nnio 0.3.1

Neural network inference on accelerators simplified

Please refer to the project's documentation.

What is it

nnio is a light-weight python package for easily running neural networks.

It supports running models on CPU as well as some of the edge devices:

• Google USB Accelerator
• Intel Compute Stick
• Intel integrated GPUs

For each device there exists an own library and a model format. We wrap all those in a single well-defined python package.

Look at this simple example:

import nnio

# Create model and put it on a Google Coral Edge TPU device
model = nnio.EdgeTPUModel(
    model_path='path/to/model_quant_edgetpu.tflite',
    device='TPU',
)
# Create preprocessor
preproc = nnio.Preprocessing(
    resize=(224, 224),
    batch_dimension=True,
)

# Preprocess your numpy image
image = preproc(image_rgb)

# Make prediction
class_scores = model(image)

nnio was developed for the Fast Sense X microcomputer. It has six neural accelerators, which are all supported by nnio:

• 3 x Google Coral Edge TPU
• 2 x Intel VPU
• an integrated Intel GPU

More usage examples can be found in the documentation.