Remove context_ratio from agentic GRPO config.

examples/deepswe/run_deepswe_disagg_v5p_32.sh

@@ -151,7 +151,6 @@ python -m tunix.cli.grpo_main \
   `# ── Agentic / multi-turn ─────────────────────────────────────────────` \
   agentic_grpo_config.max_turns=20 \
   agentic_grpo_config.per_turn_timeout_secs=300 \
-  agentic_grpo_config.context_ratio=2 \
   agentic_grpo_config.max_concurrency=100 \
   \
   `# ── GRPO algorithm ───────────────────────────────────────────────────` \

tests/cli/grpo_main_test.py

@@ -557,8 +557,7 @@ def test_single_turn_kv_cache(self):
   def test_multi_turn_kv_cache(self):
     p = self._make_agentic_pipeline(max_turns=20, context_ratio=2)
     cfg = p.create_rollout_config()
-    # max_prompt=256, max_response=512, 20 turns * ratio 2
-    self.assertEqual(cfg.kv_cache_size, 256 + 512 * 2 * 20)
+    self.assertEqual(cfg.kv_cache_size, 256 + 512 + 256)
 
   def test_standard_grpo_kv_cache(self):
     extra = """

tunix/cli/grpo_main.py

@@ -70,7 +70,7 @@ class GrpoPipeline(config.HyperParameters):
   GRPOLearner.  Additional config sections are recognised:
 
   * ``agentic_grpo_config``: GRPOConfig fields (num_generations, beta, …)
-    plus ``max_turns``, ``context_ratio``, ``per_turn_timeout_secs``.
+    plus ``max_turns``, ``per_turn_timeout_secs``.
   * role-specific ``*_model_config.mesh``: any role with an explicit mesh gets
     its own device slice; omitted meshes share the actor mesh by default.
   * role-specific ``same_mesh_as``: optional mesh sharing like
@@ -259,8 +259,8 @@ def create_rollout_config(
     Standard mode: pass rollout_config fields through with kv_cache_size =
     max_prompt_length + total_generation_steps + 256.
 
-    Agentic mode: same base, but multi-turn KV cache =
-    max_prompt + total_generation_steps * context_ratio * max_turns.
+    Agentic mode: same base. Same kv_cache_size calculation. 
+
     Engine-specific extras (sglang_jax_config, vllm_config) are also applied.
     """
     rollout_cfg = self.config["rollout_config"]
@@ -281,12 +281,7 @@ def create_rollout_config(
 
     if mode == "agentic_grpo":
       agentic_cfg = self.config.get("agentic_grpo_config", {})
-      max_turns = agentic_cfg.get("max_turns", 1)
-      context_ratio = agentic_cfg.get("context_ratio", 1)
-      if max_turns > 1:
-        kv_cache_size = max_prompt + max_response * context_ratio * max_turns
-      else:
-        kv_cache_size = max_prompt + max_response + 256
+      kv_cache_size = max_prompt + max_response + 256
       filtered["kv_cache_size"] = kv_cache_size
       logging.info("kv_cache_size: %d", kv_cache_size)
 
@@ -659,7 +654,6 @@ def _create_agentic_grpo_config(self):
     # Strip helper keys that are not GRPOConfig fields
     valid = {f.name for f in dataclasses.fields(GRPOConfig)}
     cfg.pop("max_turns", None)
-    cfg.pop("context_ratio", None)
     return GRPOConfig(**{k: v for k, v in cfg.items() if k in valid})
 
   def _create_chat_parser(self, tokenizer: Any) -> Any:
@@ -744,7 +738,7 @@ def _run(self, mode: str = "grpo"):
     rl_cluster = self.create_rl_cluster(tokenizer)
 
     if mode == "grpo":
-      from tunix.rl.grpo import grpo_learner
+      from tunix.rl.grpo import grpo_learner  # pylint: disable=g-import-not-at-top
 
       grpo_trainer = grpo_learner.GrpoLearner(
           rl_cluster=rl_cluster,