Make ruff happy

flairNLP · Dec 17, 2023 · d0441d7 · d0441d7
1 parent 6382c47
commit d0441d7
Showing 1 changed file with 19 additions and 16 deletions.
diff --git a/flair/datasets/document_classification.py b/flair/datasets/document_classification.py
@@ -908,8 +908,9 @@ def __init__(
 
 
 class AGNEWS(ClassificationCorpus):
-    """The AG's News Topic Classification Corpus, classifying news into 4 coarse-grained topics
-    (World, Sports, Business, Sci/Tech).
+    """The AG's News Topic Classification Corpus, classifying news into 4 coarse-grained topics.
+
+    Labels: World, Sports, Business, Sci/Tech.
     """
 
     def __init__(
@@ -920,6 +921,7 @@ def __init__(
         **corpusargs,
     ):
         """Instantiates AGNews Classification Corpus with 4 classes.
+
         :param base_path: Provide this only if you store the AGNEWS corpus in a specific folder, otherwise use default.
         :param tokenizer: Custom tokenizer to use (default is SpaceTokenizer)
         :param memory_mode: Set to 'partial' by default. Can also be 'full' or 'none'.
@@ -953,22 +955,23 @@ def __init__(
         original_filenames = original_filenames[:-1]
         if not data_file.is_file():
             for original_filename, new_filename in zip(original_filenames, new_filenames):
-                with open(data_folder / "original" / original_filename, encoding="utf-8") as open_fp:
-                    with open(data_folder / new_filename, "w", encoding="utf-8") as write_fp:
-                        csv_reader = csv.reader(
-                            open_fp, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
-                        )
-                        for id_, row in enumerate(csv_reader):
-                            label, title, description = row
-                            # Original labels are [1, 2, 3, 4] -> ['World', 'Sports', 'Business', 'Sci/Tech']
-                            # Re-map to [0, 1, 2, 3].
-                            label = int(label) - 1
-                            text = " ".join((title, description))
+                with open(data_folder / "original" / original_filename, encoding="utf-8") as open_fp, open(
+                    data_folder / new_filename, "w", encoding="utf-8"
+                ) as write_fp:
+                    csv_reader = csv.reader(
+                        open_fp, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
+                    )
+                    for id_, row in enumerate(csv_reader):
+                        label, title, description = row
+                        # Original labels are [1, 2, 3, 4] -> ['World', 'Sports', 'Business', 'Sci/Tech']
+                        # Re-map to [0, 1, 2, 3].
+                        label = int(label) - 1
+                        text = " ".join((title, description))
 
-                            new_label = "__label__"
-                            new_label += label_dict[label]
+                        new_label = "__label__"
+                        new_label += label_dict[label]
 
-                            write_fp.write(f"{new_label} {text}\n")
+                        write_fp.write(f"{new_label} {text}\n")
 
         super().__init__(data_folder, label_type="topic", tokenizer=tokenizer, memory_mode=memory_mode, **corpusargs)