Comments (2)
OLive is a pure Python package. So there isn't any issue to build OLive package for python 3.9. However, to use OLive inference optimization service, user also needs to install onnxruntime with all EPs and mlperf_loadgen. These two packages only support Python from 3.6 to 3.8. We are working to support Python 3.9 from onnxruntime 1.10 update.
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Close this issue. Free to reopen for any issue.
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Related Issues (20)
- [Bug]: whisper gpu does not consume gpu resources HOT 1
- [Bug]: OnnxQuantization HOT 8
- [Bug]: No model is selected. Skip packaging output artifacts. whisper HOT 8
- [Question] Whisper GPU mobile NNAPI HOT 1
- [Bug]: ort-nightly-gpu not installing HOT 4
- [Bug]: `ActivationSymmetric` default is not enforced in Vitis AI quantizer HOT 6
- [Bug]: Vitis AI quantizer with symmetric uint8 activation wrongfully hard-codes `zero_point=0` HOT 5
- model_type field required (type=value_error.missing) HOT 5
- [Bug]: Vitis quantization doesn't work with ORT 1.16.
- [FR]: quantize a fine-tuned model HOT 7
- [FR]: Enable optimization by onnxruntime on stable_diffusion.py HOT 5
- [Bug]: ImportError: cannot import name 'load_model' from ' 6800xt model HOT 2
- CUDAExecutionProvider is not in the session providers HOT 3
- [Bug]: Running Olive with ROCMExecutionProvider. HOT 6
- [FR]: About path. HOT 2
- [FR]: Whisper int4 support HOT 2
- [Bug]: TypeError: __init__() got an unexpected keyword argument 'io_config' HOT 9
- [FR]: Any roadmap for arm architecture HOT 1
- Add ONNXRuntimePackages builds for Java HOT 5
- [FR]: Hope Olive supports Pydantic version 2.0 or higher HOT 3
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