From dc9c5a01fcecf4a56c7b0674834c2afb6404cde8 Mon Sep 17 00:00:00 2001
From: Weirui Kuang <39145382+rayrayraykk@users.noreply.github.com>
Date: Mon, 9 May 2022 20:31:46 +0800
Subject: [PATCH] fix url in dblp_new.py

---
 federatedscope/gfl/dataset/dblp_new.py | 26 ++++++++++----------------
 1 file changed, 10 insertions(+), 16 deletions(-)

diff --git a/federatedscope/gfl/dataset/dblp_new.py b/federatedscope/gfl/dataset/dblp_new.py
index 61d8ac4bc..3ff676729 100644
--- a/federatedscope/gfl/dataset/dblp_new.py
+++ b/federatedscope/gfl/dataset/dblp_new.py
@@ -1,6 +1,4 @@
-import os
 import os.path as osp
-
 import numpy as np
 import networkx as nx
 import torch
@@ -8,20 +6,20 @@
 from torch_geometric.utils import from_networkx
 from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.feature_extraction._stop_words import ENGLISH_STOP_WORDS as sklearn_stopwords
-from nltk import word_tokenize
-from nltk.stem import WordNetLemmatizer
-from nltk.corpus import stopwords as nltk_stopwords
 
 
 class LemmaTokenizer(object):
     def __init__(self):
+        from nltk.stem import WordNetLemmatizer
         self.wnl = WordNetLemmatizer()
 
     def __call__(self, doc):
+        from nltk import word_tokenize
         return [self.wnl.lemmatize(t) for t in word_tokenize(doc)]
 
 
 def build_feature(words, threshold):
+    from nltk.corpus import stopwords as nltk_stopwords
     # use bag-of-words representation of paper titles as the features of papers
     stopwords = sklearn_stopwords.union(set(nltk_stopwords.words('english')))
     vectorizer = CountVectorizer(min_df=int(threshold),
@@ -32,10 +30,8 @@ def build_feature(words, threshold):
     return features_paper
 
 
-def build_graph(path, FL=0, threshold=15):
-
-    filename = 'gfl%2Fpaper_classification_dataset.tsv'
-    with open(os.path.join(path, filename), 'r') as f:
+def build_graph(path, filename, FL=0, threshold=15):
+    with open(osp.join(path, filename), 'r') as f:
         node_cnt = sum([1 for line in f])
 
     G = nx.DiGraph()
@@ -47,7 +43,7 @@ def build_graph(path, FL=0, threshold=15):
         org2paper = dict()
 
     # Build node feature from title
-    with open(os.path.join(path, filename), 'r') as f:
+    with open(osp.join(path, filename), 'r') as f:
         for line in f:
             cols = line.strip().split('\t')
             nid, title = int(cols[0]), cols[3]
@@ -57,7 +53,7 @@ def build_graph(path, FL=0, threshold=15):
                         dtype=np.float32)
 
     # Build graph structure
-    with open(os.path.join(path, filename), 'r') as f:
+    with open(osp.join(path, filename), 'r') as f:
         for line in f:
             cols = line.strip().split('\t')
             nid, conf, org, label = int(cols[0]), cols[1], cols[2], int(
@@ -132,9 +128,7 @@ def __init__(self,
 
     @property
     def raw_file_names(self):
-        names = [
-            'gfl%2Fpaper_classification_dataset.tsv',
-        ]
+        names = ['dblp_new.tsv']
         return names
 
     @property
@@ -151,13 +145,13 @@ def processed_dir(self):
 
     def download(self):
         # Download to `self.raw_dir`.
-        url = 'xxx.com'
+        url = 'https://federatedscope.oss-cn-beijing.aliyuncs.com'
         for name in self.raw_file_names:
             download_url(osp.join(url, name), self.raw_dir)
 
     def process(self):
         # Read data into huge `Data` list.
-        data_list = build_graph(self.raw_dir, self.FL)
+        data_list = build_graph(self.raw_dir, self.raw_file_names[0], self.FL)
 
         data_list_w_masks = []
         for data in data_list: