Upload trans2.py

trans2.py

@@ -0,0 +1,135 @@
+import json
+import os
+from transformers import AutoTokenizer
+
+# 1. 配置
+MODEL_PATH = "/home/at0842/ycl466704.ai13/.cache/huggingface/hub/models--openai--gpt-oss-20b/snapshots/6cee5e81ee83917806bbde320786a8fb61efebee"
+INPUT_JSONL = "all_dupcleaned_data_turn.jsonl"
+OUTPUT_JSONL = "all_dupcleaned_data_turn_gpt_oss_20b_pretokenized.jsonl"
+MAX_LENGTH = 14436 
+
+if not os.path.exists(MODEL_PATH):
+    print(f"❌ 錯誤：找不到模型路徑 {MODEL_PATH}")
+    exit()
+
+print(f"⏳ 正在初始化 GPT-OSS 20B Tokenizer...")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH, trust_remote_code=True)
+
+# 事先取得 <|return|> 的 ID
+RETURN_TOKEN_ID = tokenizer.convert_tokens_to_ids("<|return|>")
+
+def process_entry(entry, index):
+    try:
+        messages = entry.get("messages", [])
+        raw_tools = entry.get("tools", None) 
+        
+        # --- 工具格式化 ---
+        formatted_tools = None
+        if raw_tools and isinstance(raw_tools, list):
+            formatted_tools = []
+            for t in raw_tools:
+                if isinstance(t, dict) and "function" in t:
+                    formatted_tools.append(t)
+                else:
+                    formatted_tools.append({
+                        "type": "function",
+                        "function": t
+                    })
+
+        if not isinstance(messages, list) or len(messages) < 2:
+            return None, "對話輪次不足"
+        
+        if messages[-1].get("role") != "assistant":
+            return None, f"最後一則不是 assistant (抓到的是: {messages[-1].get('role')})"
+
+        # 1. 取得原始完整序列 (關閉自動剪裁)
+        full_ids = tokenizer.apply_chat_template(
+            messages, 
+            tools=formatted_tools,
+            tokenize=True, 
+            add_generation_prompt=False,
+            truncation=False 
+        )
+        
+        # --- 核心邏輯：手動補強結束符號 ---
+        # 如果最後一個 ID 不是 <|return|>，手動補上
+        if full_ids[-1] != RETURN_TOKEN_ID:
+            full_ids.append(RETURN_TOKEN_ID)
+            
+        # 2. 補完結束符後，再進行長度檢查
+        actual_length = len(full_ids)
+        if actual_length > MAX_LENGTH:
+            return None, f"加上結束符後過長 ({actual_length} > {MAX_LENGTH})"
+
+        # 3. 計算 Context 長度 (提示部分)
+        context_ids = tokenizer.apply_chat_template(
+            messages[:-1], 
+            tools=formatted_tools,
+            tokenize=True, 
+            add_generation_prompt=True,
+            truncation=False
+        )   
+        
+        start_idx = len(context_ids)
+        
+        # 安全檢查
+        if start_idx >= actual_length:
+            return None, "計算錯誤：Context 長度大於等於總長度"
+
+        # 4. 製作 Labels (包含剛才補上的結束符號)
+        labels = [-100] * actual_length
+        for i in range(start_idx, actual_length):
+            labels[i] = full_ids[i]
+            
+        return {
+            "input_ids": full_ids,
+            "attention_mask": [1] * actual_length,
+            "labels": labels
+        }, None
+
+    except Exception as e:
+        return None, str(e)
+
+# --- 執行主程式 ---
+success_count = 0
+drop_count = 0
+
+print(f" 🚀 開始處理資料...")
+
+with open(INPUT_JSONL, "r", encoding="utf-8") as f_in, \
+     open(OUTPUT_JSONL, "w", encoding="utf-8") as f_out:
+    
+    for i, line in enumerate(f_in):
+        line = line.strip()
+        if not line: continue
+        
+        try:
+            entry = json.loads(line)
+            result, error_msg = process_entry(entry, i)
+            
+            if result:
+                f_out.write(json.dumps(result, ensure_ascii=False) + "\n")
+                success_count += 1
+                
+                if success_count == 1:
+                    print("\n" + "="*60)
+                    print("【首筆資料切分預覽 - 修正結尾版】")
+                    loss_indices = [idx for idx, val in enumerate(result['labels']) if val != -100]
+                    loss_tokens = [result['input_ids'][idx] for idx in loss_indices]
+                    target_text = tokenizer.decode(loss_tokens)
+                    print(f" Target (計算 Loss 部分): \n{target_text}")
+                    print(f" 總長度: {len(result['input_ids'])}")
+                    
+                    last_tokens = tokenizer.convert_ids_to_tokens(result['input_ids'][-3:])
+                    print(f" 序列末端三個 Token: {last_tokens}")
+                    print("="*60 + "\n")
+            else:
+                drop_count += 1
+                
+        except Exception as e:
+            drop_count += 1
+
+print(f" ✅ 處理完成！")
+print(f" 成功筆數: {success_count}")
+print(f" 丟棄筆數: {drop_count}")
+print(f" 結果檔案: {OUTPUT_JSONL}")