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Updated installation instructions for on-device training package #192
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What do you mean update the notebook to the latest 1.18.1 version? Are you running into issues with running the notebook with 1.18.1? The README for the masked language modeling example already includes the updated installation instructions for ONNXRuntime, and this example was written for CPU EP only. |
The whole problem with onnxruntime-training is lack of specific information on requirements for CUDA 12.* and lack of testing that when using c# |
I'll update the notebook & add a requirements.txt file for the on-device training example. We can add adding a CUDA C# example to the backlog. I understand your frustration with the lack of documentation and we do need to improve ONNXRuntime documentation, but creating good documentation and examples also takes time. |
@carzh |
Ah, I gave a try, and did not run into any issues with that import line. What error do you run into and with what version of ONNXRuntime package? (ie, are you using onnxruntime-training-cpu?) |
I can not use python to upgrade onnxruntime-training from 1.15.1 to 1.18.1 The link to download the windows version is hard to find mobilebert-uncased.ckpt is not created. Only checkpoint file is written. |
@GeorgeS2019 The link to download the windows version is available at onnxruntime.ai. All the documentation should point to that installation table. Try the following: pip uninstall onnxruntime-training -y
python -m pip install cerberus flatbuffers h5py numpy>=1.16.6 onnx packaging protobuf sympy setuptools>=41.4.0
pip install -i https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT/pypi/simple/ onnxruntime-training-cpu --no-cache-dir I appended the no-cache-dir flag to ensure that pip doesn't pick up on any locally cached onnxruntime-training python packages. |
I managed to download onnxruntime-training python package for windows: 1.18.0 Problem1: string checkpointPath = Path.Combine(parentDir, "training_artifacts", "mobilebert-uncased.ckpt"); |
Use the most up-to-date package unless the example specifies otherwise. The latest release includes CUDA 12 support, but CUDA 12 is not supported for all configurations of ORT, as it looks like you've discovered. For example, on-device training with Python for Linux supports CUDA 12, but on-device training with Python for Windows does not. The easiest way to check if a configuration supports CUDA 12 is with the installation table on onnxruntime.ai.
The README specifies to use the python package for CPU. The C# example was written for CPU EP, and not CUDA. I'll try reproducing the issues you are running into later today and I'll push some updates to make it clearer that the masked language modeling example is for CPU. |
Any update? |
To reflect the updated installation instructions for installing onnxruntime for training. Also adds requirements.txt for mobilebert example
Addresses ONNXRuntime issue #21149