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Comparissons.txt
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Comparissons.txt
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TFLITE No quantization
STM32F407 TFLiteuC Deep Learning test!<\r><\n>
<\r><\n>
STM32F407 TensorFlow Lite test<\r><\n>
<\r><\n>
Number of input elements: 1<\r><\n>
In: 0.000000 | Out: -0.018659 | 25[uS]<\r><\n>
In: 0.062832 | Out: 0.059352 | 25[uS]<\r><\n>
In: 0.125664 | Out: 0.137363 | 25[uS]<\r><\n>
In: 0.188496 | Out: 0.215373 | 25[uS]<\r><\n>
In: 0.251327 | Out: 0.293384 | 25[uS]<\r><\n>
In: 0.314159 | Out: 0.365296 | 25[uS]<\r><\n>
In: 0.376991 | Out: 0.395453 | 25[uS]<\r><\n>
In: 0.439823 | Out: 0.425611 | 25[uS]<\r><\n>
In: 0.502655 | Out: 0.455768 | 25[uS]<\r><\n>
In: 0.565487 | Out: 0.489595 | 25[uS]<\r><\n>
In: 0.628319 | Out: 0.549352 | 25[uS]<\r><\n>
In: 0.691150 | Out: 0.609109 | 25[uS]<\r><\n>
In: 0.753982 | Out: 0.668866 | 25[uS]<\r><\n>
In: 0.816814 | Out: 0.728623 | 25[uS]<\r><\n>
In: 0.879646 | Out: 0.788380 | 25[uS]<\r><\n>
In: 0.942478 | Out: 0.831551 | 25[uS]<\r><\n>
In: 1.005310 | Out: 0.858797 | 25[uS]<\r><\n>
In: 1.068141 | Out: 0.886042 | 25[uS]<\r><\n>
In: 1.130973 | Out: 0.913288 | 25[uS]<\r><\n>
In: 1.193805 | Out: 0.940534 | 25[uS]<\r><\n>
In: 1.256637 | Out: 0.963158 | 25[uS]<\r><\n>
In: 1.319469 | Out: 0.978423 | 25[uS]<\r><\n>
In: 1.382301 | Out: 0.993688 | 25[uS]<\r><\n>
In: 1.445133 | Out: 1.008954 | 25[uS]<\r><\n>
In: 1.507964 | Out: 1.024219 | 25[uS]<\r><\n>
In: 1.570796 | Out: 1.039485 | 25[uS]<\r><\n>
In: 1.633628 | Out: 1.036224 | 25[uS]<\r><\n>
In: 1.696460 | Out: 1.014797 | 25[uS]<\r><\n>
In: 1.759292 | Out: 0.993369 | 25[uS]<\r><\n>
In: 1.822124 | Out: 0.971942 | 25[uS]<\r><\n>
In: 1.884956 | Out: 0.950514 | 25[uS]<\r><\n>
In: 1.947787 | Out: 0.929087 | 25[uS]<\r><\n>
In: 2.010619 | Out: 0.907659 | 25[uS]<\r><\n>
In: 2.073451 | Out: 0.886232 | 25[uS]<\r><\n>
In: 2.136283 | Out: 0.864577 | 25[uS]<\r><\n>
In: 2.199115 | Out: 0.826942 | 25[uS]<\r><\n>
In: 2.261947 | Out: 0.789306 | 25[uS]<\r><\n>
In: 2.324779 | Out: 0.751670 | 25[uS]<\r><\n>
In: 2.387610 | Out: 0.700336 | 25[uS]<\r><\n>
In: 2.450442 | Out: 0.641881 | 25[uS]<\r><\n>
In: 2.513274 | Out: 0.583425 | 25[uS]<\r><\n>
In: 2.576106 | Out: 0.524969 | 25[uS]<\r><\n>
In: 2.638938 | Out: 0.466513 | 25[uS]<\r><\n>
