This project is base on AAML_MCU_TinyML_Lab
- import
train_with_cifar10.ipynbon colab - run the code and it will start training
- after training , download
resnet_v1_eembc.tflite&resnet_v1_eembc_quant.tflite
- import
Lab1_2_3/basic_compile.ipynb(basic) orLab3_4/cmsis_compile.ipynb(cmsis) - upload the model (cmsis can only run with quant model)
- modify the
model_path = ""to your model path - run the code and it will compile the project
- after compile , download the .bin file
- connect the F767ZI with your computer
- download termite
- open termite & set the baod rate
115200 - copy the .bin file into F767ZI
- see the output in termite
| NUCLEO_F767ZI | TFLM | TFLM + int8 Quant | TFLM + int8 Quant + cmsis |
|---|---|---|---|
| Time(us) | 4,634,854 | 4,672,161 | 437,600 |
| Arena Size(bytes) | 201,696 | 54,452 | 55,108 |
| DISCO_F746NG | TFLM | TFLM + int8 Quant | TFLM + int8 Quant + cmsis |
|---|---|---|---|
| Time(us) | 4,625,590 | 5,747,635 | 428,668 |
| Arena Size(bytes) | 201,696 | 54,452 | 55,108 |
- change the model architecture (add / remove some layer) in
train_with_cifar10.ipynb - compare the new model's(add/remove)
Inference Time,Arena size,Model sizewith origin one in non-quant / quant / quant + CMSIS condition
| Method | Time(us) | Model size | Arena Size |
|---|---|---|---|
| remove layer float | - | - | - |
| remove layer quant | - | - | - |
| remove layer quant + CMSIS | - | - | - |
| origin float | - | - | - |
| origin quant | - | - | - |
| origin quant + CMSIS | - | - | - |
| add layer float | - | - | - |
| add layer quant | - | - | - |
| add layer quant + CMSIS | - | - | - |
| Method | Time(us) | Model size | Arena Size |
|---|---|---|---|
| float | - | - | - |
| quant | - | - | - |
| quant + CMSIS | - | - | - |
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent