Project Name change from "Intel Low Precision Inference Toolkit" to "Intel Low Precision Optimization Tool".

Author: ftian1

CONTRIBUTING.md

@@ -1,6 +1,6 @@
 # Contributing guidelines
-If you have improvements to lp-inference-kit, send us your pull requests for
-[review](https://github.com/intel/lp-inference-kit/pulls)! For those
+If you have improvements to iLiT, send us your pull requests for
+[review](https://github.com/intel/lp-opt-tool/pulls)! For those
 just getting started, Github has a
 [how to](https://help.github.com/articles/using-pull-requests/).
 
@@ -12,8 +12,8 @@ list.
 - Changes are consistent with the Python [Coding Style](https://github.com/google/styleguide/blob/gh-pages/pyguide.md).
 - Use pylint to check your Python code
 - Use flake8 and autopep8 to make Python code clean 
-- Add unit tests in [Unit Tests](https://github.com/intel/lp-inference-kit/tree/master/tests) to cover the code you would like to contribute. 
-- Run [Unit Tests](https://github.com/intel/lp-inference-kit/tree/master/tests). 
+- Add unit tests in [Unit Tests](https://github.com/intel/lp-opt-tool/tree/master/tests) to cover the code you would like to contribute.
+- Run [Unit Tests](https://github.com/intel/lp-opt-tool/tree/master/tests).
 
 ## Pull Request Template
 ### Change Summary

README.md

@@ -1,7 +1,7 @@
-Intel® Low Precision Inference Toolkit (iLiT)
+Intel® Low Precision Optimization Tool (iLiT)
 =========================================
 
-Intel® Low Precision Inference Toolkit (iLiT) is an open-source python library which is intended to deliver a unified low-precision inference interface cross multiple Intel optimized DL frameworks on both CPU and GPU. It supports automatic accuracy-driven tuning strategies, along with additional objectives like performance, model size, or memory footprint. It also provides the easy extension capability for new backends, tuning strategies, metrics and objectives.
+Intel® Low Precision Optimization Tool (iLiT) is an open-source python library which is intended to deliver a unified low-precision inference interface cross multiple Intel optimized DL frameworks on both CPU and GPU. It supports automatic accuracy-driven tuning strategies, along with additional objectives like performance, model size, or memory footprint. It also provides the easy extension capability for new backends, tuning strategies, metrics and objectives.
 
 > **WARNING**
 >
@@ -27,8 +27,8 @@ comprehensive step-by-step instructions of how to enable iLiT on sample models.
 # Install from source 
 
   ```Shell
-  git clone https://github.com/intel/lp-inference-kit.git
-  cd lp-inference-kit
+  git clone https://github.com/intel/lp-opt-tool.git
+  cd lp-opt-tool
   python setup.py install
   ```
 
@@ -84,7 +84,7 @@ The followings are the examples integrated with iLiT for auto tuning.
 # Support
 
 Please submit your questions, feature requests, and bug reports on the
-[GitHub issues](https://github.com/intel/lp-inference-kit/issues) page. You may also reach out to [email protected].
+[GitHub issues](https://github.com/intel/lp-opt-tool/issues) page. You may also reach out to [email protected].
 
 # Contributing
 
@@ -97,7 +97,7 @@ to improve the library:
  [code contribution guidelines](CONTRIBUTING.md#code_contribution_guidelines)
  and [coding style](CONTRIBUTING.md#coding_style).
 * Ensure that you can run all the examples with your patch.
-* Submit a [pull request](https://github.com/intel/lp-inference-kit/pulls).
+* Submit a [pull request](https://github.com/intel/lp-opt-tool/pulls).
 
 For additional details, see [contribution guidelines](CONTRIBUTING.md).
 
@@ -132,8 +132,8 @@ If you use iLiT in your research or wish to refer to the tuning results publishe
 ```
 @misc{iLiT,
   author =       {Feng Tian, Chuanqi Wang, Guoming Zhang, Penghui Cheng, Pengxin Yuan, Haihao Shen, and Jiong Gong},
-  title =        {Intel® Low Precision Inference Toolkit},
-  howpublished = {\url{https://github.com/intel/lp-inference-kit}},
+  title =        {Intel® Low Precision Optimization Tool},
+  howpublished = {\url{https://github.com/intel/lp-opt-tool}},
   year =         {2020}
 }
 ```

setup.py

@@ -6,12 +6,12 @@
     version="1.0a0",
     author="Intel MLP/MLPC Team",
     author_email="[email protected], [email protected], [email protected], [email protected], [email protected], [email protected]",
-    description="Repository of intel low precision inference toolkit",
+    description="Repository of Intel Low Precision Optimization Tool",
     long_description=open("README.md", "r", encoding='utf-8').read(),
     long_description_content_type="text/markdown",
     keywords='quantization, auto-tuning, post-training static quantization, post-training dynamic quantization, quantization-aware training, tuning strategy',
     license='',
-    url="https://github.intel.com/intel/lp-inference-kit",
+    url="https://github.com/intel/lp-opt-tool",
     packages = find_packages(),
     package_dir = {'':'.'},
     package_data={'': ['*.py', '*.yaml']},

third-party-programs.txt

@@ -1,4 +1,4 @@
-Intel� Low Precision Inference Toolkit Third Party Programs File
+Intel� Low Precision Optimization Tool Third Party Programs File
 
 This file contains the list of third party software ("third party programs")
 contained in the Intel software and their required notices and/or license