Update URLs to IntelLabs

IntelLabs · Nov 17, 2020 · 1e4ad56 · 1e4ad56
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diff --git a/.github/workflows/build_docs.yml b/.github/workflows/build_docs.yml
@@ -37,7 +37,6 @@ jobs:
         rm -rfv ./docs
         cp -rv ./docs-source/build/html ./docs
         touch ./docs/.nojekyll
-        cp CNAME ./docs/CNAME
 
     - name: Commit documentation changes
       run:  |

diff --git a/CNAME b/CNAME
diff --git a/README.md b/README.md
@@ -1,20 +1,20 @@
 <p align="center">
     <br>
-    <img src="https://raw.githubusercontent.com/NervanaSystems/nlp-architect/master/docs-source/source/assets/nlp_architect_logo_trans.png" width="400"/>
+    <img src="https://raw.githubusercontent.com/IntelLabs/nlp-architect/master/docs-source/source/assets/nlp_architect_logo_trans.png" width="400"/>
     <br>
 <p>
 <h2 align="center">
 A Deep Learning NLP/NLU library by <a href="https://www.intel.ai/research/">Intel® AI Lab</a>
 </h2>
 <p align="center">
-    <a href="https://github.com/NervanaSystems/nlp-architect/blob/master/LICENSE">
-        <img alt="GitHub" src="https://img.shields.io/github/license/NervanaSystems/nlp-architect.svg?color=blue&style=flat-square">
+    <a href="https://github.com/IntelLabs/nlp-architect/blob/master/LICENSE">
+        <img alt="GitHub" src="https://img.shields.io/github/license/IntelLabs/nlp-architect.svg?color=blue&style=flat-square">
     </a>
-    <a href="http://nlp_architect.nervanasys.com">
-        <img alt="Website" src="https://img.shields.io/website/http/nlp_architect.nervanasys.com.svg?down_color=red&down_message=offline&style=flat-square&up_message=online">
+    <a href="https://intellabs.github.io/nlp-architect">
+        <img alt="Website" src="https://img.shields.io/website/http/intellabs.github.io/nlp-architect.svg?down_color=red&down_message=offline&style=flat-square&up_message=online">
     </a>
-    <a href="https://github.com/NervanaSystems/nlp-architect/releases">
-        <img alt="GitHub release" src="https://img.shields.io/github/release/NervanaSystems/nlp-architect.svg?style=flat-square">
+    <a href="https://github.com/IntelLabs/nlp-architect/releases">
+        <img alt="GitHub release" src="https://img.shields.io/github/release/IntelLabs/nlp-architect.svg?style=flat-square">
     </a>
     <a href="https://pepy.tech/project/nlp-architect">
         <img src="https://pepy.tech/badge/nlp-architect">
@@ -25,10 +25,10 @@ A Deep Learning NLP/NLU library by <a href="https://www.intel.ai/research/">Inte
   <a href="#overview">Overview</a> |
   <a href="#models">Models</a> |
   <a href="#installing-nlp-architect">Installation</a> |
-  <a href="https://github.com/NervanaSystems/nlp-architect/tree/master/examples">Examples</a> <a href="http://nlp_architect.nervanasys.com/"></a> |
-  <a href="http://nlp_architect.nervanasys.com">Documentation</a> |
-  <a href="https://github.com/NervanaSystems/nlp-architect/tree/master/tutorials">Tutorials</a> |
-  <a href="http://nlp_architect.nervanasys.com/developer_guide.html">Contributing</a>
+  <a href="https://github.com/IntelLabs/nlp-architect/tree/master/examples">Examples</a> <a href="https://intellabs.github.io/nlp-architect/"></a> |
+  <a href="https://intellabs.github.io/nlp-architect">Documentation</a> |
+  <a href="https://github.com/IntelLabs/nlp-architect/tree/master/tutorials">Tutorials</a> |
+  <a href="https://intellabs.github.io/nlp-architect/developer_guide.html">Contributing</a>
 </h4>
 
 NLP Architect is an open source Python library for exploring state-of-the-art
@@ -74,7 +74,7 @@ pip install nlp-architect
 Includes core library, examples, solutions and tutorials:
 
 ```sh
-git clone https://github.com/NervanaSystems/nlp-architect.git
+git clone https://github.com/IntelLabs/nlp-architect.git
 cd nlp-architect
 pip install -e .  # install in developer mode
 ```
@@ -92,40 +92,40 @@ pip install .[all]
 
 NLP models that provide best (or near) in class performance:
 
-* [Word chunking](http://nlp_architect.nervanasys.com/tagging/sequence_tagging.html#word-chunker)
-* [Named Entity Recognition](http://nlp_architect.nervanasys.com/tagging/sequence_tagging.html#named-entity-recognition)
-* [Dependency parsing](http://nlp_architect.nervanasys.com/bist_parser.html)
-* [Intent Extraction](http://nlp_architect.nervanasys.com/intent.html)
-* [Sentiment classification](http://nlp_architect.nervanasys.com/sentiment.html#supervised-sentiment)
-* [Language models](http://nlp_architect.nervanasys.com/lm.html#language-modeling-with-tcn)
-* [Transformers](http://nlp_architect.nervanasys.com/transformers.html) (for NLP tasks)
+* [Word chunking](https://intellabs.github.io/nlp-architect/tagging/sequence_tagging.html#word-chunker)
+* [Named Entity Recognition](https://intellabs.github.io/nlp-architect/tagging/sequence_tagging.html#named-entity-recognition)
+* [Dependency parsing](https://intellabs.github.io/nlp-architect/bist_parser.html)
+* [Intent Extraction](https://intellabs.github.io/nlp-architect/intent.html)
+* [Sentiment classification](https://intellabs.github.io/nlp-architect/sentiment.html#supervised-sentiment)
+* [Language models](https://intellabs.github.io/nlp-architect/lm.html#language-modeling-with-tcn)
+* [Transformers](https://intellabs.github.io/nlp-architect/transformers.html) (for NLP tasks)
 
 Natural Language Understanding (NLU) models that address semantic understanding:
 
-* [Aspect Based Sentiment Analysis (ABSA)](http://nlp_architect.nervanasys.com/absa.html)
-* [Joint intent detection and slot tagging](http://nlp_architect.nervanasys.com/intent.html)
-* [Noun phrase embedding representation (NP2Vec)](http://nlp_architect.nervanasys.com/np2vec.html)
-* [Most common word sense detection](http://nlp_architect.nervanasys.com/word_sense.html)
-* [Relation identification](http://nlp_architect.nervanasys.com/identifying_semantic_relation.html)
-* [Cross document coreference](http://nlp_architect.nervanasys.com/cross_doc_coref.html)
-* [Noun phrase semantic segmentation](http://nlp_architect.nervanasys.com/np_segmentation.html)
+* [Aspect Based Sentiment Analysis (ABSA)](https://intellabs.github.io/nlp-architect/absa.html)
+* [Joint intent detection and slot tagging](https://intellabs.github.io/nlp-architect/intent.html)
+* [Noun phrase embedding representation (NP2Vec)](https://intellabs.github.io/nlp-architect/np2vec.html)
+* [Most common word sense detection](https://intellabs.github.io/nlp-architect/word_sense.html)
+* [Relation identification](https://intellabs.github.io/nlp-architect/identifying_semantic_relation.html)
+* [Cross document coreference](https://intellabs.github.io/nlp-architect/cross_doc_coref.html)
+* [Noun phrase semantic segmentation](https://intellabs.github.io/nlp-architect/np_segmentation.html)
 
 Optimizing NLP/NLU models and misc. optimization techniques:
 
-* [Quantized BERT (8bit)](http://nlp_architect.nervanasys.com/quantized_bert.html)
-* [Knowledge Distillation using Transformers](http://nlp_architect.nervanasys.com/transformers_distillation.html)
-* [Sparse and Quantized Neural Machine Translation (GNMT)](http://nlp_architect.nervanasys.com/sparse_gnmt.html)
+* [Quantized BERT (8bit)](https://intellabs.github.io/nlp-architect/quantized_bert.html)
+* [Knowledge Distillation using Transformers](https://intellabs.github.io/nlp-architect/transformers_distillation.html)
+* [Sparse and Quantized Neural Machine Translation (GNMT)](https://intellabs.github.io/nlp-architect/sparse_gnmt.html)
 
