MNNDump2Json

MNNDump2Json is used to dump MNN binary model file to readable json format. It is helpful to compare to original model parameters to double check the model format conversion is done correctly.

  1. ./MNNDump2Json.out mobilenet_v2.caffe.mnn output.json
  2. cat output.json 
  4. { oplists: 
  5. [ 
  6. { type: Input, name: "data", outputIndexes: 
  7. [ 0 ]
  8. , main_type: Input, main: 
  9. { dims: 
  10. [ 1, 3,  ... ]
  11.  }
  12.  }
  13. , 
  14. { type: Convolution, name: "conv1", inputIndexes: 
  15. [ 0 ]
  16. , outputIndexes: 
  17. [ 1 ]
  18. , main_type: Convolution2D, main: 
  19. { common: 
  20. { dilateX: 1, dilateY: 1, strideX: 2, strideY: 2, kernelX: 3, kernelY: 3, padX: 1, padY: 1, group: 1, outputCount: 32, relu: true }
  21. , weight: 
  22. [ -0.113041, 0.15978,  ... ]
  23. , bias: 
  24. [ 0.61395, 2.009104,  ... ]
  25.  }
  26.  }
  27. , 
  28. ...
  29.  ]
  30. , tensorName: 
  31. [ "data", "conv1/bn", "conv2_1/expand/bn", "conv2_1/dwise/bn", "conv2_1/linear/bn", "conv2_2/expand/bn", "conv2_2/dwise/bn", "conv2_2/linear/bn", "conv3_1/expand/bn", "conv3_1/dwise/bn", "conv3_1/linear/bn", "block_3_1", "conv3_2/expand/bn", "conv3_2/dwise/bn", "conv3_2/linear/bn", "conv4_1/expand/bn", "conv4_1/dwise/bn", "conv4_1/linear/bn", "block_4_1", "conv4_2/expand/bn", "conv4_2/dwise/bn", "conv4_2/linear/bn", "block_4_2", "conv4_3/expand/bn", "conv4_3/dwise/bn", "conv4_3/linear/bn", "conv4_4/expand/bn", "conv4_4/dwise/bn", "conv4_4/linear/bn", "block_4_4", "conv4_5/expand/bn", "conv4_5/dwise/bn", "conv4_5/linear/bn", "block_4_5", "conv4_6/expand/bn", "conv4_6/dwise/bn", "conv4_6/linear/bn", "block_4_6", "conv4_7/expand/bn", "conv4_7/dwise/bn", "conv4_7/linear/bn", "conv5_1/expand/bn", "conv5_1/dwise/bn", "conv5_1/linear/bn", "block_5_1", "conv5_2/expand/bn", "conv5_2/dwise/bn", "conv5_2/linear/bn", "block_5_2", "conv5_3/expand/bn", "conv5_3/dwise/bn", "conv5_3/linear/bn", "conv6_1/expand/bn", "conv6_1/dwise/bn", "conv6_1/linear/bn", "block_6_1", "conv6_2/expand/bn", "conv6_2/dwise/bn", "conv6_2/linear/bn", "block_6_2", "conv6_3/expand/bn", "conv6_3/dwise/bn", "conv6_3/linear/bn", "conv6_4/bn", "pool6", "fc7", "prob" ]
  32. , bizCode: "0000" }