In: 2.701770 | Out: 0.408057 | 25[uS]<\r><\n>
In: 2.764601 | Out: 0.349601 | 25[uS]<\r><\n>
In: 2.827433 | Out: 0.291146 | 25[uS]<\r><\n>
In: 2.890265 | Out: 0.232690 | 25[uS]<\r><\n>
In: 2.953097 | Out: 0.174234 | 25[uS]<\r><\n>
In: 3.015929 | Out: 0.115778 | 25[uS]<\r><\n>
In: 3.078761 | Out: 0.057322 | 25[uS]<\r><\n>
In: 3.141593 | Out: -0.001134 | 25[uS]<\r><\n>
In: 3.204425 | Out: -0.059590 | 25[uS]<\r><\n>
In: 3.267256 | Out: -0.118045 | 25[uS]<\r><\n>
In: 3.330088 | Out: -0.176501 | 25[uS]<\r><\n>
In: 3.392920 | Out: -0.234957 | 25[uS]<\r><\n>
In: 3.455752 | Out: -0.293413 | 25[uS]<\r><\n>
In: 3.518584 | Out: -0.351869 | 25[uS]<\r><\n>
In: 3.581416 | Out: -0.410324 | 25[uS]<\r><\n>
In: 3.644248 | Out: -0.464681 | 25[uS]<\r><\n>
In: 3.707079 | Out: -0.518193 | 25[uS]<\r><\n>
In: 3.769911 | Out: -0.571706 | 25[uS]<\r><\n>
In: 3.832743 | Out: -0.625218 | 25[uS]<\r><\n>
In: 3.895575 | Out: -0.678730 | 25[uS]<\r><\n>
In: 3.958407 | Out: -0.718591 | 25[uS]<\r><\n>
In: 4.021239 | Out: -0.747864 | 25[uS]<\r><\n>
In: 4.084071 | Out: -0.777137 | 25[uS]<\r><\n>
In: 4.146902 | Out: -0.806410 | 25[uS]<\r><\n>
In: 4.209734 | Out: -0.835682 | 25[uS]<\r><\n>
In: 4.272566 | Out: -0.864955 | 25[uS]<\r><\n>
In: 4.335398 | Out: -0.894228 | 25[uS]<\r><\n>
In: 4.398230 | Out: -0.923501 | 25[uS]<\r><\n>
In: 4.461061 | Out: -0.952774 | 25[uS]<\r><\n>
In: 4.523893 | Out: -0.982046 | 25[uS]<\r><\n>
In: 4.586725 | Out: -1.011319 | 25[uS]<\r><\n>
In: 4.649557 | Out: -1.040592 | 25[uS]<\r><\n>
In: 4.712389 | Out: -1.069865 | 25[uS]<\r><\n>
In: 4.775221 | Out: -1.099137 | 25[uS]<\r><\n>
In: 4.838053 | Out: -1.101192 | 25[uS]<\r><\n>
In: 4.900885 | Out: -1.058769 | 25[uS]<\r><\n>
In: 4.963717 | Out: -1.016345 | 25[uS]<\r><\n>
In: 5.026548 | Out: -0.973921 | 25[uS]<\r><\n>
In: 5.089380 | Out: -0.931497 | 25[uS]<\r><\n>
In: 5.152212 | Out: -0.889074 | 25[uS]<\r><\n>
In: 5.215044 | Out: -0.846650 | 25[uS]<\r><\n>
In: 5.277875 | Out: -0.804227 | 25[uS]<\r><\n>
In: 5.340707 | Out: -0.761803 | 25[uS]<\r><\n>
In: 5.403539 | Out: -0.719379 | 25[uS]<\r><\n>
In: 5.466371 | Out: -0.676956 | 25[uS]<\r><\n>
In: 5.529203 | Out: -0.634532 | 25[uS]<\r><\n>
In: 5.592035 | Out: -0.592108 | 25[uS]<\r><\n>
In: 5.654867 | Out: -0.549685 | 25[uS]<\r><\n>
In: 5.717699 | Out: -0.507261 | 25[uS]<\r><\n>