 Solutions (End-to-end applications) using one or more models:
 
-* [Term Set expansion](http://nlp_architect.nervanasys.com/term_set_expansion.html) - uses the included word chunker as a noun phrase extractor and NP2Vec to create semantic term sets
-* [Topics and trend analysis](http://nlp_architect.nervanasys.com/trend_analysis.html) - analyzing trending phrases in temporal corpora
-* [Aspect Based Sentiment Analysis (ABSA)](http://nlp_architect.nervanasys.com/absa_solution.html)
+* [Term Set expansion](https://intellabs.github.io/nlp-architect/term_set_expansion.html) - uses the included word chunker as a noun phrase extractor and NP2Vec to create semantic term sets
+* [Topics and trend analysis](https://intellabs.github.io/nlp-architect/trend_analysis.html) - analyzing trending phrases in temporal corpora
+* [Aspect Based Sentiment Analysis (ABSA)](https://intellabs.github.io/nlp-architect/absa_solution.html)
 
 ## Documentation
 
-Full library [documentation](http://nlp_architect.nervanasys.com/) of NLP models, algorithms, solutions and instructions
-on how to run each model can be found on our [website](http://nlp_architect.nervanasys.com/).
+Full library [documentation](https://intellabs.github.io/nlp-architect/) of NLP models, algorithms, solutions and instructions
+on how to run each model can be found on our [website](https://intellabs.github.io/nlp-architect/).
 
 ## NLP Architect library design philosophy
 
@@ -176,7 +176,7 @@ and NLP research communities are more than welcome.
 Contact the NLP Architect development team through Github issues or
 email: [email protected]
 
-[documentation]:http://nlp_architect.nervanasys.com
+[documentation]:https://intellabs.github.io/nlp-architect
 [TensorFlow]:https://www.tensorflow.org/
 [PyTorch]:https://pytorch.org/
 [Dynet]:https://dynet.readthedocs.io/en/latest/
diff --git a/docker/Dockerfile b/docker/Dockerfile
@@ -9,7 +9,7 @@ RUN python3 -m pip install --no-cache-dir --upgrade pip setuptools && \
     python3 -m pip install --no-cache-dir jupyter
 
 WORKDIR /workspace
-RUN git clone https://github.com/NervanaSystems/nlp-architect.git
+RUN git clone https://github.com/IntelLabs/nlp-architect.git
 RUN cd nlp-architect/ && \
     python3 -m pip install -e .[all,dev] && \
     python3 -m pip install -r server/requirements.txt && \

diff --git a/docs-source/Makefile b/docs-source/Makefile
@@ -1,5 +1,5 @@
 # ----------------------------------------------------------------------------
-# Copyright 2016 Nervana Systems Inc.
+# Copyright 2016 Intel Corp.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/docs-source/source/CONTRIBUTING.rst b/docs-source/source/CONTRIBUTING.rst
@@ -20,15 +20,15 @@ Contribution Process
 1. File an issue (to track your contribution):
 
    * Create an issue on GitHub:
-     https://github.com/NervanaSystems/nlp-architect/issues
+     https://github.com/IntelLabs/nlp-architect/issues
 
 2. Fork NLP Architect and/or update your checked out copy of 
    nlp-architect to ensure you have the
    most recent commits from the master branch, for example:
 
   .. code-block:: bash
 
-      git clone https://github.com/NervanaSystems/nlp-architect.git
+      git clone https://github.com/IntelLabs/nlp-architect.git
       cd nlp-architect
       git fetch origin
       git checkout master
@@ -71,7 +71,7 @@ Contribution Process
       git commit -m "Added new awesome functionality.  Closes issue #1"
       git push origin my_new_feature_branch
 
-7. Create a new `pull request <https://github.com/NervanaSystems/nlp-architect/pulls>`_
+7. Create a new `pull request <https://github.com/IntelLabs/nlp-architect/pulls>`_
    to get your feature branch merged into master for others to use.
    You'll first need to ensure your feature branch contains the latest changes from
    master.

diff --git a/docs-source/source/absa_solution.rst b/docs-source/source/absa_solution.rst
@@ -36,7 +36,7 @@ For more details see :doc:`ABSA <absa>`.
 
