Comments (3)
godhj93
commented on June 21, 2024
2
I tested it again and It works well on AGX Xavier!
Thanks!
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CNugteren
commented on June 21, 2024
1
Thanks for reporting the issue. Actually, we noticed this bug a while ago but forgot to report an issue, sorry about that.
The good news is that this should already be fixed in the latest main branch since 5 days, see #727. We will soon release a new version of the larq-compute-engine with the fixed binaries. Until then you can compile them yourself from the latest sources, e.g.:
bazelisk build //larq_compute_engine/tflite/benchmark:lce_benchmark_model --config=aarch64 -c opt --copt=-O3
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CNugteren
commented on June 21, 2024
1
We have just made a new release (v0.7.0), which has pre-compiled binaries that should no longer suffer from this issue. Could you try it out and confirm by closing this issue? Thanks!
from compute-engine.
Related Issues (20)
- Upgrade TensorFlow dependency to 2.6 HOT 3
- Automatic release builds for benchmarking binaries are broken HOT 2
- Deployment on Cortex-M 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
- 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
- Larq Compute Engine seems incompatible with tensorflow-lite-task-vision on Android (using the latest tensorflow lite demo code) HOT 2
- Dorefa model size and behavior with full precision model and ste_sign model HOT 13
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