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https://github.com/open-mmlab/mmdeploy.git
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ea0a9e5d43
* feat(tools): add onnx2ncnn_quant_table * feat(tools): add quantization image dataset * feat(tools): add image dataset * feat(tools/deploy.py): support quant * fix(CI): lint * fix(CI): format * docs(zh_cn): add quantization usage * docs(zh_cn): add benchmark * feat(tools): add onnx2ncnn_quant_table * docs(zh_cn): add more test result * CI(github): add quant script * CI(.github/scripts): add test quant * fix(CI): remove pushd and popd * feat(CI): debug * fix(CI): path error * fix(CI): fix path * fix(CI): install wget * fix(CI): review advices * improvement(mmdeploy): review advice * fix(tools): rename to onnx2ncnn_quant_table.py * improvement(tools): rename file * improvement(test): remove useless * fix(tools/quant_image_dataset): remove loadFile in test.pipeline * docs(quantization.md): update description * fix(CI): protobuf version * fix(CI): pip install * docs(quantization): review advice * fix(CI): revert mmcv version * fix(CI): udpate pb version * fix(CI): update
60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import os
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import subprocess
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# list of tuple: onnx filename, download_url and model_config.
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CONFIGS = [
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[
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'hrnet.onnx',
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'https://media.githubusercontent.com/media/tpoisonooo/mmdeploy-onnx2ncnn-testdata/main/hrnet.onnx', # noqa: E501
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'~/mmclassification/configs/hrnet/hrnet-w18_4xb32_in1k.py',
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],
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[
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'resnet18.onnx',
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'https://media.githubusercontent.com/media/tpoisonooo/mmdeploy-onnx2ncnn-testdata/main/resnet18.onnx', # noqa: E501
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'~/mmclassification/configs/resnet/resnet18_8xb16_cifar10.py',
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],
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[
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'mobilenet-v2.onnx',
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'https://media.githubusercontent.com/media/tpoisonooo/mmdeploy-onnx2ncnn-testdata/main/mobilenet-v2.onnx', # noqa: E501
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'~/mmclassification/configs/mobilenet_v2/mobilenet-v2_8xb32_in1k.py',
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]
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]
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def prepare_dataset():
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DATASET = (
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'dataset',
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'https://media.githubusercontent.com/media/tpoisonooo/mmdeploy-onnx2ncnn-testdata/main/dataset.tar' # noqa: E501
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) # noqa: E501
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os.system('wget {}'.format(DATASET[1]))
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os.system('tar xvf dataset.tar')
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return DATASET[0]
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def main():
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"""test `tools/onnx2ncnn_quant_table.py`
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First quantize onnx model to ncnn with ppq.
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"""
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data_dir = prepare_dataset()
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for conf in CONFIGS:
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model = conf[0]
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os.system('wget {}'.format(conf[1]))
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model_cfg = conf[2]
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deploy_cfg = 'configs/mmcls/classification_ncnn-int8_static.py'
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quant_cmd = [
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'python3', 'tools/onnx2ncnn_quant_table.py', '--onnx', model,
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'--deploy-cfg', deploy_cfg, '--model-cfg', model_cfg, '--out-onnx',
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'quant.onnx', '--out-table', 'ncnn.table', '--image-dir', data_dir
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]
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print(' '.join(quant_cmd))
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print(subprocess.call(quant_cmd))
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if __name__ == '__main__':
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main()
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