 Installing and Running
 ======================
-For instructions on running the end-to-end solution UI, see here: `ABSA Solution README <https://github.com/NervanaSystems/nlp-architect/tree/master/solutions/absa_solution#setup>`__
+For instructions on running the end-to-end solution UI, see here: `ABSA Solution README <https://github.com/IntelLabs/nlp-architect/tree/master/solutions/absa_solution#setup>`__
 
 
 Workflow and UI

diff --git a/docs-source/source/index.rst b/docs-source/source/index.rst
@@ -75,4 +75,4 @@
    nlp_architect API <generated_api/nlp_architect_api_index.rst>
    developer_guide.rst
 
-.. _https://github.com/NervanaSystems/nlp-architect: https://github.com/NervanaSystems/nlp-architect
+.. _https://github.com/IntelLabs/nlp-architect: https://github.com/IntelLabs/nlp-architect
diff --git a/docs-source/source/installation.rst b/docs-source/source/installation.rst
@@ -76,7 +76,7 @@ Install from source
 
 .. code:: bash
 
-    git clone https://github.com/NervanaSystems/nlp-architect.git
+    git clone https://github.com/IntelLabs/nlp-architect.git
     cd nlp-architect
     pip install -e .
 

diff --git a/docs-source/source/main.rst b/docs-source/source/main.rst
@@ -22,7 +22,7 @@ NLP Architect is an open source Python library for exploring state-of-the-art de
 
 The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab.
 
-NLP Architect can be downloaded from Github: https://github.com/NervanaSystems/nlp-architect
+NLP Architect can be downloaded from Github: https://github.com/IntelLabs/nlp-architect
 
 Overview
 ========

diff --git a/docs-source/source/quick_start.rst b/docs-source/source/quick_start.rst
@@ -35,7 +35,7 @@ From source
 
 .. code:: bash
 
-    git clone https://github.com/NervanaSystems/nlp-architect.git
+    git clone https://github.com/IntelLabs/nlp-architect.git
     cd nlp-architect
     pip install -e .  # install in development mode
 

diff --git a/docs-source/source/sparse_gnmt.rst b/docs-source/source/sparse_gnmt.rst
@@ -384,7 +384,7 @@ References
 .. _wmt16_en_de.sh: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/wmt16_en_de.sh
 .. _`WMT Shared Task: Machine Translation of News`: http://www.statmt.org/wmt16/translation-task.html
 .. _`Shared Task`: http://www.statmt.org/wmt16/translation-task.html
-.. _`Model Zoo`: http://nlp_architect.nervanasys.com/model_zoo.html
+.. _`Model Zoo`: https://intellabs.github.io/nlp-architect/model_zoo.html
 .. _`TensorFlow API`: https://www.tensorflow.org/api_docs/python/tf/quantize
 .. _`Sparse`: https://d2zs9tzlek599f.cloudfront.net/models/sparse_gnmt/gnmt_sparse.zip
 .. _`2x2 Block Sparse`: https://d2zs9tzlek599f.cloudfront.net/models/sparse_gnmt/gnmt_blocksparse2x2.zip
diff --git a/docs-source/source/static/install.js b/docs-source/source/static/install.js
@@ -20,7 +20,7 @@ new Vue({
         cmd.push("pip install nlp-architect")
       }
       if (this.form.source == "0") {
-        cmd.push("git clone https://github.com/NervanaSystems/nlp-architect.git<br>cd nlp-architect")
+        cmd.push("git clone https://github.com/IntelLabs/nlp-architect.git<br>cd nlp-architect")
       }
       if (this.form.source == "0" && this.form.inst_type == "0") {
         cmd.push("pip3 install -e .")

