refactor(async_rollout_worker): renamed tool variables to mirror grpo_trainer.py

trl/experimental/async_grpo/async_rollout_worker.py

@@ -546,27 +546,28 @@ async def _generate_one(
             tool_call_count += n_calls
             tool_failure_count += n_failures
             completion.extend(tool_messages)
-            tool_suffix_ids = self._build_messages_suffix_ids(tool_messages)
-            completion_ids.extend(tool_suffix_ids)
-            completion_logprobs.extend([0.0] * len(tool_suffix_ids))
-            tool_mask.extend([0] * len(tool_suffix_ids))
-            prompt_ids = prompt_ids + turn_ids + tool_suffix_ids
+            suffix_ids = self._get_tool_suffix_ids(tool_messages)
+            completion_ids.extend(suffix_ids)
+            completion_logprobs.extend([0.0] * len(suffix_ids))
+            tool_mask.extend([0] * len(suffix_ids))
+            prompt_ids = prompt_ids + turn_ids + suffix_ids
             iteration_num += 1
 
-    def _build_messages_suffix_ids(self, messages: list[dict[str, Any]]) -> list[int]:
-        template_messages = [
+    def _get_tool_suffix_ids(self, tool_messages: list[dict[str, Any]]) -> list[int]:
+        """Get token IDs for tool result formatting by using a minimal dummy conversation."""
+        dummy_messages = [
             {"role": "user", "content": ""},
             {"role": "assistant", "content": ""},
         ]
         prefix_ids = self.tokenizer.apply_chat_template(
-            template_messages,
+            dummy_messages,
             return_dict=False,
             tools=self.tools,
             chat_template=self.chat_template,
             **self.chat_template_kwargs,
         )
-        prefix_and_messages_ids = self.tokenizer.apply_chat_template(
-            template_messages + messages,
+        full_ids = self.tokenizer.apply_chat_template(
+            dummy_messages + tool_messages,
             return_dict=False,
             chat_template=self.chat_template,
             add_generation_prompt=True,
@@ -575,15 +576,15 @@ def _build_messages_suffix_ids(self, messages: list[dict[str, Any]]) -> list[int
         )
 
         # Some chat templates (notably Qwen3/Qwen3.5) render "...<|im_end|>\n" after an assistant/tool block.
-        # When we compute `suffix_ids` by slicing `prefix_and_messages_ids`, we must align the slicing boundary to
+        # When we compute `suffix_ids` by slicing `full_ids`, we must align the slicing boundary to
         # EOS (not EOS + newline).
         last_eos_idx = max(i for i, tok_id in enumerate(prefix_ids) if tok_id == self.tokenizer.eos_token_id)
         prefix_ids = prefix_ids[: last_eos_idx + 1]
 
-        if prefix_and_messages_ids[: len(prefix_ids)] != prefix_ids:
+        if full_ids[: len(prefix_ids)] != prefix_ids:
             raise ValueError("Unexpected tokenization: the EOS-trimmed prefix IDs are not a prefix of the full IDs.")
 
-        return prefix_and_messages_ids[len(prefix_ids) :]
+        return full_ids[len(prefix_ids) :]
 
     def _execute_tool_calls(
         self, tool_calls: list[dict[str, Any]], tool_dict: dict[str, Callable]