Comments (2)
mengna0707
commented on June 21, 2024
3
Hi CNugteren，thank you very much for your contact information.
I have sent an email to inquire about relevant matters and look forward to receiving the reply.
from compute-engine.
CNugteren
commented on June 21, 2024
Hello mengna0707. Thank you for your interest in the Larq Compute Engine.
The open-source version of the Larq Compute Engine does not support deployment on Cortex-M. If you are interested in inference on Cortex-M, please contact our sales team at [email protected] and we'll get into contact with you. In your email please provide relevant details such as the kinds of neural networks you are planning to use, the exact target board(s) and an estimation of the amount of devices you are planning to deploy onto.
from compute-engine.
Related Issues (20)
- Upgrade TensorFlow dependency to 2.6 HOT 3
- Automatic release builds for benchmarking binaries are broken HOT 2
- Tensor transform triggers dequantization HOT 6
- Error on import HOT 2
- Select indirect BGEMM kernels - Benchmarking grouped binary convolutions HOT 3
- LCEInterpreter and converter design HOT 1
- core dumped when number of threads is larger than 2 HOT 3
- Benchmarking custom model HOT 3
- Int8 quantization for microcontroller HOT 13
- Failed import 'org.tensorflow.lite.DataType' on Android project HOT 8
- `convert_keras_model()` does not work as expected for BinaryDenseNet37 Dilated and XNORNet HOT 1
- DoReFa quantizer with higher number of MACs/Ops, Grouped convs as custom ops on LCE 0.7.0 HOT 3
- Get Operator-wise Profiling Results HOT 1
- Error while performing benchmarking HOT 44
- Bool input tensor HOT 7
- extra model size induced by non-parameter layer HOT 1
- Fix Android benchmarker build
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