dynamic quantization: quantize fp32 weight to int8 during quantization phase , compute quant params (scale and zero point) on the fly which will increase performance overhead when doing inference but its accurac
quantize_static(model_name, quantize_name, calibration_data_reader=DataReader(x, x_lengths, scales), quant_format=QuantFormat.QDQ) File "/home/mllopart/PycharmProjects/ttsAPI/venv/lib/python3.10/site-packages/onnxruntime/quantization/quantize.py", line 406, in quantize_static quantizer.quantize_...
Our second optimization step is quantization. Again, ONNX Runtime provides an excellent utility for this. We’ve used both quantize_dynamic() and quantize_static() in production, depending on our desired balance of speed and accuracy for a specific model. Inference Once we have an optimized...
git clone --recursive https://github.com/microsoft/onnxruntime Specify the CUDA compiler, or add its location to the PATH. Cmake can't automatically find the correct nvcc if it's not in the PATH. export CUDACXX="/usr/local/cuda/bin/nvcc" or: export PATH="/usr/local/cuda/bin:$...
git clone --recursive https://github.com/microsoft/onnxruntime Specify the CUDA compiler, or add its location to the PATH. Cmake can't automatically find the correct nvcc if it's not in the PATH. export CUDACXX="/usr/local/cuda/bin/nvcc" or: export PATH="/usr/local/cuda/bin:$...
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File "/usr/local/lib/python3.8/dist-packages/onnxruntime/quantization/quantize.py", line 435, in quantize_static calibrator.collect_data(calibration_data_reader) File "/usr/local/lib/python3.8/dist-packages/onnxruntime/quantization/calibrate.py", line 304, in collect_data self.intermediate_outpu...
Remove two lines in the Dockerfile for Github Codespace (microsoft#12278 Jul 22, 2022 .gdn Update win-ci-pipeline.yml: enable xnnpack tests (microsoft#16244) Jun 15, 2023 .github [CPU EP] Int4 support for QuantizeLinear, DequantizeLinear, and Trans… May 31, 2024 .pipelines Upgrade ESRP...
Additional contrib op support: SimplifiedLayerNormalization, SkipSimplifiedLayerNormalization, QLinearAveragePool, MatMulIntegerToFloat, GroupQueryAttention, DynamicQuantizeMatMul, and QAttention. Mobile Improved performance of ARM64 4-bit quantization. ...
"homepage": "https://github.com/microsoft/onnxruntime", "license": "MIT", "supports": "windows & !x86 & !uwp & !static & !arm" "supports": "windows & !x86 & !uwp & !static & !arm", "dependencies": [ { "name": "onnxruntime", "features": [ "cuda" ] } ] } 70 chan...