tensorflow lite conversion changes model weights

Question

I have a model saved in .pb file and it works fine, but when I convert it to tflite model with command tflite_convert or python api, the result is wrong. And I find that the weights have been changed after conversion. The weights of first convolution layer in .pb file are as follows:

shape - 
(3, 3, 1, 8)
Value - 
[[[[-0.09953183  0.11656161  0.1101007  -0.02618909 -0.21355744
    -0.05877252  0.11881053 -0.17588891]]

  [[-0.16565287  0.16550814  0.02200373  0.0987333   0.0194475
    -0.12387082 -0.06090429 -0.19122925]]

  [[-0.19570269  0.11854213 -0.14988026 -0.01476914  0.12554781
    -0.1324673  -0.04035608 -0.05299769]]]


 [[[ 0.08548407 -0.09644134  0.24321978  0.15008359 -0.2591259
     0.2421266   0.02051029 -0.05138292]]

  [[ 0.04847065 -0.22357103 -0.00074622  0.19842042  0.00228794
     0.13352048 -0.24048899 -0.00679056]]

  [[-0.01857976 -0.09324262 -0.19632849  0.02247559  0.18489467
    -0.07365554 -0.39479995  0.0622104 ]]]


 [[[ 0.13633308  0.04041797  0.10581032 -0.13119537  0.01122213
     0.15191257  0.03097369  0.07342041]]

  [[ 0.16241515 -0.04534301 -0.06334146 -0.19276966 -0.03890191
     0.08520683 -0.0117504   0.14705475]]

  [[ 0.07332639 -0.00533756 -0.06285968 -0.12631118  0.09094885
    -0.09658462 -0.04983746  0.13325559]]]]

And The weights of first convolution layer in .tflite file are as follows:

shape - 
(1, 3, 3, 8)
Value - 
[[[[ -31.412575     42.14294      36.269154     -8.724394
     -67.77634     -12.249788     43.18692     -76.762474  ]
   [ -52.280594     59.839592      7.248423     32.89111
       6.1720166   -25.818043    -22.138346    -83.4574    ]
   [ -61.764416     42.858997    -49.373257     -4.9200554
      39.844883    -27.609783    -14.669194    -23.129562  ]]

  [[  26.979053    -34.86844      80.12097      49.997475
     -82.23831      50.46576       7.4553676   -22.424837  ]
   [  15.297499    -80.832275     -0.24581672   66.09997
       0.7261198    27.829294    -87.41631      -2.963576  ]
   [  -5.8638325   -33.71194     -64.67414       7.487314
      58.679688    -15.351814   -143.50742      27.15023   ]]

  [[  43.02717      14.613146     34.855824    -43.705227
       3.561546     31.662704     11.25875      32.04257   ]
   [  51.258755    -16.393799    -20.865818    -64.21752
     -12.346229     17.759417     -4.2712016    64.1785    ]
   [  23.14205      -1.929798    -20.70711     -42.07815
      28.864273    -20.130857    -18.115618     58.15619   ]]]]

It seems there are some relations.

the tensorflow version is 1.12.

The command is

tflite_convert --output_file=graph_net_half.tflite --graph_def_file=graph_net_half.pb  --input_arrays=input_image --output_arrays=output_landmark 

there is another similar question with no answer: tflite weights

Answer 1

It's expect that the weights will be changed when running tflite_convert for several reasons:

• TensorFlow Conv2D uses HWIO weights (filter_height, filter_weight, input_channels, output_channels). TensorFlow Lite Conv2D uses IHWO weights for optimization reasons. The axis of weights must be reordered.
• tflite_convert does optimizations like constant folding, which will also change the weights.

Seeing different weights doesn't mean the conversion is wrong.