[docker] optimize r3 with base64 encode

docker/patch/latest/sglang.patch

@@ -814,27 +814,23 @@ index 7f6f6a010..c4a673145 100644
              if not get_global_server_args().sampling_backend == "ascend" or (
                  return_logprob and not SGLANG_RETURN_ORIGINAL_LOGPROB
 diff --git a/python/sglang/srt/managers/detokenizer_manager.py b/python/sglang/srt/managers/detokenizer_manager.py
-index 87922077e..8cb6bad8d 100644
+index 87922077e..6507d8bf5 100644
 --- a/python/sglang/srt/managers/detokenizer_manager.py
 +++ b/python/sglang/srt/managers/detokenizer_manager.py
-@@ -247,6 +247,16 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
+@@ -247,6 +247,12 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
              s.sent_offset = len(output_str)
              output_strs.append(incremental_output)
 
 +        output_routed_experts = []
 +        if recv_obj.output_routed_experts is not None:
 +            output_routed_experts = [
-+                (
-+                    output_routed_experts.tolist()
-+                    if output_routed_experts is not None
-+                    else []
-+                )
++                output_routed_experts
 +                for output_routed_experts in recv_obj.output_routed_experts
 +            ]
          return BatchStrOutput(
              rids=recv_obj.rids,
              http_worker_ipcs=recv_obj.http_worker_ipcs,
-@@ -272,6 +282,7 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
+@@ -272,6 +278,7 @@ class DetokenizerManager(MultiHttpWorkerDetokenizerMixin):
              output_token_ids_logprobs_idx=recv_obj.output_token_ids_logprobs_idx,
              output_token_entropy_val=recv_obj.output_token_entropy_val,
              output_hidden_states=recv_obj.output_hidden_states,
@@ -1165,29 +1161,72 @@ index f8ebfc1f4..48b9a1a3b 100644
          return ResumeMemoryOccupationReqOutput()
 
      def check_weights(self: Scheduler, recv_req: CheckWeightsReqInput):
+diff --git a/python/sglang/srt/managers/tokenizer_communicator_mixin.py b/python/sglang/srt/managers/tokenizer_communicator_mixin.py
+index edbc52526..2cdc42755 100644
+--- a/python/sglang/srt/managers/tokenizer_communicator_mixin.py
++++ b/python/sglang/srt/managers/tokenizer_communicator_mixin.py
+@@ -421,6 +421,11 @@ class TokenizerCommunicatorMixin:
+                 result = (await self.update_weights_from_distributed_communicator(obj))[
+                     0
+                 ]
++                if result.success and obj.weight_version is not None:
++                    self._update_weight_version_if_provided(obj.weight_version)
++                    result.message += (
++                        f" Weight version updated to {obj.weight_version}."
++                    )
+                 return result.success, result.message
+
+         # This means that weight sync
+@@ -480,6 +485,11 @@ class TokenizerCommunicatorMixin:
+         async with self.is_pause_cond:
+             if self.is_pause:
+                 result = (await self.update_weights_from_tensor_communicator(obj))[0]
++                if result.success and obj.weight_version is not None:
++                    self._update_weight_version_if_provided(obj.weight_version)
++                    result.message += (
++                        f" Weight version updated to {obj.weight_version}."
++                    )
+                 return result.success, result.message
+
+         # This means that weight sync
 diff --git a/python/sglang/srt/managers/tokenizer_manager.py b/python/sglang/srt/managers/tokenizer_manager.py
-index b90cf0616..98d71d896 100644
+index b90cf0616..9b0992655 100644
 --- a/python/sglang/srt/managers/tokenizer_manager.py
 +++ b/python/sglang/srt/managers/tokenizer_manager.py
-@@ -888,6 +888,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
+@@ -20,6 +20,7 @@ import logging
+ import math
+ import os
+ import pickle
++import pybase64
+ import signal
+ import sys
+ import threading
+@@ -888,6 +889,7 @@ class TokenizerManager(TokenizerCommunicatorMixin):
                  session_params=session_params,
                  custom_logit_processor=obj.custom_logit_processor,
                  return_hidden_states=obj.return_hidden_states,
 +                return_routed_experts=obj.return_routed_experts,
                  data_parallel_rank=obj.data_parallel_rank,
                  priority=obj.priority,
                  extra_key=obj.extra_key,
-@@ -1621,6 +1622,9 @@ class TokenizerManager(TokenizerCommunicatorMixin):
+@@ -1621,6 +1623,16 @@ class TokenizerManager(TokenizerCommunicatorMixin):
              if getattr(recv_obj, "output_hidden_states", None):
                  meta_info["hidden_states"] = recv_obj.output_hidden_states[i]
 