diff --git a/docs-source/source/tutorials.rst b/docs-source/source/tutorials.rst
@@ -45,10 +45,10 @@ If you don't have Jupyter installed, follow these instructions to install:
 
 List of tutorials
 -----------------
-- `Natural Language Question/Answering Systems <https://github.com/NervanaSystems/nlp-architect/blob/master/tutorials/Question_Answering/Natural_Language_Question_Answer_Systems.ipynb>`_
-- `Intent Extraction <https://github.com/NervanaSystems/nlp-architect/blob/master/tutorials/intent_extraction/intent_extraction_demo.ipynb>`_
-- `Named Entity Recognition <https://github.com/NervanaSystems/nlp-architect/blob/master/tutorials/ner/ner_demo.ipynb>`_
-- `NP Semantic Segmentation <https://github.com/NervanaSystems/nlp-architect/blob/master/tutorials/np_semantic_segmentation/np_semantic_segmentation_demo.ipynb>`_
-- `Sentiment Analysis <https://github.com/NervanaSystems/nlp-architect/blob/master/tutorials/sentiment/Deep_Learning_Sentiment_Demo.ipynb>`_
-- `NP2Vec <https://github.com/NervanaSystems/nlp-architect/blob/master/tutorials/NP2vec/NP2vec_training.ipynb>`_
-- `Term set expansion <https://github.com/NervanaSystems/private-nlp-architect/blob/master/tutorials/Term_Set_Expansion/term_set_expansion.ipynb>`_
+- `Natural Language Question/Answering Systems <https://github.com/IntelLabs/nlp-architect/blob/master/tutorials/Question_Answering/Natural_Language_Question_Answer_Systems.ipynb>`_
+- `Intent Extraction <https://github.com/IntelLabs/nlp-architect/blob/master/tutorials/intent_extraction/intent_extraction_demo.ipynb>`_
+- `Named Entity Recognition <https://github.com/IntelLabs/nlp-architect/blob/master/tutorials/ner/ner_demo.ipynb>`_
+- `NP Semantic Segmentation <https://github.com/IntelLabs/nlp-architect/blob/master/tutorials/np_semantic_segmentation/np_semantic_segmentation_demo.ipynb>`_
+- `Sentiment Analysis <https://github.com/IntelLabs/nlp-architect/blob/master/tutorials/sentiment/Deep_Learning_Sentiment_Demo.ipynb>`_
+- `NP2Vec <https://github.com/IntelLabs/nlp-architect/blob/master/tutorials/NP2vec/NP2vec_training.ipynb>`_
+- `Term set expansion <https://github.com/IntelLabs/private-nlp-architect/blob/master/tutorials/Term_Set_Expansion/term_set_expansion.ipynb>`_
diff --git a/docs/CNAME b/docs/CNAME
diff --git a/examples/chunker/README.md b/examples/chunker/README.md
@@ -15,7 +15,7 @@ In this example the sentence can be divided into 4 phrases, `The quick brown fox
 ## Documentation
 
 This model is based on the paper: [Deep multi-task learning with low level tasks supervised at lower layers](http://anthology.aclweb.org/P16-2038). \
-Full documentation of this example and the neural network model can be found here: [http://nlp_architect.nervanasys.com/chunker.html](http://nlp_architect.nervanasys.com/chunker.html)
+Full documentation of this example and the neural network model can be found here: [https://intellabs.github.io/nlp-architect/chunker.html](https://intellabs.github.io/nlp-architect/chunker.html)
 
 ## Dataset
 

diff --git a/examples/sparse_gnmt/README.md b/examples/sparse_gnmt/README.md
@@ -26,7 +26,7 @@ You can use the script [wmt16_en_de.sh](https://github.com/tensorflow/nmt/blob/m
 
 ## Results & Pre-Trained Models
 The following table presents some of our experiments and results.
-Furthermore, some of our pre-trained models are offered in the form of checkpoints in our [Model Zoo](http://nlp_architect.nervanasys.com/model_zoo.html).
+Furthermore, some of our pre-trained models are offered in the form of checkpoints in our [Model Zoo](https://intellabs.github.io/nlp-architect/model_zoo.html).
 You can use these models to [Run Inference with Pre-Trained Model](#run-inference-with-pre-trained-model) and evaluate them.
 
