Can you install and run fastai in raspberry pi and coral?

[Xalsar]

Hi @BobMcDear great answer. I asked the FastAI discord server and found very interesting resources (thanks to discord user @ Roshi).

Basically they guide you on how to convert the pytorch model with ONNX so you can use it with Coral TPU.

Fastai Model conversion to ONNX, TF, CoreML, Caffe2, TFlite

Here I would like to share a simple notebook as a walkthrough for model conversion. Some notes: TF to TFlite is not very mature when coming from PyTorch since sometimes operations can’t be expressed as native TF ops or TF lite only supports NHWC data format. Fix is to just add a permute() to beginning of your model for converting NHWC to NCHW which can be used by the actual PyTorch model. Other than TFLite - ONNX, TF, CoreML, Caffe2 seems to work fine. Probably swift would cross out all the a…

Edge TPU Compiler | Coral

As far as I have read (but I am a very beginner), ONNX is not very complex to use to convert pytorch models but I am probably wrong for what you say.

Example code I found to process Pytorch model:

// Code written by @ Roshi
torch.onnx.export(
    learn.model, # the model
    torch.randn(1, 3, 224, 224, device='cpu'), #Dummy input
    "PATH_TO_PRINT_MODEL", #Name your model and where you want to put it
    input_names=["input"], # No clue
    output_names=['output'] #Yes...
)

I think NVIDIA products may be more suitable in this case. I will have to study jetson nano in more detail. Do you know if its compatible with Raspberry Pi or do I need the developer kit?

And thank you very much.