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update main page (#1973)
Signed-off-by: chensuyue <[email protected]>
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.azure-pipelines/scripts/ut/run_itrex.sh

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@@ -19,6 +19,8 @@ sed -i '/neural-compressor.git/d' /intel-extension-for-transformers/tests/requir
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pip install -r /intel-extension-for-transformers/tests/requirements.txt
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# workaround
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pip install onnx==1.15.0
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echo "pip list itrex ut deps..."
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pip list
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LOG_DIR=/neural-compressor/log_dir
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mkdir -p ${LOG_DIR}
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ut_log_name=${LOG_DIR}/ut_itrex.log

.azure-pipelines/ut-3x-pt-fp8.yml

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dockerConfigName: "commonDockerConfig"
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utScriptFileName: "3x/run_3x_pt_fp8"
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uploadPath: $(UPLOAD_PATH)
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utArtifact: "ut_3x_pt_fp8"
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utArtifact: "ut_3x"
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- stage: Torch_habana_baseline
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displayName: Torch 3x Habana FP8 baseline
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dockerConfigName: "gitCloneDockerConfig"
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utScriptFileName: "3x/run_3x_pt_fp8"
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uploadPath: $(UPLOAD_PATH)
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utArtifact: "ut_3x_pt_fp8_baseline"
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utArtifact: "ut_3x_baseline"
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- stage: Coverage
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displayName: "Coverage Compare"

README.md

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Intel® Neural Compressor
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===========================
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<h3> An open-source Python library supporting popular model compression techniques on all mainstream deep learning frameworks (TensorFlow, PyTorch, ONNX Runtime, and MXNet)</h3>
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<h3> An open-source Python library supporting popular model compression techniques on all mainstream deep learning frameworks (TensorFlow, PyTorch, and ONNX Runtime)</h3>
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[![python](https://img.shields.io/badge/python-3.8%2B-blue)](https://github.com/intel/neural-compressor)
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[![version](https://img.shields.io/badge/release-3.0-green)](https://github.com/intel/neural-compressor/releases)
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---
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<div align="left">
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Intel® Neural Compressor aims to provide popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as [TensorFlow](https://www.tensorflow.org/), [PyTorch](https://pytorch.org/), [ONNX Runtime](https://onnxruntime.ai/), and [MXNet](https://mxnet.apache.org/),
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Intel® Neural Compressor aims to provide popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as [TensorFlow](https://www.tensorflow.org/), [PyTorch](https://pytorch.org/), and [ONNX Runtime](https://onnxruntime.ai/),
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as well as Intel extensions such as [Intel Extension for TensorFlow](https://github.com/intel/intel-extension-for-tensorflow) and [Intel Extension for PyTorch](https://github.com/intel/intel-extension-for-pytorch).
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In particular, the tool provides the key features, typical examples, and open collaborations as below:
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docs/source/CONTRIBUTING.md

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| Code Scan | Bandit/CopyRight/DocStyle/SpellCheck | PASS |
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| [DCO](https://github.com/apps/dco/) | Use `git commit -s` to sign off | PASS |
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| Unit Test | Pytest scripts under [test](/test) | PASS (No failure, No core dump, No segmentation fault, No coverage drop) |
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| Model Test | Pytorch + TensorFlow + ONNX Runtime + MXNet | PASS (Functionality pass, FP32/INT8 No performance regression) |
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| Model Test | Pytorch + TensorFlow + ONNX Runtime | PASS (Functionality pass, FP32/INT8 No performance regression) |
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## Support
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