ONNC-bench is a Python wrapper of ONNC
Project description
ONNC-bench
ONNC-bench is a Python wrapper of ONNC
Installation
Using pip
pip install onnc-bench
Python API Example
Here is an example to show how to use ONNC python API
from onnc.bench import login, Project
# Setup your ONNC API key
api_key = "Your API KEY"
login(api_key)
# Instantiate a projct
project = Project('experiment-1')
# Add a model and its coresponding calibration samples
project.add_model('path/to/model', 'path/to/samples')
# Compile the model and optmize to `CMSIS-NN` backend
project.compile(target='CMSIS-NN-DEFAULT')
# Save the compiled model
deployment = project.save('./output')
print(deployment.report)
{
'sram_size': 2490,
'flash_size': 101970
}
The report shows we need: 2,490 bytes of SRAM 101,970 bytes of ROM to run this model on a CortexM device.
Please Check https://docs-tinyonnc.skymizer.com/index.html for the full documents.
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