Fixed S3 links

doc/source/model_zoo.rst

@@ -30,12 +30,12 @@ NLP Architect Model Zoo
         | `2x2 block sparse model <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/sparse_gnmt/gnmt_blocksparse2x2.zip>`_
    * - :doc:`Intent Extraction <intent>`
      - A :py:class:`MultiTaskIntentModel <nlp_architect.models.intent_extraction.MultiTaskIntentModel>` intent extraction and slot tagging model, trained on SNIPS NLU dataset
-     - | `model <https://s3-us-west-2.amazonaws.com/models/intent/model.h5>`_
-       | `params <https://s3-us-west-2.amazonaws.com/models/intent/model_info.dat>`_
+     - | `model <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/intent/model.h5>`_
+       | `params <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/intent/model_info.dat>`_
    * - :doc:`Named Entity Recognition <ner_crf>`
      - A :py:class:`NERCRF <nlp_architect.models.ner_crf.NERCRF>` model trained on CoNLL 2003 dataset
-     - | `model <https://s3-us-west-2.amazonaws.com/models/ner/model.h5>`_
-       | `params <https://s3-us-west-2.amazonaws.com/models/ner/model_info.dat>`_
+     - | `model <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/ner/model.h5>`_
+       | `params <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/ner/model_info.dat>`_
    * - :doc:`Dependency parser <bist_parser>`
      - Graph-based dependency parser using BiLSTM feature extractors
      - `model <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/dep_parse/bist-pretrained.zip>`_

doc/source/term_set_expansion.rst

@@ -75,20 +75,19 @@ size, min_count, window and hs hyperparameters. Please refer to the np2vec modul
     --corpus_format txt
 
 
-A `pretrained model <http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_pretrained_set_expansion.txt>`__
+A `pretrained model <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_pretrained_set_expansion.txt.tar.gz>`__
 on English Wikipedia dump (``enwiki-20171201-pages-articles-multistream.xml.bz2``) is available under
 Apache 2.0 license. It has been trained with hyperparameters values
-recommended above. Full English Wikipedia `raw corpus <http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201.txt>`_ and
-`marked corpus <http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_spacy_marked.txt>`_
+recommended above. Full English Wikipedia `raw corpus <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201.txt.gz>`_ and
+`marked corpus <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_spacy_marked.txt.tar.gz>`_
 are also available under the
 `Creative Commons Attribution-Share-Alike 3.0 License <https://creativecommons.org/licenses/by-sa/3.0/>`__.
 
-A `pretrained model with grouping <http://nervana-modelzoo.s3.amazonaws
-.com/NLP/SetExp/enwiki-20171201_grouping_pretrained_set_expansion/>`__
+A `pretrained model with grouping <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_grouping_pretrained_set_expansion.tar.gz>`__
 on the same English Wikipedia dump is also
 available under
 Apache 2.0 license. It has been trained with hyperparameters values
-recommended above. `Marked corpus <http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_grouping_marked.txt>`_
+recommended above. `Marked corpus <https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_grouping_marked.txt.tar.gz>`_
 is also available under the
 `Creative Commons Attribution-Share-Alike 3.0 License <https://creativecommons.org/licenses/by-sa/3.0/>`__.
 

nlp_architect/solutions/set_expansion/README.md

@@ -28,7 +28,7 @@ provide a subset of English Wikipedia at datasets/wikipedia as a sample corpus u
 [Creative Commons Attribution-Share-Alike 3.0 License](https://creativecommons.org/licenses/by-sa/3.0/)- Copyright 2018 Wikimedia Foundation.
 
 The output of this step is the marked corpus where noun phrases are marked with the marking character (default: "\_") as described in the [NLP Architect np2vec module documentation](http://nlp_architect.nervanasys.com/np2vec.html).
-The Noun phrase extraction module is using a pre-trained [model](http://nervana-modelzoo.s3.amazonaws.com/NLP/chunker/model.h5) which is available under the Apache 2.0 license. 
+The Noun phrase extraction module is using a pre-trained [model](https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/chunker/model.h5) which is available under the Apache 2.0 license. 
 
 This is done by running:
 ```
@@ -58,19 +58,19 @@ size, min_count, window and hs hyperparameters. Please refer to the np2vec modul
 python examples/np2vec/train.py --size 100 --min_count 10 --window 10 --hs 0 --corpus MARKED_TRAINING_CORPUS --np2vec_model_file MODEL_PATH --corpus_format txt
 ```
 
-A [pretrained model](http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_pretrained_set_expansion.txt) 
+A [pretrained model](https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_pretrained_set_expansion.txt.tar.gz) 
 on English Wikipedia dump (enwiki-20171201-pages-articles-multistream.xml.bz2) is available under the
 Apache 2.0 license. It has been trained with hyperparameters values
-recommended above. Full English Wikipedia [raw corpus](http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201.txt) and 
-[marked corpus](http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_spacy_marked.txt) 
+recommended above. Full English Wikipedia [raw corpus](https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201.txt.gz) and 
+[marked corpus](https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_spacy_marked.txt.tar.gz) 
 are also available under the  
 [Creative Commons Attribution-Share-Alike 3.0 License](https://creativecommons.org/licenses/by-sa/3.0/).
 
-A [pretrained model with grouping](http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_grouping_pretrained_set_expansion/)
+A [pretrained model with grouping](https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_grouping_pretrained_set_expansion.tar.gz)
 on the same English Wikipedia dump is also
 available under
 Apache 2.0 license. It has been trained with hyperparameters values
-recommended above. [Marked corpus](http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_grouping_marked.txt)
+recommended above. [Marked corpus](https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_grouping_marked.txt.tar.gz)
 is also available under the
 [Creative Commons Attribution-Share-Alike 3.0 License](https://creativecommons.org/licenses/by-sa/3.0/).
 

nlp_architect/solutions/set_expansion/prepare_data.py

@@ -39,7 +39,7 @@
 id2group = {}
 id2rep = {}
 np2count = {}
-nlp_chunker_url = 'http://nervana-modelzoo.s3.amazonaws.com/NLP/chunker/'
+nlp_chunker_url = 'https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/chunker/'
 chunker_path = str(LIBRARY_OUT / 'chunker-pretrained')
 chunker_model_dat_file = 'model_info.dat.params'
 chunker_model_file = 'model.h5'

tutorials/Term_Set_Expansion/term_set_expansion.ipynb

@@ -73,8 +73,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "url = 'http://nervana-modelzoo.s3.amazonaws.com/NLP/SetExp/enwiki-20171201_pretrained_set_expansion.txt'  \n",
-    "wget.download(url, 'enwiki-20171201_pretrained_set_expansion.txt')"
+    "url = 'https://s3-us-west-2.amazonaws.com/nlp-architect-data/models/term_set/enwiki-20171201_pretrained_set_expansion.txt.tar.gz'\n",
+    "wget.download(url, 'enwiki-20171201_pretrained_set_expansion.txt.tar.gz')\n",
+    "import tarfile \n",
+    "tarf = tarfile.open('enwiki-20171201_pretrained_set_expansion.txt.tar.gz') \n",
+    "tarf.extractall()"
    ]
   },
   {