Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
1M - 10M
ArXiv:
License:
Update files from the datasets library (from 1.16.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.16.0
- README.md +2 -1
- amazon_polarity.py +17 -16
README.md
CHANGED
@@ -18,9 +18,10 @@ task_categories:
|
|
18 |
task_ids:
|
19 |
- sentiment-classification
|
20 |
paperswithcode_id: null
|
|
|
21 |
---
|
22 |
|
23 |
-
# Dataset Card for
|
24 |
|
25 |
## Table of Contents
|
26 |
- [Dataset Description](#dataset-description)
|
|
|
18 |
task_ids:
|
19 |
- sentiment-classification
|
20 |
paperswithcode_id: null
|
21 |
+
pretty_name: Amazon Review Polarity
|
22 |
---
|
23 |
|
24 |
+
# Dataset Card for Amazon Review Polarity
|
25 |
|
26 |
## Table of Contents
|
27 |
- [Dataset Description](#dataset-description)
|
amazon_polarity.py
CHANGED
@@ -16,7 +16,6 @@
|
|
16 |
|
17 |
|
18 |
import csv
|
19 |
-
import os
|
20 |
|
21 |
import datasets
|
22 |
|
@@ -94,32 +93,34 @@ class AmazonPolarity(datasets.GeneratorBasedBuilder):
|
|
94 |
def _split_generators(self, dl_manager):
|
95 |
"""Returns SplitGenerators."""
|
96 |
my_urls = _URLs[self.config.name]
|
97 |
-
|
98 |
return [
|
99 |
datasets.SplitGenerator(
|
100 |
name=datasets.Split.TRAIN,
|
101 |
gen_kwargs={
|
102 |
-
"filepath":
|
103 |
-
"
|
104 |
},
|
105 |
),
|
106 |
datasets.SplitGenerator(
|
107 |
name=datasets.Split.TEST,
|
108 |
gen_kwargs={
|
109 |
-
"filepath":
|
110 |
-
"
|
111 |
},
|
112 |
),
|
113 |
]
|
114 |
|
115 |
-
def _generate_examples(self, filepath,
|
116 |
"""Yields examples."""
|
117 |
-
|
118 |
-
|
119 |
-
|
120 |
-
|
121 |
-
|
122 |
-
|
123 |
-
|
124 |
-
|
125 |
-
|
|
|
|
|
|
16 |
|
17 |
|
18 |
import csv
|
|
|
19 |
|
20 |
import datasets
|
21 |
|
|
|
93 |
def _split_generators(self, dl_manager):
|
94 |
"""Returns SplitGenerators."""
|
95 |
my_urls = _URLs[self.config.name]
|
96 |
+
archive = dl_manager.download(my_urls)
|
97 |
return [
|
98 |
datasets.SplitGenerator(
|
99 |
name=datasets.Split.TRAIN,
|
100 |
gen_kwargs={
|
101 |
+
"filepath": "/".join(["amazon_review_polarity_csv", "train.csv"]),
|
102 |
+
"files": dl_manager.iter_archive(archive),
|
103 |
},
|
104 |
),
|
105 |
datasets.SplitGenerator(
|
106 |
name=datasets.Split.TEST,
|
107 |
gen_kwargs={
|
108 |
+
"filepath": "/".join(["amazon_review_polarity_csv", "test.csv"]),
|
109 |
+
"files": dl_manager.iter_archive(archive),
|
110 |
},
|
111 |
),
|
112 |
]
|
113 |
|
114 |
+
def _generate_examples(self, filepath, files):
|
115 |
"""Yields examples."""
|
116 |
+
for path, f in files:
|
117 |
+
if path == filepath:
|
118 |
+
lines = (line.decode("utf-8") for line in f)
|
119 |
+
data = csv.reader(lines, delimiter=",", quoting=csv.QUOTE_ALL)
|
120 |
+
for id_, row in enumerate(data):
|
121 |
+
yield id_, {
|
122 |
+
"title": row[1],
|
123 |
+
"content": row[2],
|
124 |
+
"label": int(row[0]) - 1,
|
125 |
+
}
|
126 |
+
break
|