disentangle model from tuner and rename modules

src/llmtuner/train/rm/collator.py

@@ -0,0 +1,27 @@
+import torch
+from dataclasses import dataclass
+from typing import Any, Dict, Sequence
+from transformers import DataCollatorWithPadding
+
+
+@dataclass
+class PairwiseDataCollatorWithPadding(DataCollatorWithPadding):
+    r"""
+    Data collator for pairwise data.
+    """
+
+    def __call__(self, features: Sequence[Dict[str, Any]]) -> Dict[str, torch.Tensor]:
+        r"""
+        Pads batched data to the longest sequence in the batch.
+
+        We generate 2 * n examples where the first n examples represent chosen examples and
+        the last n examples represent rejected examples.
+        """
+        features = [
+            {
+                "input_ids": feature["prompt_ids"] + feature[key],
+                "attention_mask": [1] * (len(feature["prompt_ids"]) + len(feature[key]))
+            }
+            for key in ("chosen_ids", "rejected_ids") for feature in features
+        ]
+        return super().__call__(features)