv20 0=1024 1=1 2=1 3=1 4=0 5=0 6=524288

  129. BatchNorm        conv20/bn        1 1 conv20 conv20_conv20/bn 0=1024

  130. Scale            conv20/scale     1 1 conv20_conv20/bn conv20_conv20/scale 0=1024 1=1

  131. ReLU             conv20/relu      1 1 conv20_conv20/scale conv20_conv20/relu

  132. Convolution      conv22_indoor    1 1 conv17_conv17/relu_splitncnn_0 conv22 0=125 1=1 2=1 3=1 4=0 5=1 6=128000

  133. Convolution      conv23_indoor    1 1 conv20_conv20/relu conv23 0=125 1=1 2=1 3=1 4=0 5=1 6=128000

  134. YoloDetectionOutput detection_out    2 1 conv22 conv23 detection_out 0=20 1=5 2=0.400000 3=0.450000 -23304=10,1.080000,1.190000,3.420000,4.410000,6.630000,11.380000,9.420000,5.110000,16.620001,10.520000