[BugFix][MM]support VLLM_RANDOMIZE_DP_DUMMY_INPUTS (#30472)

Signed-off-by: Xingyu Liu <charlotteliu12x@gmail.com>
Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk>

vllm/v1/worker/gpu_model_runner.py

 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
+import functools
 import gc
 import itertools
 import time
@@ -3892,19 +3893,21 @@ class GPUModelRunner(
             return {}
 
     @contextmanager
-    def maybe_randomize_inputs(self, input_ids: torch.Tensor):
+    def maybe_randomize_inputs(
+        self, input_ids: torch.Tensor | None, inputs_embeds: torch.Tensor | None
+    ):
         """
         Randomize input_ids if VLLM_RANDOMIZE_DP_DUMMY_INPUTS is set.
         This is to help balance expert-selection
          - during profile_run
          - during DP rank dummy run
         """
+
         dp_size = self.vllm_config.parallel_config.data_parallel_size
         randomize_inputs = envs.VLLM_RANDOMIZE_DP_DUMMY_INPUTS and dp_size > 1
         if not randomize_inputs:
             yield
-        else:
-            import functools
+        elif input_ids is not None:
 
             @functools.cache
             def rand_input_ids() -> torch.Tensor:
@@ -3912,13 +3915,27 @@ class GPUModelRunner(
                     self.input_ids.gpu,
                     low=0,
                     high=self.model_config.get_vocab_size(),
-                    dtype=input_ids.dtype,
                 )
 
-            logger.debug_once("Randomizing dummy data for DP Rank")
+            logger.debug_once("Randomizing dummy input_ids for DP Rank")
             input_ids.copy_(rand_input_ids()[: input_ids.size(0)], non_blocking=True)
             yield
             input_ids.fill_(0)
+        else:
+
+            @functools.cache
+            def rand_inputs_embeds() -> torch.Tensor:
+                return torch.randn_like(
+                    self.inputs_embeds.gpu,
+                )
+
+            assert inputs_embeds is not None
+            logger.debug_once("Randomizing dummy inputs_embeds for DP Rank")
+            inputs_embeds.copy_(
+                rand_inputs_embeds()[: inputs_embeds.size(0)], non_blocking=True
+            )
+            yield
+            inputs_embeds.fill_(0)
 
     def _get_mm_dummy_batch(
         self,
@@ -4167,7 +4184,7 @@ class GPUModelRunner(
                     num_tokens_across_dp[:] = num_tokens_padded
 
             with (
-                self.maybe_randomize_inputs(input_ids),
+                self.maybe_randomize_inputs(input_ids, inputs_embeds),
                 set_forward_context(
                     attn_metadata,
                     self.vllm_config,