In: 5.780530 | Out: -0.464837 | 25[uS]<\r><\n>
In: 5.843362 | Out: -0.422413 | 25[uS]<\r><\n>
In: 5.906194 | Out: -0.379990 | 25[uS]<\r><\n>
In: 5.969026 | Out: -0.337566 | 25[uS]<\r><\n>
In: 6.031858 | Out: -0.295143 | 25[uS]<\r><\n>
In: 6.094690 | Out: -0.252719 | 25[uS]<\r><\n>
In: 6.157522 | Out: -0.210295 | 25[uS]<\r><\n>
**********************************************************************
CUBEMX No quantization
HTT Deep Learning test!<\r><\n>
In: 0.000000 | Out: -0.018664 | 20[uS]<\r><\n>
In: 0.062832 | Out: 0.059348 | 20[uS]<\r><\n>
In: 0.125664 | Out: 0.137359 | 20[uS]<\r><\n>
In: 0.188496 | Out: 0.215371 | 20[uS]<\r><\n>
In: 0.251327 | Out: 0.293383 | 20[uS]<\r><\n>
In: 0.314159 | Out: 0.365307 | 20[uS]<\r><\n>
In: 0.376991 | Out: 0.395463 | 20[uS]<\r><\n>
In: 0.439823 | Out: 0.425618 | 20[uS]<\r><\n>
In: 0.502655 | Out: 0.455774 | 20[uS]<\r><\n>
In: 0.565487 | Out: 0.489600 | 20[uS]<\r><\n>
In: 0.628319 | Out: 0.549354 | 20[uS]<\r><\n>
In: 0.691150 | Out: 0.609109 | 20[uS]<\r><\n>
In: 0.753982 | Out: 0.668864 | 20[uS]<\r><\n>
In: 0.816814 | Out: 0.728618 | 20[uS]<\r><\n>
In: 0.879646 | Out: 0.788373 | 20[uS]<\r><\n>
In: 0.942478 | Out: 0.831551 | 20[uS]<\r><\n>
In: 1.005310 | Out: 0.858795 | 20[uS]<\r><\n>
In: 1.068141 | Out: 0.886039 | 20[uS]<\r><\n>
In: 1.130973 | Out: 0.913283 | 20[uS]<\r><\n>
In: 1.193805 | Out: 0.940527 | 20[uS]<\r><\n>
In: 1.256637 | Out: 0.963164 | 20[uS]<\r><\n>
In: 1.319469 | Out: 0.978428 | 20[uS]<\r><\n>
In: 1.382301 | Out: 0.993692 | 20[uS]<\r><\n>
In: 1.445133 | Out: 1.008956 | 20[uS]<\r><\n>
In: 1.507964 | Out: 1.024220 | 20[uS]<\r><\n>
In: 1.570796 | Out: 1.039484 | 20[uS]<\r><\n>
In: 1.633628 | Out: 1.036231 | 20[uS]<\r><\n>
In: 1.696460 | Out: 1.014802 | 20[uS]<\r><\n>
In: 1.759292 | Out: 0.993373 | 20[uS]<\r><\n>
In: 1.822124 | Out: 0.971944 | 20[uS]<\r><\n>
In: 1.884956 | Out: 0.950514 | 20[uS]<\r><\n>
In: 1.947787 | Out: 0.929085 | 20[uS]<\r><\n>
In: 2.010619 | Out: 0.907656 | 20[uS]<\r><\n>
In: 2.073451 | Out: 0.886227 | 20[uS]<\r><\n>
In: 2.136283 | Out: 0.864575 | 20[uS]<\r><\n>
In: 2.199115 | Out: 0.826940 | 20[uS]<\r><\n>
In: 2.261947 | Out: 0.789303 | 20[uS]<\r><\n>
In: 2.324779 | Out: 0.751667 | 20[uS]<\r><\n>
In: 2.387610 | Out: 0.700337 | 20[uS]<\r><\n>
In: 2.450442 | Out: 0.641881 | 20[uS]<\r><\n>
In: 2.513274 | Out: 0.583425 | 20[uS]<\r><\n>
