[megatron] Add TIS support to megatron backend (verl-project#3513)

### What does this PR do?

Add the TIS support from verl-project#2953 to
megatron actor

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Co-authored-by: Shuang Yu <shuangy@shuangy-mlt.client.nvidia.com>

Author: sharonyu-115

verl/workers/actor/megatron_actor.py

@@ -288,6 +288,13 @@ def make_minibatch_iterator(self, data: DataProto) -> Iterable[DataProto]:
         ]
         if self.config.use_kl_loss:
             select_keys.append("ref_log_prob")
+        if self.config.tis_imp_ratio_cap > 0:
+            assert "rollout_log_probs" in data.batch.keys(), (
+                "Truncated Importance Sampling (TIS) requires to configure "
+                "`actor_rollout_ref.rollout.calculate_log_probs=True` "
+                "and is not currently supported in Server mode (agent loop)."
+            )
+            select_keys.append("rollout_log_probs")
         self.has_multi_modal_inputs = "multi_modal_inputs" in data.non_tensor_batch.keys()
         if self.has_multi_modal_inputs:
             data = data.select(select_keys, ["multi_modal_inputs"])
@@ -309,6 +316,7 @@ def compute_ppo_loss(self, model_output, data):
         response_mask = data["response_mask"].to(bool)
         # compute policy loss
         old_log_prob = data["old_log_probs"]
+        rollout_log_probs = data["rollout_log_probs"] if self.config.tis_imp_ratio_cap > 0 else None
         advantages = data["advantages"]
 
         loss_agg_mode = self.config.loss_agg_mode
@@ -323,6 +331,7 @@ def compute_ppo_loss(self, model_output, data):
             response_mask=response_mask,
             loss_agg_mode=loss_agg_mode,
             config=self.config,
+            rollout_log_probs=rollout_log_probs,
         )
 
         metrics.update(