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Xilinx / Vitis-AI

Vitis AI is Xilinx’s development stack for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards.
https://www.xilinx.com/ai
Apache License 2.0
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Import slim model from pruning to quantization #1039

Open Sinelemouk opened 1 year ago

Sinelemouk commented 1 year ago

Hello Xilinx,

Thank you for alowing me to play with your tool,

I succesfully create a slim_model with the vitis-ai-optimizer_pytorch. However, if i try to to the quantization with this conda env, i get the folowing error : 

  File "/opt/vitis_ai/conda/envs/vitis-ai-optimizer_pytorch/lib/python3.7/site-packages/nndct_shared/compile/xgraph.py", line 24, in <module>
    raise Exception('please install xir package')

In the reverse, i can't load the slim_model in the vitis-ai-pytorch as describe in the ug1333 because of the folowing error:

ImportError: cannot import name 'get_pruning_runner' from 'pytorch_nndct' (/opt/vitis_ai/conda/envs/vitis-ai-pytorch/lib/python3.7/site-packages/pytorch_nndct/__init__.py)

How can i load the pruned model for the quantization step? Is there any exemple?

I am using the "With Pruning API" for loading the slim_model.

method = 'iterative' # or 'one_step'
runner = get_pruning_runner(model, input_signature, method)
slim_model = runner.prune(removal_ratio=0.2, mode='slim')
slim_model.load_state_dict(torch.load('model_pruned.pth'))

The Without Pruning API doesent work for me. The model.json file does not fit the slim_model_from_state_dict_and_pruning_info function you provided.

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}

Thanks

akuzminski commented 1 year ago

Is there any update on this? I have the same problem because weight shapes changed.