change script

lccc.py

@@ -13,9 +13,9 @@
 # limitations under the License.
 """
 LCCC: Large-scale Cleaned Chinese Conversation corpus (LCCC) is a large corpus of Chinese conversations.
-A rigorous data cleaning pipeline is designed to ensure the quality of the corpus. 
-This pipeline involves a set of rules and several classifier-based filters. 
-Noises such as offensive or sensitive words, special symbols, emojis, 
+A rigorous data cleaning pipeline is designed to ensure the quality of the corpus.
+This pipeline involves a set of rules and several classifier-based filters.
+Noises such as offensive or sensitive words, special symbols, emojis,
 grammatically incorrect sentences, and incoherent conversations are filtered.
 """
 
@@ -39,9 +39,9 @@ url={https://arxiv.org/abs/2008.03946}
 # Description of the dataset here
 _DESCRIPTION = """\
 LCCC: Large-scale Cleaned Chinese Conversation corpus (LCCC) is a large corpus of Chinese conversations.
-A rigorous data cleaning pipeline is designed to ensure the quality of the corpus. 
-This pipeline involves a set of rules and several classifier-based filters. 
-Noises such as offensive or sensitive words, special symbols, emojis, 
+A rigorous data cleaning pipeline is designed to ensure the quality of the corpus.
+This pipeline involves a set of rules and several classifier-based filters.
+Noises such as offensive or sensitive words, special symbols, emojis,
 grammatically incorrect sentences, and incoherent conversations are filtered.
 """
 
@@ -53,7 +53,7 @@ _URLS = {
         "train": "https://huggingface.co/datasets/silver/lccc/resolve/main/lccc_base_train.jsonl.gz",
         "valid": "https://huggingface.co/datasets/silver/lccc/resolve/main/lccc_base_valid.jsonl.gz",
         "test": "https://huggingface.co/datasets/silver/lccc/resolve/main/lccc_base_test.jsonl.gz",
-    }
+    },
 }
 
 
@@ -70,7 +70,7 @@ class LCCC(datasets.GeneratorBasedBuilder):
     def _info(self):
         features = datasets.Features(
             {
-                "dialog": datasets.Value("string"),
+                "dialog": [datasets.Value("string")],
             }
         )
         return datasets.DatasetInfo(
@@ -95,23 +95,32 @@ class LCCC(datasets.GeneratorBasedBuilder):
         if self.config.name == "large":
             return [
                 datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN, 
-                    gen_kwargs={ "filepath": os.path.join(downloaded_data), "split": "train", }
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": os.path.join(downloaded_data),
+                        "split": "train",
+                    },
                 )
             ]
         if self.config.name == "base":
             return [
                 datasets.SplitGenerator(
                     name=datasets.Split.TRAIN,
-                    gen_kwargs={ "filepath": os.path.join(downloaded_data["train"]), "split": "train", },
+                    gen_kwargs={
+                        "filepath": os.path.join(downloaded_data["train"]),
+                        "split": "train",
+                    },
                 ),
                 datasets.SplitGenerator(
                     name=datasets.Split.TEST,
-                    gen_kwargs={ "filepath": os.path.join(downloaded_data["test"]), "split": "test" },
+                    gen_kwargs={"filepath": os.path.join(downloaded_data["test"]), "split": "test"},
                 ),
                 datasets.SplitGenerator(
                     name=datasets.Split.VALIDATION,
-                    gen_kwargs={ "filepath": os.path.join(downloaded_data["valid"]), "split": "dev", },
+                    gen_kwargs={
+                        "filepath": os.path.join(downloaded_data["valid"]),
+                        "split": "dev",
+                    },
                 ),
             ]
 
@@ -120,7 +129,8 @@ class LCCC(datasets.GeneratorBasedBuilder):
         with open(filepath, encoding="utf-8") as f:
             for key, row in enumerate(f):
                 row = row.strip()
-                if len(row) == 0: continue
+                if len(row) == 0:
+                    continue
                 yield key, {
                     "dialog": json.loads(row),
                 }