 | Model                      | Sparsity | BLEU| Non-Zero Parameters | Data Type |

diff --git a/licenses/neon-license.txt b/licenses/neon-license.txt
@@ -1,4 +1,4 @@
-https://github.com/NervanaSystems/neon/blob/master/LICENSE
+https://github.com/IntelLabs/neon/blob/master/LICENSE
 
 
  Apache License

diff --git a/licenses/ngraph_python-license.txt b/licenses/ngraph_python-license.txt
@@ -1,4 +1,4 @@
-https://github.com/NervanaSystems/ngraph-python/blob/master/LICENSE
+https://github.com/IntelLabs/ngraph-python/blob/master/LICENSE
 
 
   Apache License

diff --git a/server/angular-ui/dist/angular-ui/main.24b2853170a2cf16e1bc.js b/server/angular-ui/dist/angular-ui/main.24b2853170a2cf16e1bc.js
diff --git a/setup.py b/setup.py
@@ -76,7 +76,7 @@
     keywords="NLP NLU deep learning natural language processing tensorflow pytorch",
     author="Intel AI Lab",
     author_email="[email protected]",
-    url="https://github.com/NervanaSystems/nlp-architect",
+    url="https://github.com/IntelLabs/nlp-architect",
     license="Apache 2.0",
     python_requires=">=3.6.*",
     packages=find_packages(

diff --git a/solutions/absa_solution/README.md b/solutions/absa_solution/README.md
@@ -12,18 +12,18 @@ Producing sentiment knowledge at the aspect level (vs. sentence-level) provides
 
 ## Video Demo
 
-[![Video Demo](https://raw.githubusercontent.com/NervanaSystems/nlp-architect/master/solutions/absa_solution/assets/video.png)](https://drive.google.com/open?id=1BLk0xkjIOqyRhNy4UQEFQpDF_KR_NMAd)
+[![Video Demo](https://raw.githubusercontent.com/IntelLabs/nlp-architect/master/solutions/absa_solution/assets/video.png)](https://drive.google.com/open?id=1BLk0xkjIOqyRhNy4UQEFQpDF_KR_NMAd)
 *Figure 1*
 
 
 ## Workflow and UI
 
-![Workflow](https://raw.githubusercontent.com/NervanaSystems/nlp-architect/master/solutions/absa_solution/assets/absa_solution_workflow.png)  
+![Workflow](https://raw.githubusercontent.com/IntelLabs/nlp-architect/master/solutions/absa_solution/assets/absa_solution_workflow.png)  
 *Figure 2*
 
 
 
-![Workflow](https://raw.githubusercontent.com/NervanaSystems/nlp-architect/master/solutions/absa_solution/assets/absa_solution_ui_3.png)
+![Workflow](https://raw.githubusercontent.com/IntelLabs/nlp-architect/master/solutions/absa_solution/assets/absa_solution_ui_3.png)
 *Figure 3*  
 
 
@@ -54,7 +54,7 @@ source absa_env/bin/activate
 - **Clone and install**:
 
 ```bash
-git clone https://github.com/NervanaSystems/nlp-architect.git
+git clone https://github.com/IntelLabs/nlp-architect.git
 pip install -U pip
 pip install -e nlp-architect
 pip install -r nlp-architect/solutions/absa_solution/requirements.txt

diff --git a/solutions/absa_solution/ui.py b/solutions/absa_solution/ui.py
@@ -74,7 +74,7 @@ def _create_header(train_dropdown, inference_dropdown, text_status) -> layouts.R
     """Utility function for creating and styling the header row in the UI layout."""
 
     architect_logo = Div(
-        text='<a href="http://nlp_architect.nervanasys.com"> <img border="0" '
+        text='<a href="https://intellabs.github.io/nlp-architect"> <img border="0" '
         'src="style/nlp_architect.jpg" width="200"></a> by Intel® AI Lab',
         style={
             "margin-left": "500px",