feat(utils): 增加数据集处理的灵活性和可配置性

utils.py

@@ -19,7 +19,9 @@ def process_dataset(
     dataset_name: str,
     output_subdir: str,
     dataset_config: str = None,
+    max_chunk_size: int = None,
     split_name: str = "train",
+    column_name: str = "text",
     chunk_size: int = 1000000,
     normalization_func=comprehensive_normalization
 ):
@@ -29,12 +31,13 @@ def process_dataset(
 
     total_samples = len(train_dataset)
     num_chunks = (total_samples // chunk_size) + 1
+    lim_chunks = max_chunk_size if max_chunk_size else num_chunks
 
     script_dir = os.path.dirname(os.path.abspath(__file__))
     output_dir = os.path.join(script_dir, "dataset", output_subdir)
     os.makedirs(output_dir, exist_ok=True)
 
-    for i in range(num_chunks):
+    for i in range(lim_chunks):
         start_idx = i * chunk_size
         end_idx = min((i + 1) * chunk_size, total_samples)
         chunk = train_dataset.select(range(start_idx, end_idx))
@@ -42,10 +45,10 @@ def process_dataset(
         output_path = os.path.join(output_dir, f"{output_subdir}_text_chunk_{i}.jsonl")
         with open(output_path, "w", encoding="utf-8") as f:
             for example in chunk:
-                text = example["text"]
+                text = example[column_name]
                 if normalization_func:
                     text = normalization_func(text)
-                json_line = {"text": text}
+                json_line = {column_name : text}
                 f.write(json.dumps(json_line, ensure_ascii=False) + "\n")
 
         print(f"Saved text chunk {i} to {output_path}")