update s3 links (#215)

docs/source/env_var.rst

+Environment Variables
+=====================
+
+Backend Options
+---------------
+* DGLBACKEND
+    * Values: String (default='pytorch')
+    * The backend deep lerarning framework for DGL.
+    * Choices:
+        * 'pytorch': use PyTorch as the backend implentation.
+        * 'mxnet': use Apache MXNet as the backend implementation.
+
+Data Repository
+---------------
+* DGL_REPO
+    * Values: String (default='https://s3.us-east-2.amazonaws.com/dgl.ai/')
+    * The repository url to be used for DGL datasets and pre-trained models.
+    * Suggested values:
+        * 'https://s3.us-east-2.amazonaws.com/dgl.ai/': DGL repo for U.S.
+        * 'https://s3-ap-southeast-1.amazonaws.com/dgl.ai.asia/': DGL repo for Asia

python/dgl/contrib/data/knowledge_graph.py

@@ -13,11 +13,11 @@ import rdflib as rdf
 import pandas as pd
 from collections import Counter
 
-from dgl.data.utils import download, extract_archive, get_download_dir
+from dgl.data.utils import download, extract_archive, get_download_dir, _get_dgl_url
 
 np.random.seed(123)
 
-_downlaod_prefix = 'https://s3.us-east-2.amazonaws.com/dgl.ai/dataset/'
+_downlaod_prefix = _get_dgl_url('dataset/')
 
 class RGCNEntityDataset(object):
     """RGCN Entity Classification dataset

python/dgl/data/citation_graph.py

-
 """Cora, citeseer, pubmed dataset.
 
 (lingfan): following dataset loading and preprocessing code from tkipf/gcn
@@ -12,12 +11,12 @@ import networkx as nx
 import scipy.sparse as sp
 import os, sys
 
-from .utils import download, extract_archive, get_download_dir
+from .utils import download, extract_archive, get_download_dir, _get_dgl_url
 
 _urls = {
-    'cora' : 'https://s3.us-east-2.amazonaws.com/dgl.ai/dataset/cora.zip',
-    'citeseer' : 'https://s3.us-east-2.amazonaws.com/dgl.ai/dataset/citeseer.zip',
-    'pubmed' : 'https://s3.us-east-2.amazonaws.com/dgl.ai/dataset/pubmed.zip',
+    'cora' : 'dataset/cora.zip',
+    'citeseer' : 'dataset/citeseer.zip',
+    'pubmed' : 'dataset/pubmed.zip',
 }
 
 class CitationGraphDataset(object):
@@ -25,7 +24,7 @@ class CitationGraphDataset(object):
         self.name = name
         self.dir = get_download_dir()
         self.zip_file_path='{}/{}.zip'.format(self.dir, name)
-        download(_urls[name], path=self.zip_file_path)
+        download(_get_dgl_url(_urls[name]), path=self.zip_file_path)
         extract_archive(self.zip_file_path, '{}/{}'.format(self.dir, name))
         self._load()
 

python/dgl/data/tree.py

@@ -14,10 +14,10 @@ import numpy as np
 import os
 import dgl
 import dgl.backend as F
-from dgl.data.utils import download, extract_archive, get_download_dir
+from dgl.data.utils import download, extract_archive, get_download_dir, _get_dgl_url
 
 _urls = {
-    'sst' : 'https://s3.us-east-2.amazonaws.com/dgl.ai/dataset/sst.zip',
+    'sst' : 'dataset/sst.zip',
 }
 
 SSTBatch = namedtuple('SSTBatch', ['graph', 'mask', 'wordid', 'label'])
@@ -54,7 +54,7 @@ class SST(object):
         self.pretrained_file = 'glove.840B.300d.txt' if mode == 'train' else ''
         self.pretrained_emb = None
         self.vocab_file = '{}/sst/vocab.txt'.format(self.dir) if vocab_file is None else vocab_file
-        download(_urls['sst'], path=self.zip_file_path)
+        download(_get_dgl_url(_urls['sst']), path=self.zip_file_path)
         extract_archive(self.zip_file_path, '{}/sst'.format(self.dir))
         self.trees = []
         self.num_classes = 5

python/dgl/data/utils.py

@@ -13,6 +13,15 @@ except ImportError:
         pass
     requests = requests_failed_to_import
 
+def _get_dgl_url(file_url):
+    """Get DGL online url for download."""
+    dgl_repo_url = 'https://s3.us-east-2.amazonaws.com/dgl.ai/'
+    repo_url = os.environ.get('DGL_REPO', dgl_repo_url)
+    if repo_url[-1] != '/':
+        repo_url = repo_url + '/'
+    return repo_url + file_url
+
+
 def download(url, path=None, overwrite=False, sha1_hash=None, retries=5, verify_ssl=True):
     """Download a given URL.