Added initial script

amazon.py

@@ -0,0 +1,208 @@
+import csv
+import os
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """
+"""
+
+_URLS = {
+    "clothing": "https://drive.google.com/u/0/uc?id=1HP3EPX9Q8JffUUZz2czXD7qudzvitscq&export=download",
+    "electronics": "https://drive.google.com/u/0/uc?id=1W50FNd0707qK1CCktEF30nlDqsImLg3X&export=download",
+    "office": "https://drive.google.com/u/0/uc?id=1lsttnBIjFD4nQw9idZYQNUWKSzj5VibD&export=download",
+}
+
+_FIELDS = ["date", "rating", "reviewText", "summary"]
+_RATINGS = ["1", "2", "3", "4", "5"]
+
+
+class AmazonConfig(datasets.BuilderConfig):
+    def __init__(
+        self,
+        training_files,
+        testing_files,
+        url,
+        label_classes=_RATINGS,
+        **kwargs,
+    ):
+        super().__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.label_classes = label_classes
+        self.training_files = training_files
+        self.testing_files = testing_files
+        self.url = url
+
+
+class Amazon(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        AmazonConfig(
+            name="clothing_majorshift01",
+            description="",
+            url=_URLS["clothing"],
+            training_files=[
+                "201011.csv",
+                "201012.csv",
+                "201101.csv",
+                "201102.csv",
+                "201103.csv",
+                "201104.csv",
+                "201105.csv",
+                "201106.csv",
+                "201107.csv",
+                "201108.csv",
+                "201109.csv",
+                "201110.csv",
+                "201111.csv",
+                "201112.csv",
+                "201201.csv",
+                "201202.csv",
+                "201203.csv",
+                "201204.csv",
+                "201205.csv",
+                "201206.csv",
+                "201207.csv",
+                "201208.csv",
+                "201209.csv",
+                "201210.csv",
+            ],
+            testing_files=[
+                "201211.csv",
+                "201212.csv",
+                "201301.csv",
+                "201302.csv",
+                "201303.csv",
+                "201304.csv",
+            ],
+        ),
+        AmazonConfig(
+            name="clothing_majorshift02",
+            description="",
+            url=_URLS["clothing"],
+            training_files=[
+                "200808.csv",
+                "200809.csv",
+                "200810.csv",
+                "200811.csv",
+                "200812.csv",
+                "200901.csv",
+                "200902.csv",
+                "200903.csv",
+                "200904.csv",
+                "200905.csv",
+                "200906.csv",
+                "200907.csv",
+                "200908.csv",
+                "200909.csv",
+                "200910.csv",
+                "200911.csv",
+                "200912.csv",
+                "201001.csv",
+                "201002.csv",
+                "201003.csv",
+                "201004.csv",
+                "201005.csv",
+                "201006.csv",
+                "201007.csv",
+            ],
+            testing_files=[
+                "201008.csv",
+                "201009.csv",
+                "201010.csv",
+                "201011.csv",
+                "201012.csv",
+                "201101.csv",
+            ],
+        ),
+        AmazonConfig(
+            name="clothing_majorshift03",
+            description="",
+            url=_URLS["clothing"],
+            training_files=[
+                "201602.csv",
+                "201603.csv",
+                "201604.csv",
+                "201605.csv",
+                "201606.csv",
+                "201607.csv",
+                "201608.csv",
+                "201609.csv",
+                "201610.csv",
+                "201611.csv",
+                "201612.csv",
+                "201701.csv",
+                "201702.csv",
+                "201703.csv",
+                "201704.csv",
+                "201705.csv",
+                "201706.csv",
+                "201707.csv",
+                "201708.csv",
+                "201709.csv",
+                "201710.csv",
+                "201711.csv",
+                "201712.csv",
+                "201801.csv",
+            ],
+            testing_files=[
+                "201802.csv",
+                "201803.csv",
+                "201804.csv",
+                "201805.csv",
+                "201806.csv",
+                "201807.csv",
+            ],
+        ),
+    ]
+
+    def _info(self):
+        features = {
+            "date": datasets.Value("string"),
+            "id": datasets.Value("int32"),
+            "label": datasets.features.ClassLabel(names=self.config.label_classes),
+            "text": datasets.Value("string"),
+        }
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(features),
+        )
+
+    def _split_generators(self, dl_manager):
+        dirname = dl_manager.download_and_extract(self.config.url)
+        logger.info(str(dirname))
+        category = self.config.name.split("_")[
+            0
+        ]  # extract category name from the config
+        train_filepaths = tuple(
+            os.path.join(dirname, category, fname)
+            for fname in self.config.training_files
+        )
+        test_filepaths = tuple(
+            os.path.join(dirname, category, fname)
+            for fname in self.config.testing_files
+        )
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepaths": train_filepaths},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepaths": test_filepaths},
+            ),
+        ]
+
+    def _generate_examples(self, filepaths):
+        logger.info(f"generating examples from {len(filepaths)} files")
+        idx = 0
+        for filepath in filepaths:
+            with open(filepath, encoding="utf-8") as f:
+                reader = csv.DictReader(f, fieldnames=_FIELDS)
+                for row in reader:
+                    yield idx, {
+                        "date": row["date"],
+                        "id": idx,
+                        "label": row["rating"],
+                        "text": row["reviewText"],
+                    }
+                    idx += 1