In: 2.576106 | Out: 0.524969 | 20[uS]<\r><\n>
In: 2.638938 | Out: 0.466514 | 20[uS]<\r><\n>
In: 2.701770 | Out: 0.408057 | 20[uS]<\r><\n>
In: 2.764601 | Out: 0.349601 | 20[uS]<\r><\n>
In: 2.827433 | Out: 0.291145 | 20[uS]<\r><\n>
In: 2.890265 | Out: 0.232689 | 20[uS]<\r><\n>
In: 2.953097 | Out: 0.174233 | 20[uS]<\r><\n>
In: 3.015929 | Out: 0.115777 | 20[uS]<\r><\n>
In: 3.078761 | Out: 0.057321 | 20[uS]<\r><\n>
In: 3.141593 | Out: -0.001135 | 20[uS]<\r><\n>
In: 3.204425 | Out: -0.059591 | 20[uS]<\r><\n>
In: 3.267256 | Out: -0.118047 | 20[uS]<\r><\n>
In: 3.330088 | Out: -0.176503 | 20[uS]<\r><\n>
In: 3.392920 | Out: -0.234959 | 20[uS]<\r><\n>
In: 3.455752 | Out: -0.293415 | 20[uS]<\r><\n>
In: 3.518584 | Out: -0.351871 | 20[uS]<\r><\n>
In: 3.581416 | Out: -0.410327 | 20[uS]<\r><\n>
In: 3.644248 | Out: -0.464680 | 20[uS]<\r><\n>
In: 3.707079 | Out: -0.518193 | 20[uS]<\r><\n>
In: 3.769911 | Out: -0.571706 | 20[uS]<\r><\n>
In: 3.832743 | Out: -0.625218 | 20[uS]<\r><\n>
In: 3.895575 | Out: -0.678731 | 20[uS]<\r><\n>
In: 3.958407 | Out: -0.718591 | 20[uS]<\r><\n>
In: 4.021239 | Out: -0.747865 | 20[uS]<\r><\n>
In: 4.084071 | Out: -0.777137 | 20[uS]<\r><\n>
In: 4.146902 | Out: -0.806410 | 20[uS]<\r><\n>
In: 4.209734 | Out: -0.835683 | 20[uS]<\r><\n>
In: 4.272566 | Out: -0.864956 | 20[uS]<\r><\n>
In: 4.335398 | Out: -0.894229 | 20[uS]<\r><\n>
In: 4.398230 | Out: -0.923502 | 20[uS]<\r><\n>
In: 4.461061 | Out: -0.952775 | 20[uS]<\r><\n>
In: 4.523893 | Out: -0.982047 | 20[uS]<\r><\n>
In: 4.586725 | Out: -1.011320 | 20[uS]<\r><\n>
In: 4.649557 | Out: -1.040593 | 20[uS]<\r><\n>
In: 4.712389 | Out: -1.069866 | 20[uS]<\r><\n>
In: 4.775221 | Out: -1.099139 | 20[uS]<\r><\n>
In: 4.838053 | Out: -1.101199 | 20[uS]<\r><\n>
In: 4.900885 | Out: -1.058775 | 20[uS]<\r><\n>
In: 4.963717 | Out: -1.016351 | 20[uS]<\r><\n>
In: 5.026548 | Out: -0.973926 | 20[uS]<\r><\n>
In: 5.089380 | Out: -0.931502 | 20[uS]<\r><\n>
In: 5.152212 | Out: -0.889078 | 20[uS]<\r><\n>
In: 5.215044 | Out: -0.846653 | 20[uS]<\r><\n>
In: 5.277875 | Out: -0.804229 | 20[uS]<\r><\n>
In: 5.340707 | Out: -0.761805 | 20[uS]<\r><\n>
In: 5.403539 | Out: -0.719381 | 20[uS]<\r><\n>
In: 5.466371 | Out: -0.676956 | 20[uS]<\r><\n>
In: 5.529203 | Out: -0.634532 | 20[uS]<\r><\n>
In: 5.592035 | Out: -0.592108 | 20[uS]<\r><\n>