 +            if getattr(recv_obj, "output_routed_experts", None):
-+                meta_info["routed_experts"] = recv_obj.output_routed_experts[i]
++                if recv_obj.output_routed_experts[i] is not None:
++                    # print(f"{recv_obj.output_routed_experts[i].shape=}, {recv_obj.output_routed_experts[i].dtype=}")
++                    # torch.save(recv_obj.output_routed_experts[i], f"/root/{recv_obj.output_routed_experts[i].shape[0]}.pt")
++                    meta_info["routed_experts"] = pybase64.b64encode(
++                        recv_obj.output_routed_experts[i].contiguous().numpy().tobytes(order="C")
++                    ).decode("ascii")
++                else:
++                    meta_info["routed_experts"] = None
 +
              if isinstance(recv_obj, BatchStrOutput):
                  state.text += recv_obj.output_strs[i]
                  if self.server_args.stream_output and state.obj.stream:
-@@ -1747,12 +1751,13 @@ class TokenizerManager(TokenizerCommunicatorMixin):
+@@ -1747,12 +1759,13 @@ class TokenizerManager(TokenizerCommunicatorMixin):
              return
 
          if len(recv_obj.input_token_logprobs_val) > 0:
@@ -1975,31 +2014,3 @@ index b3d72df05..ddfe0b178 100644
 
 
  @dataclass
-diff --git a/python/sglang/srt/managers/tokenizer_communicator_mixin.py b/python/sglang/srt/managers/tokenizer_communicator_mixin.py
-index edbc52526..2cdc42755 100644
---- a/python/sglang/srt/managers/tokenizer_communicator_mixin.py
-+++ b/python/sglang/srt/managers/tokenizer_communicator_mixin.py
-@@ -421,6 +421,11 @@ class TokenizerCommunicatorMixin:
-                 result = (await self.update_weights_from_distributed_communicator(obj))[
-                     0
-                 ]
-+                if result.success and obj.weight_version is not None:
-+                    self._update_weight_version_if_provided(obj.weight_version)
-+                    result.message += (
-+                        f" Weight version updated to {obj.weight_version}."
-+                    )
-                 return result.success, result.message
-
-         # This means that weight sync
-@@ -480,6 +485,11 @@ class TokenizerCommunicatorMixin:
-         async with self.is_pause_cond:
-             if self.is_pause:
-                 result = (await self.update_weights_from_tensor_communicator(obj))[0]
-+                if result.success and obj.weight_version is not None:
-+                    self._update_weight_version_if_provided(obj.weight_version)
-+                    result.message += (
-+                        f" Weight version updated to {obj.weight_version}."
-+                    )
-                 return result.success, result.message
-
-         # This means that weight sync

docker/version.txt

@@ -1 +1 @@
-nightly-dev-20251215a
+nightly-dev-20251216a

slime/rollout/sglang_rollout.py

@@ -7,6 +7,7 @@
 from typing import Any
 
 import numpy as np
+import pybase64
 import sglang_router
 from packaging.version import parse
 from tqdm import tqdm
@@ -186,8 +187,14 @@ async def generate(args: Namespace, sample: Sample, sampling_params: dict[str, A
         sample.weight_versions.append(output["meta_info"]["weight_version"])
 
     if "routed_experts" in output["meta_info"]:
-        assert len(output["meta_info"]["routed_experts"]) == len(sample.tokens) - 1
-        sample.rollout_routed_experts = np.array(output["meta_info"]["routed_experts"])
+        sample.rollout_routed_experts = np.frombuffer(
+            pybase64.b64decode(output["meta_info"]["routed_experts"].encode("ascii")),
+            dtype=np.int32,
+        ).reshape(
+            len(sample.tokens) - 1,
+            args.num_layers,
+            args.moe_router_topk,
+        )
 
     match output["meta_info"]["finish_reason"]["type"]:
         case "length":