Run steps

Run from base directory.

source scripts/setup_paths.sh

• python3 benchmarks/src/generate.py --tier L1 --task example_task --output-path tmp
• python3 benchmarks/src/generate.py --tier L1 --task ExampleTask --output-path tmp --param1 "range(1,10)" --param2 "range(1, 10)"

Installation Steps

Make a new mbed program for your MCU.

mbed new <my_name>
cd <my_name>

Then we have to add the uTensor library.

mbed add https://www.github.com/uTensor/uTensor

After writing your main.cpp file, you can just compile.

mbed compile -m <boardname> -t GCC_ARM --profile uTensor/build_profile/release.json

If it complains about a profile, then try running it without one.

mbed compile -m <boardname> -t GCC_ARM

The official docs for the mbed cli are here for reference. The easiest way to see the correct boardname is by using mbed detect. For example, the NUCLEO F767ZI board has the target NUCLEO_F767ZI.

## Troubleshooting

### mbed sterm doesn't work

Make sure that the current user is in dialout if using Ubuntu.

```bash
sudo adduser $(whoami) dialout

Serialization Error in TF

If the tensorflow stuff gives you an error with serialization:

TypeError: __new__() got an unexpected keyword argument 'serialized_options'

It may be an issue with the protobuf version. So make sure you have a good protobuf version.

pip uninstall protobuf
pip install protobuf

and this fixed the issue for me.

Mac issues with const struct timeval

Sometimes you may get this compiler error:

mbed_rtc_time.cpp@111,7: invalid use of incomplete type 'struct timeval'

Try installing the toolchain available here, I think it's an issue with the default compiler installed through brew.

Then, make sure that the cross compiler version is OK. I think version 6 works the best, rather than version 7.

brew tap ArmMbed/homebrew-formulae
brew install arm-none-eabi-gcc 

If this doesn't install version 6, then try using the official website and downloading the version 6 binary here.

Then, make sure that in your develop.json or release.json that you compile C++ using gnu++11 rather than c++11. This is probably the root cause of the issue, the GNU extensions aren't on by default.

Compilation Issues with RELU mismatched templates

If you have an old version of utensor_cgen you might get the following error:

error: wrong number of template arguments (3, should be 2)
     ctx.push(new ReluOp<uint8_t, float, uint8_t>(),

Just update the version of utensor_cgen. I went to version 0.3.5.

Sub not supported operation in uTensor

Make sure you don't use Subtract in Tensorflow when training, and only use Add. If you use default layers, you might have to implement them from scratch or use a different version of Tensorflow.