In: 5.654867 | Out: -0.549684 | 20[uS]<\r><\n>
In: 5.717699 | Out: -0.507259 | 20[uS]<\r><\n>
In: 5.780530 | Out: -0.464835 | 20[uS]<\r><\n>
In: 5.843362 | Out: -0.422411 | 20[uS]<\r><\n>
In: 5.906194 | Out: -0.379986 | 20[uS]<\r><\n>
In: 5.969026 | Out: -0.337562 | 20[uS]<\r><\n>
In: 6.031858 | Out: -0.295138 | 20[uS]<\r><\n>
In: 6.094690 | Out: -0.252713 | 20[uS]<\r><\n>
In: 6.157522 | Out: -0.210289 | 20[uS]<\r><\n>
**********************************************************************
TFLITE i8 quantization
STM32F407 TFLiteuC Deep Learning test!<\r><\n>
<\r><\n>
STM32F407 TensorFlow Lite test<\r><\n>
<\r><\n>
Number of input elements: 1<\r><\n>
In: 0.000000 | Out: 0.000000 | 37[uS]<\r><\n>
In: 0.062832 | Out: 0.101664 | 37[uS]<\r><\n>
In: 0.125664 | Out: 0.160968 | 37[uS]<\r><\n>
In: 0.188496 | Out: 0.237216 | 37[uS]<\r><\n>
In: 0.251327 | Out: 0.296520 | 37[uS]<\r><\n>
In: 0.314159 | Out: 0.372768 | 37[uS]<\r><\n>
In: 0.376991 | Out: 0.389712 | 37[uS]<\r><\n>
In: 0.439823 | Out: 0.440544 | 37[uS]<\r><\n>
In: 0.502655 | Out: 0.457488 | 37[uS]<\r><\n>
In: 0.565487 | Out: 0.491376 | 37[uS]<\r><\n>
In: 0.628319 | Out: 0.559153 | 37[uS]<\r><\n>
In: 0.691150 | Out: 0.609985 | 37[uS]<\r><\n>
In: 0.753982 | Out: 0.686233 | 37[uS]<\r><\n>
In: 0.816814 | Out: 0.745537 | 37[uS]<\r><\n>
In: 0.879646 | Out: 0.796369 | 37[uS]<\r><\n>
In: 0.942478 | Out: 0.847201 | 37[uS]<\r><\n>
In: 1.005310 | Out: 0.889561 | 37[uS]<\r><\n>
In: 1.068141 | Out: 0.906505 | 37[uS]<\r><\n>
In: 1.130973 | Out: 0.931921 | 37[uS]<\r><\n>
In: 1.193805 | Out: 0.965809 | 37[uS]<\r><\n>
In: 1.256637 | Out: 0.982753 | 37[uS]<\r><\n>
In: 1.319469 | Out: 0.991225 | 37[uS]<\r><\n>
In: 1.382301 | Out: 0.999697 | 37[uS]<\r><\n>
In: 1.445133 | Out: 1.016641 | 37[uS]<\r><\n>
In: 1.507964 | Out: 1.025113 | 37[uS]<\r><\n>
In: 1.570796 | Out: 1.042057 | 37[uS]<\r><\n>
In: 1.633628 | Out: 1.033585 | 37[uS]<\r><\n>
In: 1.696460 | Out: 1.025113 | 37[uS]<\r><\n>
In: 1.759292 | Out: 0.991225 | 37[uS]<\r><\n>
In: 1.822124 | Out: 0.957337 | 37[uS]<\r><\n>
In: 1.884956 | Out: 0.957337 | 37[uS]<\r><\n>
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**********************************************************************
CUBEMX i8 quantization
STM32F407 Deep Learning test!<\r><\n>
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